artificial intelligence extended essay

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The future of AI’s impact on society

As artificial intelligence continues its rapid evolution, what influence do humans have?

• Joanna J. Bryson

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The past decade, and particularly the past few years, has been transformative for artificial intelligence, not so much in terms of what we can do with this technology as what we are doing with it. Some place the advent of this era to 2007, with the introduction of smartphones. At its most essential, intelligence is just intelligence, whether artifact or animal. It is a form of computation, and as such, a transformation of information. The cornucopia of deeply personal information that resulted from the willful tethering of a huge portion of society to the internet has allowed us to pass immense explicit and implicit knowledge from human culture via human brains into digital form. Here we can not only use it to operate with human-like competence but also produce further knowledge and behavior by means of machine-based computation.

Joanna J. Bryson is an associate professor of computer science at the University of Bath.

For decades—even prior to the inception of the term—AI has aroused both fear and excitement as humanity contemplates creating machines in our image. This expectation that intelligent artifacts should by necessity be human-like artifacts blinded most of us to the important fact that we have been achieving AI for some time. While the breakthroughs in surpassing human ability at human pursuits, such as chess, make headlines, AI has been a standard part of the industrial repertoire since at least the 1980s. Then production-rule or “expert” systems became a standard technology for checking circuit boards and detecting credit card fraud. Similarly, machine-learning (ML) strategies like genetic algorithms have long been used for intractable computational problems, such as scheduling, and neural networks not only to model and understand human learning, but also for basic industrial control and monitoring.

In the 1990s, probabilistic and Bayesian methods revolutionized ML and opened the door to some of the most pervasive AI technologies now available: searching through massive troves of data. This search capacity included the ability to do semantic analysis of raw text, astonishingly enabling web users to find the documents they seek out of trillions of webpages just by typing only a few words.

AI is core to some of the most successful companies in history in terms of market capitalization—Apple, Alphabet, Microsoft, and Amazon. Along with information and communication technology (ICT) more generally, AI has revolutionized the ease with which people from all over the world can access knowledge, credit, and other benefits of contemporary global society. Such access has helped lead to massive reduction of global inequality and extreme poverty, for example by allowing farmers to know fair prices, the best crops, and giving them access to accurate weather predictions.

For decades, AI has aroused both fear and excitement as humanity contemplates creating machines in our image.

Having said this, academics, technologists, and the general public have raised a number of concerns that may indicate a need for down-regulation or constraint. As Brad Smith, the president of Microsoft recently asserted, “Information technology raises issues that go to the heart of fundamental human-rights protections like privacy and freedom of expression. These issues heighten responsibility for tech companies that create these products. In our view, they also call for thoughtful government regulation and for the development of norms around acceptable uses.”

Artificial intelligence is already changing society at a faster pace than we realize, but at the same time it is not as novel or unique in human experience as we are often led to imagine. Other artifactual entities, such as language and writing, corporations and governments, telecommunications and oil, have previously extended our capacities, altered our economies, and disrupted our social order—generally though not universally for the better. The evidence assumption that we are on average better off for our progress is ironically perhaps the greatest hurdle we currently need to overcome: sustainable living and reversing the collapse of biodiversity.

AI and ICT more generally may well require radical innovations in the way we govern, and particularly in the way we raise revenue for redistribution. We are faced with transnational wealth transfers through business innovations that have outstripped our capacity to measure or even identify the level of income generated. Further, this new currency of unknowable value is often personal data, and personal data gives those who hold it the immense power of prediction over the individuals it references.

But beyond the economic and governance challenges, we need to remember that AI first and foremost extends and enhances what it means to be human, and in particular our problem-solving capacities. Given ongoing global challenges such as security, sustainability, and reversing the collapse of biodiversity, such enhancements promise to continue to be of significant benefit, assuming we can establish good mechanisms for their regulation. Through a sensible portfolio of regulatory policies and agencies, we should continue to expand—and also to limit, as appropriate—the scope of potential AI applications.

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Artificial Intelligence Essay for Students and Children

500+ words essay on artificial intelligence.

Artificial Intelligence refers to the intelligence of machines. This is in contrast to the natural intelligence of humans and animals. With Artificial Intelligence, machines perform functions such as learning, planning, reasoning and problem-solving. Most noteworthy, Artificial Intelligence is the simulation of human intelligence by machines. It is probably the fastest-growing development in the World of technology and innovation . Furthermore, many experts believe AI could solve major challenges and crisis situations.

Types of Artificial Intelligence

First of all, the categorization of Artificial Intelligence is into four types. Arend Hintze came up with this categorization. The categories are as follows:

Type 1: Reactive machines – These machines can react to situations. A famous example can be Deep Blue, the IBM chess program. Most noteworthy, the chess program won against Garry Kasparov , the popular chess legend. Furthermore, such machines lack memory. These machines certainly cannot use past experiences to inform future ones. It analyses all possible alternatives and chooses the best one.

Type 2: Limited memory – These AI systems are capable of using past experiences to inform future ones. A good example can be self-driving cars. Such cars have decision making systems . The car makes actions like changing lanes. Most noteworthy, these actions come from observations. There is no permanent storage of these observations.

Type 3: Theory of mind – This refers to understand others. Above all, this means to understand that others have their beliefs, intentions, desires, and opinions. However, this type of AI does not exist yet.

Type 4: Self-awareness – This is the highest and most sophisticated level of Artificial Intelligence. Such systems have a sense of self. Furthermore, they have awareness, consciousness, and emotions. Obviously, such type of technology does not yet exist. This technology would certainly be a revolution .

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Applications of Artificial Intelligence

First of all, AI has significant use in healthcare. Companies are trying to develop technologies for quick diagnosis. Artificial Intelligence would efficiently operate on patients without human supervision. Such technological surgeries are already taking place. Another excellent healthcare technology is IBM Watson.

Artificial Intelligence in business would significantly save time and effort. There is an application of robotic automation to human business tasks. Furthermore, Machine learning algorithms help in better serving customers. Chatbots provide immediate response and service to customers.

AI can greatly increase the rate of work in manufacturing. Manufacture of a huge number of products can take place with AI. Furthermore, the entire production process can take place without human intervention. Hence, a lot of time and effort is saved.

Artificial Intelligence has applications in various other fields. These fields can be military , law , video games , government, finance, automotive, audit, art, etc. Hence, it’s clear that AI has a massive amount of different applications.

To sum it up, Artificial Intelligence looks all set to be the future of the World. Experts believe AI would certainly become a part and parcel of human life soon. AI would completely change the way we view our World. With Artificial Intelligence, the future seems intriguing and exciting.

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106 Artificial Intelligence Essay Topics & Samples

In a research paper or any other assignment about AI, there are many topics and questions to consider. To help you out, our experts have provided a list of 76 titles , along with artificial intelligence essay examples, for your consideration.

💾 Top 10 Artificial Intelligence Essay Topics

🏆 best essay topics on artificial intelligence, 🖱️ interesting artificial intelligence topics for essays, 🖥️ good ai essay titles, ❓ artificial intelligence research questions.

• AI and Human Intelligence.
• Computer Vision.
• Future of AI Technology.
• Machine Learning.
• AI in Daily Life.
• Impact of Deep Learning.
• Natural Language Processing.
• Threats in Robotics.
• Reinforcement Learning.
• Ethics of Artificial Intelligence.
• The Problem of Artificial Intelligence The introduction of new approaches to work and rest triggered the reconsideration of traditional values and promoted the growth of a certain style of life characterized by the mass use of innovations and their integration […]
• Artificial Intelligence: Positive or Negative Innovation? He argues that while humans will still be in charge of a few aspects of life in the near future, their control will be reduced due to the development of artificial intelligence.
• Artificial Intelligence: The Helper or the Threat? To conclude, artificial intelligence development is a problem that leaves nobody indifferent as it is closely associated with the future of the humanity.
• Artificial Intelligence and Humans Co-Existence Some strategies to address these challenges exist; however, the strict maintenance of key areas under human control is the only valid solution to ensure people’s safety.
• Artificial Intelligence Advantages and Disadvantages In the early years of the field, AI scientists sort to fully duplicate the human capacities of thought and language on the digital computer.
• Autonomous Controller Robotics: The Future of Robots The middle level is the Coordination level which interfaces the actions of the top and lower level s in the architecture.
• Application of Artificial Intelligence in Business The connection of AI and the business strategy of an organization is displayed through the ability to use its algorithm for achieving competitive advantage and maintaining it.
• Artificial Intelligence Managing Human Life Although the above examples explain how humans can use AI to perform a wide range of tasks, it is necessary for stakeholders to control and manage the replication of human intelligence.
• Artificial Intelligence in the Documentary “Transcendent Man” The artificial intelligence is becoming a threat to the existence of humanity since these machines are slowly but steadily replacing the roles of mankind in all spheres of life.
• Artificial Intelligence: Pros and Cons Artificial intelligence, or robots, one of the most scandalous and brilliant inventions of the XX century, causing people’s concern for the world safety, has become one of the leading branches of the modern science, which […]
• Artificial Intelligence and People-Focused Cities The aim of this research is to examine the relationship between the application of effective AI technologies to enhance urban planning approaches and the development of modern smart and people focused cities.
• Artificial Intelligence and Related Social Threats It may be expressed in a variety of ways, from peaceful attempts to attract attention to the issue to violent and criminal activities.
• What Progress Has Been Made With Artificial Intelligence? According to Dunjko and Briegel, AI contains a variety of fields and concepts, including the necessity to understand human capacities, abstract all the aspects of work, and realize similar aptitudes in machines.
• Artificial Intelligence: A Systems Approach That is to say, limitations on innovations should be applied to the degree to which robots and machine intelligence can be autonomous.
• Turing Test: Real and Artificial Intelligence The answers provided by the computer is consistent with that of human and the assessor can hardly guess whether the answer is from the machine or human.
• Saudi Arabia Information Technology: Artificial Intelligence The systems could therefore not fulfill the expectations of people who first thought that they would relieve managers and professionals of the need to make certain types of decisions.
• Artificial Intelligence and Video Games Development Therefore, in contrast to settings that have been designed for agents only, StarCraft and Blizzard can offer DeepMind an enormous amount of data gathered from playing time which teaches the AI to perform a set […]
• Artificial Intelligence System for Smart Energy Consumption The proposed energy consumption saver is an innovative technology that aims to increase the efficiency of energy consumption in residential buildings, production and commercial facilities, and other types of structures.
• Artificial Intelligence Reducing Costs in Hospitality Industry One of the factors that contribute to increased costs in the hospitality industry is the inability of management to cope with changing consumer demands.
• Artificial Intelligence in Healthcare Delivery and Control Side Effects This report presents the status of AI in healthcare delivery and the motivations of deploying the technology in human services, information types analysed by AI frameworks, components that empower clinical outcomes and disease types.
• Artificial Intelligence for Diabetes: Project Experiences At the end of this reflective practice report, I plan to recognize my strengths and weaknesses in terms of team-working on the project about AI in diabetic retinopathy detection and want to determine my future […]
• Artificial Intelligence Company’s Economic Indicators On the other hand, it is vital to mention that if an artificial intelligence company has come of age and it is generally at the level of a large corporation, it can swiftly maneuver the […]
• Artificial Intelligence and Future of Sales It is assumed that one of the major factors that currently affect and will be affecting sales in the future is the artificial intelligence.
• Apple’s Company Announcement on Artificial Intelligence This development in Apple’s software is a reflection of the social construction of technology theory based on how the needs of the user impact how technological development is oriented.
• Artificial Intelligence Threat to Human Activities Despite the fictional and speculative nature of the majority of implications connected to the supposed threat that the artificial intelligence poses to mankind and the resulting low credibility ascribed to all such suggestions, at least […]
• Artificial Intelligence and the Associated Threats Artificial Intelligence, commonly referred to as AI refers to a branch of computer science that deals with the establishment of computer software and programs aimed at the change of the way many people carry out […]
• Non Experts: Artificial Intelligence Regardless of speed and the complexity of mathematical problems that they can solve, all that they do is to accept some input and generate desired output. This system is akin to that found in a […]
• Exploring the Impact of Artificial Intelligence: Prediction versus Judgment
• Maintaining Project Networks in Automated Artificial Intelligence Planning
• The Effects Artificial Intelligence Has Had On Society And On Business
• What Role Will Artificial Intelligence Actually Play in Human Affairs in the Next Few Decades?
• How Artificial Intelligence and Machine Learning Can Impact Market Design
• The Use of Artificial Intelligence in Today’s Technological Devices
• The Correlation of Artificial Intelligence and the Invention of Modern Day Computers and Programming Languages
• How Artificial Intelligence Will Affect Social Media Monitoring
• Artificial Intelligence and Neural Network: The Future of Computing and Computer Programming
• The Foundations and History of Artificial Intelligence
• Comment on Prediction, Judgment, and Complexity: A Theory of Decision Making and Artificial Intelligence
• Artificial Intelligence And Law: A Review Of The Role Of Correctness In The General Data Protection Regulation Framework
• Artificial Intelligence: Compared To The Human Mind’s Capacity For Reasoning And Learning
• A Comparison Between Two Predictive Models of Artificial Intelligence
• Artificial Intelligence as a Positive and Negative Factor in Global Risk
• Search Applications, Java, and Complexity of Symbolic Artificial Intelligence
• Integrating Ethical Values and Economic Value to Steer Progress in Artificial Intelligence
• Computational Modeling of an Economy Using Elements of Artificial Intelligence
• The growth of Artificial Intelligence and its relevance to The Matrix
• The Impact of Artificial Intelligence on Innovation
• The Potential Negative Impact of Artificial Intelligence in the Future
• An Overview of the Principles of Artificial Intelligence and the Views of Noam Chomsky
• How Artificial Intelligence Technology can be Used to Treat Diabetes
• Artificial Intelligence and the UK Labour Market: Questions, Methods and a Call for a Systematic Approach to Information Gathering
• An Overview of Artificial Intelligence and Its Future Disadvantage to Our Modern Society
• Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions
• Comparing the Different Views of John Searle and Alan Turing on the Debate on Artificial Intelligence (AI)
• A Comparison of Cognitive Ability and Information Processing in Artificial Intelligence
• Improvisation Of Unmanned Aerial Vehicles Using Artificial Intelligence
• Artificial Intelligence and Its Implications for Income Distribution and Unemployment
• The Application of Artificial Intelligence in Real-Time Strategy Games
• Advancement in Technology Can Someday Bring Artificial Intelligence to Reality
• Artificial Intelligence Based Congestion Control Mechanism Via Bayesian Networks Under Opportunistic
• Artificial Intelligence Is Lost in the Woods a Conscious Mind Will Never Be Built Out of Software
• An Analysis of the Concept of Artificial Intelligence in Relation to Business
• The Different Issues Concerning the Creation of Artificial Intelligence
• Traditional Philosophical Problems Surrounding Induction Relating to Artificial Intelligence
• The Importance of Singularity and Artificial Intelligence to People
• Man Machine Collaboration And The Rise Of Artificial Intelligence
• What Are the Ethical Challenges for Companies Working In Artificial Intelligence?
• Will Artificial Intelligence Have a Progressive or Retrogressive Impact on Our Society?
• Why Won’t Artificial Intelligence Dominate the Future?
• Will Artificial Intelligence Overpower Human Beings?
• How Does Artificial Intelligence Affect the Retail Industry?
• What Can Artificial Intelligence Offer Coral Reef Managers?
• Will Artificial Intelligence Replace Computational Economists Any Time Soon?
• How Can Artificial Intelligence and Machine Learning Impact Market Design?
• Can Artificial Intelligence Lead to a More Sustainable Society?
• Will Artificial Intelligence Replace Humans at Job?
• How Can Artificial Intelligence Help Us?
• How Will Artificial Intelligence Affect the Job Industry in the Future?
• Can Artificial Intelligence Become Smarter Than Humans?
• How Would You Define Artificial Intelligence?
• Should Artificial Intelligence Have Human Rights?
• How Do Artificial Intelligence and Siri Operate in Regards to Language?
• What Are the Impacts of Artificial Intelligence on the Creative Industries?
• How Can Artificial Intelligence Help Us Understand Human Creativity?
• When Will Artificial Intelligence Defeat Human Intelligence?
• How Can Artificial Intelligence Technology Be Used to Treat Diabetes?
• Will Artificial Intelligence Replace Mankind?
• How Will Artificial Intelligence Affect Social Media Monitoring?
• Can Artificial Intelligence Change the Way in Which Companies Recruit, Train, Develop, and Manage Human Resources in Workplace?
• How Does Mary Shelley’s Depiction Show the Threats of Artificial Intelligence?
• Why Must Artificial Intelligence Be Regulated?
• Will Artificial Intelligence Devices Become Human’s Best Friend?
• Does Artificial Intelligence Exist?
• Can Artificial Intelligence Be Dangerous?
• Why Do We Need Artificial Intelligence?
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Essays on Artificial Intelligence

Writing an essay on artificial intelligence is not just an academic exercise; it's a chance to explore the cutting-edge innovations and the profound impact AI has on our lives. For students looking to delve deeper into this topic, utilizing the best AI tools for students can provide a significant edge in crafting a well-researched and analytical essay. 🚀 So, get ready to unlock the potential of AI with your words!

Artificial Intelligence Essay Topics for "Artificial Intelligence" 📝

Choosing the right topic is key to writing a compelling essay. Here's how to pick the perfect one:

Artificial Intelligence Argumentative Essay 🤨

Argumentative AI essays require you to take a stance on AI-related issues. Here are ten thought-provoking topics:

• 1. The ethical implications of AI in autonomous weaponry.
• 2. Should AI be granted legal personhood and rights?
• 3. Analyze the impact of AI on the job market and employment prospects.
• 4. The role of AI in addressing climate change and environmental challenges.
• 5. Discuss the risks and benefits of AI in healthcare and medical diagnostics.
• 6. AI's impact on privacy and surveillance in modern society.
• 7. Evaluate the use of AI in education and personalized learning.
• 8. The role of AI in improving cybersecurity and data protection.
• 9. Discuss the potential biases and discrimination in AI algorithms.
• 10. AI and its implications for creativity and the arts.
• 11. The Ethical Implications of Programming Bias into Artificial Intelligence

Artificial Intelligence Cause and Effect Essay 🤯

Dive into cause and effect relationships in the AI realm with these topics:

• 1. Explore how AI-powered virtual assistants have changed communication habits.
• 2. Analyze the effects of AI-driven predictive policing on crime rates.
• 3. Discuss how AI-driven healthcare advancements have extended human lifespans.
• 4. The consequences of AI-powered autonomous vehicles on transportation and traffic safety.
• 5. Investigate the impact of AI algorithms on social media echo chambers and polarization.
• 6. The influence of AI-driven personalized marketing on consumer behavior.
• 7. Explore how AI has revolutionized the entertainment industry and storytelling.
• 8. Analyze the cause and effect of AI's role in financial markets and investment strategies.
• 9. Discuss the effects of AI on reducing energy consumption and sustainable living.
• 10. The consequences of AI in aiding scientific research and discovery.

Artificial Intelligence Opinion Essay 😌

Express your personal views and interpretations on AI through these essay topics:

• 1. Share your opinion on the potential dangers of superintelligent AI.
• 2. Discuss your perspective on AI's role in enhancing human capabilities.
• 3. Express your thoughts on the future of work in an AI-dominated world.
• 4. Debate the significance of AI in addressing global challenges like pandemics.
• 5. Share your views on the ethical responsibilities of AI developers and researchers.
• 6. Discuss the impact of AI on human creativity and innovation.
• 7. Express your opinion on AI's influence on education and personalized learning.
• 8. Debate the ethics of AI in decision-making, such as self-driving car dilemmas.
• 9. Share your perspective on AI's potential to bridge the digital divide and promote equity.
• 10. Discuss your favorite AI-related invention or innovation and its implications.

Artificial Intelligence Informative Essay 🧐

Inform and educate your readers with these informative AI essay topics:

• 1. Explore the history and evolution of artificial intelligence.
• 2. Provide an in-depth analysis of popular AI technologies like deep learning and neural networks.
• 3. Investigate the significance of AI in autonomous robotics and space exploration.
• 4. Analyze the role of AI in natural language processing and language translation.
• 5. Examine the applications of AI in climate modeling and environmental conservation.
• 6. Explore the cultural and societal impacts of AI in science fiction literature and films.
• 7. Provide insights into the ethics of AI in medical decision-making and diagnosis.
• 8. Analyze the potential for AI in disaster response and emergency management.
• 9. Discuss the role of AI in enhancing cybersecurity and threat detection.
• 10. Examine the future trends and possibilities of AI in various industries.
• 11. Ethical Implications of AI in Healthcare: Patient Privacy
• 12. Impact of AI on Government Services: Study of Role in UPSC Exam Process

Artificial Intelligence Essay Example 📄

Artificial intelligence thesis statement examples 📜.

Here are five examples of strong thesis statements for your AI essay:

• 1. "The rapid advancements in artificial intelligence present both unprecedented opportunities and ethical dilemmas, as we navigate the journey toward an AI-driven future."
• 2. "In analyzing the impact of AI on healthcare, we unveil a transformative force that promises to revolutionize medical diagnosis and treatment, but also raises concerns about data privacy and security."
• 3. "The development of superintelligent AI systems demands careful consideration of ethical frameworks to ensure their responsible and beneficial integration into society."
• 4. "Artificial intelligence is not a replacement for human creativity but a powerful tool that amplifies our capabilities, ushering in an era of unprecedented innovation and discovery."
• 5. "AI-driven autonomous vehicles represent a technological leap that holds the potential to reshape transportation, reduce accidents, and increase accessibility, but also raises questions about liability and safety."

Artificial Intelligence Essay Introduction Examples 🚀

Here are three captivating introduction paragraphs to begin your essay:

• 1. "In a world driven by data and algorithms, artificial intelligence has emerged as both a beacon of innovation and a source of profound ethical contemplation. As we embark on this essay journey into the realm of AI, we peel back the layers of silicon and software to explore the implications, promises, and challenges of our AI-driven future."
• 2. "Imagine a world where machines not only assist us but also think, learn, and adapt. The rise of artificial intelligence has ignited a conversation that transcends technology—it delves into the very essence of human potential and the responsibilities we bear as creators. Join us as we navigate the AI landscape, one algorithm at a time."
• 3. "In an era marked by digital transformations and the ubiquity of smart devices, artificial intelligence stands as the sentinel of change. As we step into the world of AI analysis, we are confronted with a paradox: the immense power of machines and the ethical dilemmas they pose. Together, let's dissect the AI phenomenon, from its inception to its potential to shape the destiny of humanity."

Artificial Intelligence Conclusion Examples 🌟

Conclude your essay with impact using these examples:

• 1. "As we draw the curtains on this AI exploration, we stand at the intersection of innovation and ethics. Artificial intelligence, with all its wonders and complexities, challenges us to not only harness its power for progress but also to ensure its responsible and ethical use. The journey continues, and the conversation evolves as we navigate the evolving landscape of AI."
• 2. "In the closing frame of our AI analysis, we reflect on the ever-expanding possibilities and responsibilities that AI brings to our doorstep. The pages of this essay mark a beginning—a call to action. Together, we have explored the AI landscape, and the future is now in our hands, waiting for our choices to shape it."
• 3. "As the AI narrative reaches its conclusion, we find ourselves at the crossroads of human ingenuity and artificial intelligence. The journey has been both enlightening and thought-provoking, reminding us that the future of AI is a collaborative endeavor, guided by ethics, curiosity, and a shared vision of a better world."

Ai's Prospects and Its Impact on Humanity

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Artificial Intelligence in Security and Warfare

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Artificial Intelligence

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Ethical Issues in Using Ai Technology Today

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Artificial intelligence (AI) refers to the intellectual capabilities exhibited by machines, contrasting with the innate intelligence observed in living beings, such as animals and humans.

The inception of artificial intelligence research as an academic field can be traced back to its establishment in 1956. It was during the renowned Dartmouth conference of the same year that artificial intelligence acquired its distinctive name, definitive purpose, initial accomplishments, and notable pioneers, thereby earning its reputation as the birthplace of AI. The esteemed figures of Marvin Minsky and John McCarthy are widely recognized as the founding fathers of this discipline.

Early pioneers such as John McCarthy, Marvin Minsky, and Allen Newell played instrumental roles in shaping the foundations of AI research. In the following years after its original inception, AI witnessed both periods of optimism and periods of skepticism, as researchers explored different approaches and techniques. Notable breakthroughs include the development of expert systems in the 1970s, which aimed to replicate human knowledge and reasoning, and the emergence of machine learning algorithms in the 1980s and 1990s. The turn of the 21st century witnessed significant advancements in AI, with the rise of big data, powerful computing technologies, and deep learning algorithms. This led to remarkable achievements in areas such as natural language processing, computer vision, and autonomous systems.

There are four types of artificial intelligence: reactive machines, limited memory, theory of mind and self-awareness.

Healthcare: AI assists in medical diagnosis, drug discovery, personalized treatment plans, and analyzing medical images. Finance: AI is used for automated trading, fraud detection, risk assessment, and customer service through chatbots. Transportation: AI powers autonomous vehicles, traffic optimization, logistics, and supply chain management. Entertainment: AI contributes to recommendation systems, AI-generated music and art, virtual reality experiences, and content creation. Cybersecurity: AI helps in detecting and preventing cyber threats and enhancing network security. Agriculture: AI optimizes farming practices, crop management, and precision agriculture. Education: AI enables personalized learning, adaptive assessments, and intelligent tutoring systems. Natural Language Processing: AI facilitates language translation, voice assistants, chatbots, and sentiment analysis. Robotics: AI powers robots in various applications, such as manufacturing, healthcare, and exploration. Environmental Conservation: AI aids in environmental monitoring, wildlife protection, and climate modeling.

John McCarthy: Coined the term "artificial intelligence" and organized the Dartmouth Conference in 1956, which is considered the birth of AI as an academic discipline. Marvin Minsky: A cognitive scientist and AI pioneer, Minsky co-founded the Massachusetts Institute of Technology's AI Laboratory and made notable contributions to robotics and cognitive psychology. Geoffrey Hinton: Renowned for his work on neural networks and deep learning, Hinton's research has greatly advanced the field of AI and revolutionized areas such as image and speech recognition. Andrew Ng: An influential figure in the field of AI, Ng co-founded Google Brain, led the development of the deep learning framework TensorFlow, and has made significant contributions to machine learning algorithms. Fei-Fei Li: A prominent researcher in computer vision and AI, Li has made groundbreaking contributions to image recognition and has been a strong advocate for responsible and ethical AI development.. Demis Hassabis: Co-founder of DeepMind, a leading AI research company, Hassabis has made notable contributions to areas such as deep reinforcement learning and has led the development of groundbreaking AI systems. Elon Musk: Although primarily known for his role in space exploration and electric vehicles, Musk has also made notable contributions to AI through his involvement in companies like OpenAI and Neuralink, advocating for AI safety and ethics.

1. According to a report by IDC, global spending on AI systems is expected to reach $98.4 billion in 2023, indicating a significant increase from the $37.5 billion spent in 2019. 2. The job market for AI professionals is thriving. LinkedIn's 2021 Emerging Jobs Report listed AI specialist as one of the top emerging jobs, with a 74% annual growth rate over the past four years. 3. AI-powered chatbots are revolutionizing customer service. A study by Oracle found that 80% of businesses plan to use chatbots by 2022. Furthermore, 58% of consumers have already interacted with chatbots for customer support, indicating the growing acceptance and adoption of AI in enhancing customer experiences. 4. McKinsey Global Institute estimates that by 2030, automation and AI technologies could contribute to a global economic impact of $13 trillion. 5. The healthcare industry is leveraging AI for improved patient care. A study published in the journal Nature Medicine reported that an AI model was able to detect breast cancer with an accuracy of 94.5%, outperforming human radiologists.

The topic of artificial intelligence (AI) holds immense importance in today's world, making it an intriguing subject to explore in an essay. AI has revolutionized multiple facets of human life, ranging from technology and business to healthcare and transportation. Understanding its significance is crucial for comprehending the potential and impact of this rapidly evolving field. Firstly, AI has the power to reshape industries and transform economies. It enables automation, streamlines processes, and enhances efficiency, leading to increased productivity and economic growth. Moreover, AI advancements have the potential to address complex societal challenges, such as healthcare accessibility, environmental sustainability, and resource management. Secondly, AI raises ethical considerations and socio-economic implications. Discussions on privacy, bias, job displacement, and AI's role in decision-making become essential for navigating its responsible implementation. Examining the ethical dimensions of AI fosters critical thinking and encourages the development of guidelines and regulations to ensure its ethical use. Lastly, exploring AI allows us to envision the future possibilities and risks associated with this technology. It sparks discussions on the boundaries of machine intelligence, the potential for sentient AI, and the impact on human existence. By studying AI, we gain insights into technological progress, its limitations, and the responsibilities associated with harnessing its potential.

1. Russell, S. J., & Norvig, P. (2016). Artificial Intelligence: A Modern Approach (3rd ed.). Prentice Hall. 2. Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. 3. Kurzweil, R. (2005). The Singularity Is Near: When Humans Transcend Biology. Viking. 4. Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford University Press. 5. Chollet, F. (2017). Deep Learning with Python. Manning Publications. 6. Domingos, P. (2018). The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World. Basic Books. 7. Ng, A. (2017). Machine Learning Yearning. deeplearning.ai. 8. Marcus, G. (2018). Rebooting AI: Building Artificial Intelligence We Can Trust. Vintage. 9. Winfield, A. (2018). Robotics: A Very Short Introduction. Oxford University Press. 10. Shalev-Shwartz, S., & Ben-David, S. (2014). Understanding Machine Learning: From Theory to Algorithms. Cambridge University Press.

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Forget about artificial intelligence, extended intelligence is the future

Last year, I participated in a discussion of The Human Use of Human Beings , Norbert Weiner’s groundbreaking book on cybernetics theory. Out of that grew what I now consider a manifesto against the growing singularity movement, which posits that artificial intelligence, or AI, will supersede and eventually displace us humans.

The notion of singularity – which includes the idea that AI will supercede humans with its exponential growth, making everything we humans have done and will do insignificant – is a religion created mostly by people who have designed and successfully deployed computation to solve problems previously considered impossibly complex for machines.

They have found a perfect partner in digital computation, a seemingly knowable, controllable, machine-based system of thinking and creating that is rapidly increasing in its ability to harness and process complexity and, in the process, bestowing wealth and power on those who have mastered it.

In Silicon Valley, the combination of groupthink and the financial success of this cult of technology has created a feedback loop, lacking in self-regulation (although #techwontbuild, #metoo and #timesup are forcing some reflection).

On an S-curve or a bell curve, the beginning of the slope looks a lot like an exponential curve. According to systems-dynamics people, however, an exponential curve shows a positive feedback curve without limits, self-reinforcing and dangerous.

In exponential curves, Singularitarians see super-intelligence and abundance. Most people outside the Singularity bubble believe that natural systems behave like S-curves, where systems respond and self-regulate. When a pandemic has run its course, for example, its spread slows and the world settles into a new equilibrium. The world may not be in the same state as before the pandemic or other runaway change, but the notion of singularity – especially as some sort of saviour or judgment day that will allow us to transcend the messy, mortal suffering of our human existence – is fundamentally a flawed one.

By Matt Simon

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By Carlton Reid

This sort of reductionist thinking isn’t new. When the psychologist BF Skinner discovered the principle of reinforcement and was able to describe it, we designed education around his theories.

Scientists who study learning now, however, know that behaviourist approaches like Skinner’s only work for a narrow range of learning – but many schools nonetheless continue to rely on drill and practice and other pillars of reinforcement. Take, as another example, the field of eugenics, which incorrectly over-simplified the role of genetics in society. This movement helped fuel the Nazi genocide by providing a reductionist scientific view that we could “fix humanity” by manually pushing natural selection. The echoes of that horror exist today, making taboo almost any research that would link genetics with, say, intelligence.

While one of the key drivers of science is to elegantly explain the complex and increase our ability to understand, we must also remember what Albert Einstein said: “Everything should be made as simple as possible, but no simpler.” We need to embrace the unknowability – the irreducibility – of the real world that artists, biologists and those who work in the messy world of liberal arts and humanities are familiar and comfortable with.

Today, it is obvious that most of our problems – for instance, climate change, poverty, chronic disease or modern terrorism – are the result of our pursuit of the Singularity dream: exponential growth. They are extremely complex problems produced by tools used to solve past problems, such as endlessly pushing to increase productivity or to exert control over systems that have, in fact, become too complex to control.

In order to effectively respond to the significant scientific challenges of our times, I believe we must respect the many interconnected, complex, self-adaptive systems across scales and dimensions that cannot be fully known by or separated from observer and designer.

In other words, we are all participants in multiple evolutionary systems with different fitness landscapes at different scales, from our microbes to our individual identities to society and our species. Individuals themselves are systems composed of systems of systems, such as the cells in our bodies that behave more like system-level designers than we do. As Kevin Slavin says in his 2016 essay Design as Participation : “You’re not stuck in traffic, you are traffic.”

Biological evolution of individual species (genetic evolution) has been driven by reproduction and survival, instilling in us goals and yearnings to procreate and grow. That system continually evolves to regulate growth, increase diversity and complexity, and enhance its own resilience, adaptability and sustainability. We could call it “participant design” – design of systems as and by participants – that is more akin to the increase of a flourishing function, where flourishing is a measure of vigour and health rather than scale, money or power.

Machines with emergent intelligence, however, have discernibly different goals and methodologies. As we introduce such machines into complex adaptive systems such as the economy, the environment or health, I see them augmenting, not replacing, individual humans and, more importantly, augmenting such systems.

Here is where the problematic formulation of “artificial intelligence” as defined by many Singularitarians becomes evident, as it suggests forms, goals and methods that stand outside of interaction with other complex adaptive systems.

Instead of thinking about machine intelligence in terms of humans vs machines, we should consider the system that integrates humans and machines – not artificial intelligence but extended intelligence. Instead of trying to control or design or even understand systems, it is more important to design systems that participate as responsible, aware and robust elements of even more complex systems.

We must question and adapt our own purpose and sensibilities as observers and designers within systems for a much more humble approach: humility over control.

Joi Ito is director or MIT’s Media Lab. This an edited excerpt of an essay originally published in the MIT’s Journal of Design and Science and which became a call for responses.

This article was originally published by WIRED UK

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How artificial intelligence is transforming the world

Subscribe to the center for technology innovation newsletter, darrell m. west and darrell m. west senior fellow - center for technology innovation , douglas dillon chair in governmental studies john r. allen john r. allen.

April 24, 2018

Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making—and already it is transforming every walk of life. In this report, Darrell West and John Allen discuss AI’s application across a variety of sectors, address issues in its development, and offer recommendations for getting the most out of AI while still protecting important human values.

Table of Contents I. Qualities of artificial intelligence II. Applications in diverse sectors III. Policy, regulatory, and ethical issues IV. Recommendations V. Conclusion

• 49 min read

Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it. 1 A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations.

Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Our hope through this comprehensive overview is to explain AI to an audience of policymakers, opinion leaders, and interested observers, and demonstrate how AI already is altering the world and raising important questions for society, the economy, and governance.

In this paper, we discuss novel applications in finance, national security, health care, criminal justice, transportation, and smart cities, and address issues such as data access problems, algorithmic bias, AI ethics and transparency, and legal liability for AI decisions. We contrast the regulatory approaches of the U.S. and European Union, and close by making a number of recommendations for getting the most out of AI while still protecting important human values. 2

In order to maximize AI benefits, we recommend nine steps for going forward:

• Encourage greater data access for researchers without compromising users’ personal privacy,
• invest more government funding in unclassified AI research,
• promote new models of digital education and AI workforce development so employees have the skills needed in the 21 st -century economy,
• create a federal AI advisory committee to make policy recommendations,
• engage with state and local officials so they enact effective policies,
• regulate broad AI principles rather than specific algorithms,
• take bias complaints seriously so AI does not replicate historic injustice, unfairness, or discrimination in data or algorithms,
• maintain mechanisms for human oversight and control, and
• penalize malicious AI behavior and promote cybersecurity.

Qualities of artificial intelligence

Although there is no uniformly agreed upon definition, AI generally is thought to refer to “machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention.” 3  According to researchers Shubhendu and Vijay, these software systems “make decisions which normally require [a] human level of expertise” and help people anticipate problems or deal with issues as they come up. 4 As such, they operate in an intentional, intelligent, and adaptive manner.

Intentionality

Artificial intelligence algorithms are designed to make decisions, often using real-time data. They are unlike passive machines that are capable only of mechanical or predetermined responses. Using sensors, digital data, or remote inputs, they combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data. With massive improvements in storage systems, processing speeds, and analytic techniques, they are capable of tremendous sophistication in analysis and decisionmaking.

Artificial intelligence is already altering the world and raising important questions for society, the economy, and governance.

Intelligence

AI generally is undertaken in conjunction with machine learning and data analytics. 5 Machine learning takes data and looks for underlying trends. If it spots something that is relevant for a practical problem, software designers can take that knowledge and use it to analyze specific issues. All that is required are data that are sufficiently robust that algorithms can discern useful patterns. Data can come in the form of digital information, satellite imagery, visual information, text, or unstructured data.

Adaptability

AI systems have the ability to learn and adapt as they make decisions. In the transportation area, for example, semi-autonomous vehicles have tools that let drivers and vehicles know about upcoming congestion, potholes, highway construction, or other possible traffic impediments. Vehicles can take advantage of the experience of other vehicles on the road, without human involvement, and the entire corpus of their achieved “experience” is immediately and fully transferable to other similarly configured vehicles. Their advanced algorithms, sensors, and cameras incorporate experience in current operations, and use dashboards and visual displays to present information in real time so human drivers are able to make sense of ongoing traffic and vehicular conditions. And in the case of fully autonomous vehicles, advanced systems can completely control the car or truck, and make all the navigational decisions.

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Applications in diverse sectors

AI is not a futuristic vision, but rather something that is here today and being integrated with and deployed into a variety of sectors. This includes fields such as finance, national security, health care, criminal justice, transportation, and smart cities. There are numerous examples where AI already is making an impact on the world and augmenting human capabilities in significant ways. 6

One of the reasons for the growing role of AI is the tremendous opportunities for economic development that it presents. A project undertaken by PriceWaterhouseCoopers estimated that “artificial intelligence technologies could increase global GDP by $15.7 trillion, a full 14%, by 2030.” 7 That includes advances of $7 trillion in China, $3.7 trillion in North America, $1.8 trillion in Northern Europe, $1.2 trillion for Africa and Oceania, $0.9 trillion in the rest of Asia outside of China, $0.7 trillion in Southern Europe, and $0.5 trillion in Latin America. China is making rapid strides because it has set a national goal of investing $150 billion in AI and becoming the global leader in this area by 2030.

Meanwhile, a McKinsey Global Institute study of China found that “AI-led automation can give the Chinese economy a productivity injection that would add 0.8 to 1.4 percentage points to GDP growth annually, depending on the speed of adoption.” 8 Although its authors found that China currently lags the United States and the United Kingdom in AI deployment, the sheer size of its AI market gives that country tremendous opportunities for pilot testing and future development.

Investments in financial AI in the United States tripled between 2013 and 2014 to a total of $12.2 billion. 9 According to observers in that sector, “Decisions about loans are now being made by software that can take into account a variety of finely parsed data about a borrower, rather than just a credit score and a background check.” 10 In addition, there are so-called robo-advisers that “create personalized investment portfolios, obviating the need for stockbrokers and financial advisers.” 11 These advances are designed to take the emotion out of investing and undertake decisions based on analytical considerations, and make these choices in a matter of minutes.

A prominent example of this is taking place in stock exchanges, where high-frequency trading by machines has replaced much of human decisionmaking. People submit buy and sell orders, and computers match them in the blink of an eye without human intervention. Machines can spot trading inefficiencies or market differentials on a very small scale and execute trades that make money according to investor instructions. 12 Powered in some places by advanced computing, these tools have much greater capacities for storing information because of their emphasis not on a zero or a one, but on “quantum bits” that can store multiple values in each location. 13 That dramatically increases storage capacity and decreases processing times.

Fraud detection represents another way AI is helpful in financial systems. It sometimes is difficult to discern fraudulent activities in large organizations, but AI can identify abnormalities, outliers, or deviant cases requiring additional investigation. That helps managers find problems early in the cycle, before they reach dangerous levels. 14

National security

AI plays a substantial role in national defense. Through its Project Maven, the American military is deploying AI “to sift through the massive troves of data and video captured by surveillance and then alert human analysts of patterns or when there is abnormal or suspicious activity.” 15 According to Deputy Secretary of Defense Patrick Shanahan, the goal of emerging technologies in this area is “to meet our warfighters’ needs and to increase [the] speed and agility [of] technology development and procurement.” 16

Artificial intelligence will accelerate the traditional process of warfare so rapidly that a new term has been coined: hyperwar.

The big data analytics associated with AI will profoundly affect intelligence analysis, as massive amounts of data are sifted in near real time—if not eventually in real time—thereby providing commanders and their staffs a level of intelligence analysis and productivity heretofore unseen. Command and control will similarly be affected as human commanders delegate certain routine, and in special circumstances, key decisions to AI platforms, reducing dramatically the time associated with the decision and subsequent action. In the end, warfare is a time competitive process, where the side able to decide the fastest and move most quickly to execution will generally prevail. Indeed, artificially intelligent intelligence systems, tied to AI-assisted command and control systems, can move decision support and decisionmaking to a speed vastly superior to the speeds of the traditional means of waging war. So fast will be this process, especially if coupled to automatic decisions to launch artificially intelligent autonomous weapons systems capable of lethal outcomes, that a new term has been coined specifically to embrace the speed at which war will be waged: hyperwar.

While the ethical and legal debate is raging over whether America will ever wage war with artificially intelligent autonomous lethal systems, the Chinese and Russians are not nearly so mired in this debate, and we should anticipate our need to defend against these systems operating at hyperwar speeds. The challenge in the West of where to position “humans in the loop” in a hyperwar scenario will ultimately dictate the West’s capacity to be competitive in this new form of conflict. 17

Just as AI will profoundly affect the speed of warfare, the proliferation of zero day or zero second cyber threats as well as polymorphic malware will challenge even the most sophisticated signature-based cyber protection. This forces significant improvement to existing cyber defenses. Increasingly, vulnerable systems are migrating, and will need to shift to a layered approach to cybersecurity with cloud-based, cognitive AI platforms. This approach moves the community toward a “thinking” defensive capability that can defend networks through constant training on known threats. This capability includes DNA-level analysis of heretofore unknown code, with the possibility of recognizing and stopping inbound malicious code by recognizing a string component of the file. This is how certain key U.S.-based systems stopped the debilitating “WannaCry” and “Petya” viruses.

Preparing for hyperwar and defending critical cyber networks must become a high priority because China, Russia, North Korea, and other countries are putting substantial resources into AI. In 2017, China’s State Council issued a plan for the country to “build a domestic industry worth almost $150 billion” by 2030. 18 As an example of the possibilities, the Chinese search firm Baidu has pioneered a facial recognition application that finds missing people. In addition, cities such as Shenzhen are providing up to $1 million to support AI labs. That country hopes AI will provide security, combat terrorism, and improve speech recognition programs. 19 The dual-use nature of many AI algorithms will mean AI research focused on one sector of society can be rapidly modified for use in the security sector as well. 20

Health care

AI tools are helping designers improve computational sophistication in health care. For example, Merantix is a German company that applies deep learning to medical issues. It has an application in medical imaging that “detects lymph nodes in the human body in Computer Tomography (CT) images.” 21 According to its developers, the key is labeling the nodes and identifying small lesions or growths that could be problematic. Humans can do this, but radiologists charge $100 per hour and may be able to carefully read only four images an hour. If there were 10,000 images, the cost of this process would be $250,000, which is prohibitively expensive if done by humans.

What deep learning can do in this situation is train computers on data sets to learn what a normal-looking versus an irregular-appearing lymph node is. After doing that through imaging exercises and honing the accuracy of the labeling, radiological imaging specialists can apply this knowledge to actual patients and determine the extent to which someone is at risk of cancerous lymph nodes. Since only a few are likely to test positive, it is a matter of identifying the unhealthy versus healthy node.

AI has been applied to congestive heart failure as well, an illness that afflicts 10 percent of senior citizens and costs $35 billion each year in the United States. AI tools are helpful because they “predict in advance potential challenges ahead and allocate resources to patient education, sensing, and proactive interventions that keep patients out of the hospital.” 22

Criminal justice

AI is being deployed in the criminal justice area. The city of Chicago has developed an AI-driven “Strategic Subject List” that analyzes people who have been arrested for their risk of becoming future perpetrators. It ranks 400,000 people on a scale of 0 to 500, using items such as age, criminal activity, victimization, drug arrest records, and gang affiliation. In looking at the data, analysts found that youth is a strong predictor of violence, being a shooting victim is associated with becoming a future perpetrator, gang affiliation has little predictive value, and drug arrests are not significantly associated with future criminal activity. 23

Judicial experts claim AI programs reduce human bias in law enforcement and leads to a fairer sentencing system. R Street Institute Associate Caleb Watney writes:

Empirically grounded questions of predictive risk analysis play to the strengths of machine learning, automated reasoning and other forms of AI. One machine-learning policy simulation concluded that such programs could be used to cut crime up to 24.8 percent with no change in jailing rates, or reduce jail populations by up to 42 percent with no increase in crime rates. 24

However, critics worry that AI algorithms represent “a secret system to punish citizens for crimes they haven’t yet committed. The risk scores have been used numerous times to guide large-scale roundups.” 25 The fear is that such tools target people of color unfairly and have not helped Chicago reduce the murder wave that has plagued it in recent years.

Despite these concerns, other countries are moving ahead with rapid deployment in this area. In China, for example, companies already have “considerable resources and access to voices, faces and other biometric data in vast quantities, which would help them develop their technologies.” 26 New technologies make it possible to match images and voices with other types of information, and to use AI on these combined data sets to improve law enforcement and national security. Through its “Sharp Eyes” program, Chinese law enforcement is matching video images, social media activity, online purchases, travel records, and personal identity into a “police cloud.” This integrated database enables authorities to keep track of criminals, potential law-breakers, and terrorists. 27 Put differently, China has become the world’s leading AI-powered surveillance state.

Transportation

Transportation represents an area where AI and machine learning are producing major innovations. Research by Cameron Kerry and Jack Karsten of the Brookings Institution has found that over $80 billion was invested in autonomous vehicle technology between August 2014 and June 2017. Those investments include applications both for autonomous driving and the core technologies vital to that sector. 28

Autonomous vehicles—cars, trucks, buses, and drone delivery systems—use advanced technological capabilities. Those features include automated vehicle guidance and braking, lane-changing systems, the use of cameras and sensors for collision avoidance, the use of AI to analyze information in real time, and the use of high-performance computing and deep learning systems to adapt to new circumstances through detailed maps. 29

Light detection and ranging systems (LIDARs) and AI are key to navigation and collision avoidance. LIDAR systems combine light and radar instruments. They are mounted on the top of vehicles that use imaging in a 360-degree environment from a radar and light beams to measure the speed and distance of surrounding objects. Along with sensors placed on the front, sides, and back of the vehicle, these instruments provide information that keeps fast-moving cars and trucks in their own lane, helps them avoid other vehicles, applies brakes and steering when needed, and does so instantly so as to avoid accidents.

Advanced software enables cars to learn from the experiences of other vehicles on the road and adjust their guidance systems as weather, driving, or road conditions change. This means that software is the key—not the physical car or truck itself.

Since these cameras and sensors compile a huge amount of information and need to process it instantly to avoid the car in the next lane, autonomous vehicles require high-performance computing, advanced algorithms, and deep learning systems to adapt to new scenarios. This means that software is the key, not the physical car or truck itself. 30 Advanced software enables cars to learn from the experiences of other vehicles on the road and adjust their guidance systems as weather, driving, or road conditions change. 31

Ride-sharing companies are very interested in autonomous vehicles. They see advantages in terms of customer service and labor productivity. All of the major ride-sharing companies are exploring driverless cars. The surge of car-sharing and taxi services—such as Uber and Lyft in the United States, Daimler’s Mytaxi and Hailo service in Great Britain, and Didi Chuxing in China—demonstrate the opportunities of this transportation option. Uber recently signed an agreement to purchase 24,000 autonomous cars from Volvo for its ride-sharing service. 32

However, the ride-sharing firm suffered a setback in March 2018 when one of its autonomous vehicles in Arizona hit and killed a pedestrian. Uber and several auto manufacturers immediately suspended testing and launched investigations into what went wrong and how the fatality could have occurred. 33 Both industry and consumers want reassurance that the technology is safe and able to deliver on its stated promises. Unless there are persuasive answers, this accident could slow AI advancements in the transportation sector.

Smart cities

Metropolitan governments are using AI to improve urban service delivery. For example, according to Kevin Desouza, Rashmi Krishnamurthy, and Gregory Dawson:

The Cincinnati Fire Department is using data analytics to optimize medical emergency responses. The new analytics system recommends to the dispatcher an appropriate response to a medical emergency call—whether a patient can be treated on-site or needs to be taken to the hospital—by taking into account several factors, such as the type of call, location, weather, and similar calls. 34

Since it fields 80,000 requests each year, Cincinnati officials are deploying this technology to prioritize responses and determine the best ways to handle emergencies. They see AI as a way to deal with large volumes of data and figure out efficient ways of responding to public requests. Rather than address service issues in an ad hoc manner, authorities are trying to be proactive in how they provide urban services.

Cincinnati is not alone. A number of metropolitan areas are adopting smart city applications that use AI to improve service delivery, environmental planning, resource management, energy utilization, and crime prevention, among other things. For its smart cities index, the magazine Fast Company ranked American locales and found Seattle, Boston, San Francisco, Washington, D.C., and New York City as the top adopters. Seattle, for example, has embraced sustainability and is using AI to manage energy usage and resource management. Boston has launched a “City Hall To Go” that makes sure underserved communities receive needed public services. It also has deployed “cameras and inductive loops to manage traffic and acoustic sensors to identify gun shots.” San Francisco has certified 203 buildings as meeting LEED sustainability standards. 35

Through these and other means, metropolitan areas are leading the country in the deployment of AI solutions. Indeed, according to a National League of Cities report, 66 percent of American cities are investing in smart city technology. Among the top applications noted in the report are “smart meters for utilities, intelligent traffic signals, e-governance applications, Wi-Fi kiosks, and radio frequency identification sensors in pavement.” 36

Policy, regulatory, and ethical issues

These examples from a variety of sectors demonstrate how AI is transforming many walks of human existence. The increasing penetration of AI and autonomous devices into many aspects of life is altering basic operations and decisionmaking within organizations, and improving efficiency and response times.

At the same time, though, these developments raise important policy, regulatory, and ethical issues. For example, how should we promote data access? How do we guard against biased or unfair data used in algorithms? What types of ethical principles are introduced through software programming, and how transparent should designers be about their choices? What about questions of legal liability in cases where algorithms cause harm? 37

The increasing penetration of AI into many aspects of life is altering decisionmaking within organizations and improving efficiency. At the same time, though, these developments raise important policy, regulatory, and ethical issues.

Data access problems

The key to getting the most out of AI is having a “data-friendly ecosystem with unified standards and cross-platform sharing.” AI depends on data that can be analyzed in real time and brought to bear on concrete problems. Having data that are “accessible for exploration” in the research community is a prerequisite for successful AI development. 38

According to a McKinsey Global Institute study, nations that promote open data sources and data sharing are the ones most likely to see AI advances. In this regard, the United States has a substantial advantage over China. Global ratings on data openness show that U.S. ranks eighth overall in the world, compared to 93 for China. 39

But right now, the United States does not have a coherent national data strategy. There are few protocols for promoting research access or platforms that make it possible to gain new insights from proprietary data. It is not always clear who owns data or how much belongs in the public sphere. These uncertainties limit the innovation economy and act as a drag on academic research. In the following section, we outline ways to improve data access for researchers.

Biases in data and algorithms

In some instances, certain AI systems are thought to have enabled discriminatory or biased practices. 40 For example, Airbnb has been accused of having homeowners on its platform who discriminate against racial minorities. A research project undertaken by the Harvard Business School found that “Airbnb users with distinctly African American names were roughly 16 percent less likely to be accepted as guests than those with distinctly white names.” 41

Racial issues also come up with facial recognition software. Most such systems operate by comparing a person’s face to a range of faces in a large database. As pointed out by Joy Buolamwini of the Algorithmic Justice League, “If your facial recognition data contains mostly Caucasian faces, that’s what your program will learn to recognize.” 42 Unless the databases have access to diverse data, these programs perform poorly when attempting to recognize African-American or Asian-American features.

Many historical data sets reflect traditional values, which may or may not represent the preferences wanted in a current system. As Buolamwini notes, such an approach risks repeating inequities of the past:

The rise of automation and the increased reliance on algorithms for high-stakes decisions such as whether someone get insurance or not, your likelihood to default on a loan or somebody’s risk of recidivism means this is something that needs to be addressed. Even admissions decisions are increasingly automated—what school our children go to and what opportunities they have. We don’t have to bring the structural inequalities of the past into the future we create. 43

AI ethics and transparency

Algorithms embed ethical considerations and value choices into program decisions. As such, these systems raise questions concerning the criteria used in automated decisionmaking. Some people want to have a better understanding of how algorithms function and what choices are being made. 44

In the United States, many urban schools use algorithms for enrollment decisions based on a variety of considerations, such as parent preferences, neighborhood qualities, income level, and demographic background. According to Brookings researcher Jon Valant, the New Orleans–based Bricolage Academy “gives priority to economically disadvantaged applicants for up to 33 percent of available seats. In practice, though, most cities have opted for categories that prioritize siblings of current students, children of school employees, and families that live in school’s broad geographic area.” 45 Enrollment choices can be expected to be very different when considerations of this sort come into play.

Depending on how AI systems are set up, they can facilitate the redlining of mortgage applications, help people discriminate against individuals they don’t like, or help screen or build rosters of individuals based on unfair criteria. The types of considerations that go into programming decisions matter a lot in terms of how the systems operate and how they affect customers. 46

For these reasons, the EU is implementing the General Data Protection Regulation (GDPR) in May 2018. The rules specify that people have “the right to opt out of personally tailored ads” and “can contest ‘legal or similarly significant’ decisions made by algorithms and appeal for human intervention” in the form of an explanation of how the algorithm generated a particular outcome. Each guideline is designed to ensure the protection of personal data and provide individuals with information on how the “black box” operates. 47

Legal liability

There are questions concerning the legal liability of AI systems. If there are harms or infractions (or fatalities in the case of driverless cars), the operators of the algorithm likely will fall under product liability rules. A body of case law has shown that the situation’s facts and circumstances determine liability and influence the kind of penalties that are imposed. Those can range from civil fines to imprisonment for major harms. 48 The Uber-related fatality in Arizona will be an important test case for legal liability. The state actively recruited Uber to test its autonomous vehicles and gave the company considerable latitude in terms of road testing. It remains to be seen if there will be lawsuits in this case and who is sued: the human backup driver, the state of Arizona, the Phoenix suburb where the accident took place, Uber, software developers, or the auto manufacturer. Given the multiple people and organizations involved in the road testing, there are many legal questions to be resolved.

In non-transportation areas, digital platforms often have limited liability for what happens on their sites. For example, in the case of Airbnb, the firm “requires that people agree to waive their right to sue, or to join in any class-action lawsuit or class-action arbitration, to use the service.” By demanding that its users sacrifice basic rights, the company limits consumer protections and therefore curtails the ability of people to fight discrimination arising from unfair algorithms. 49 But whether the principle of neutral networks holds up in many sectors is yet to be determined on a widespread basis.

Recommendations

In order to balance innovation with basic human values, we propose a number of recommendations for moving forward with AI. This includes improving data access, increasing government investment in AI, promoting AI workforce development, creating a federal advisory committee, engaging with state and local officials to ensure they enact effective policies, regulating broad objectives as opposed to specific algorithms, taking bias seriously as an AI issue, maintaining mechanisms for human control and oversight, and penalizing malicious behavior and promoting cybersecurity.

Improving data access

The United States should develop a data strategy that promotes innovation and consumer protection. Right now, there are no uniform standards in terms of data access, data sharing, or data protection. Almost all the data are proprietary in nature and not shared very broadly with the research community, and this limits innovation and system design. AI requires data to test and improve its learning capacity. 50 Without structured and unstructured data sets, it will be nearly impossible to gain the full benefits of artificial intelligence.

In general, the research community needs better access to government and business data, although with appropriate safeguards to make sure researchers do not misuse data in the way Cambridge Analytica did with Facebook information. There is a variety of ways researchers could gain data access. One is through voluntary agreements with companies holding proprietary data. Facebook, for example, recently announced a partnership with Stanford economist Raj Chetty to use its social media data to explore inequality. 51 As part of the arrangement, researchers were required to undergo background checks and could only access data from secured sites in order to protect user privacy and security.

In the U.S., there are no uniform standards in terms of data access, data sharing, or data protection. Almost all the data are proprietary in nature and not shared very broadly with the research community, and this limits innovation and system design.

Google long has made available search results in aggregated form for researchers and the general public. Through its “Trends” site, scholars can analyze topics such as interest in Trump, views about democracy, and perspectives on the overall economy. 52 That helps people track movements in public interest and identify topics that galvanize the general public.

Twitter makes much of its tweets available to researchers through application programming interfaces, commonly referred to as APIs. These tools help people outside the company build application software and make use of data from its social media platform. They can study patterns of social media communications and see how people are commenting on or reacting to current events.

In some sectors where there is a discernible public benefit, governments can facilitate collaboration by building infrastructure that shares data. For example, the National Cancer Institute has pioneered a data-sharing protocol where certified researchers can query health data it has using de-identified information drawn from clinical data, claims information, and drug therapies. That enables researchers to evaluate efficacy and effectiveness, and make recommendations regarding the best medical approaches, without compromising the privacy of individual patients.

There could be public-private data partnerships that combine government and business data sets to improve system performance. For example, cities could integrate information from ride-sharing services with its own material on social service locations, bus lines, mass transit, and highway congestion to improve transportation. That would help metropolitan areas deal with traffic tie-ups and assist in highway and mass transit planning.

Some combination of these approaches would improve data access for researchers, the government, and the business community, without impinging on personal privacy. As noted by Ian Buck, the vice president of NVIDIA, “Data is the fuel that drives the AI engine. The federal government has access to vast sources of information. Opening access to that data will help us get insights that will transform the U.S. economy.” 53 Through its Data.gov portal, the federal government already has put over 230,000 data sets into the public domain, and this has propelled innovation and aided improvements in AI and data analytic technologies. 54 The private sector also needs to facilitate research data access so that society can achieve the full benefits of artificial intelligence.

Increase government investment in AI

According to Greg Brockman, the co-founder of OpenAI, the U.S. federal government invests only $1.1 billion in non-classified AI technology. 55 That is far lower than the amount being spent by China or other leading nations in this area of research. That shortfall is noteworthy because the economic payoffs of AI are substantial. In order to boost economic development and social innovation, federal officials need to increase investment in artificial intelligence and data analytics. Higher investment is likely to pay for itself many times over in economic and social benefits. 56

Promote digital education and workforce development

As AI applications accelerate across many sectors, it is vital that we reimagine our educational institutions for a world where AI will be ubiquitous and students need a different kind of training than they currently receive. Right now, many students do not receive instruction in the kinds of skills that will be needed in an AI-dominated landscape. For example, there currently are shortages of data scientists, computer scientists, engineers, coders, and platform developers. These are skills that are in short supply; unless our educational system generates more people with these capabilities, it will limit AI development.

For these reasons, both state and federal governments have been investing in AI human capital. For example, in 2017, the National Science Foundation funded over 6,500 graduate students in computer-related fields and has launched several new initiatives designed to encourage data and computer science at all levels from pre-K to higher and continuing education. 57 The goal is to build a larger pipeline of AI and data analytic personnel so that the United States can reap the full advantages of the knowledge revolution.

But there also needs to be substantial changes in the process of learning itself. It is not just technical skills that are needed in an AI world but skills of critical reasoning, collaboration, design, visual display of information, and independent thinking, among others. AI will reconfigure how society and the economy operate, and there needs to be “big picture” thinking on what this will mean for ethics, governance, and societal impact. People will need the ability to think broadly about many questions and integrate knowledge from a number of different areas.

One example of new ways to prepare students for a digital future is IBM’s Teacher Advisor program, utilizing Watson’s free online tools to help teachers bring the latest knowledge into the classroom. They enable instructors to develop new lesson plans in STEM and non-STEM fields, find relevant instructional videos, and help students get the most out of the classroom. 58 As such, they are precursors of new educational environments that need to be created.

Create a federal AI advisory committee

Federal officials need to think about how they deal with artificial intelligence. As noted previously, there are many issues ranging from the need for improved data access to addressing issues of bias and discrimination. It is vital that these and other concerns be considered so we gain the full benefits of this emerging technology.

In order to move forward in this area, several members of Congress have introduced the “Future of Artificial Intelligence Act,” a bill designed to establish broad policy and legal principles for AI. It proposes the secretary of commerce create a federal advisory committee on the development and implementation of artificial intelligence. The legislation provides a mechanism for the federal government to get advice on ways to promote a “climate of investment and innovation to ensure the global competitiveness of the United States,” “optimize the development of artificial intelligence to address the potential growth, restructuring, or other changes in the United States workforce,” “support the unbiased development and application of artificial intelligence,” and “protect the privacy rights of individuals.” 59

Among the specific questions the committee is asked to address include the following: competitiveness, workforce impact, education, ethics training, data sharing, international cooperation, accountability, machine learning bias, rural impact, government efficiency, investment climate, job impact, bias, and consumer impact. The committee is directed to submit a report to Congress and the administration 540 days after enactment regarding any legislative or administrative action needed on AI.

This legislation is a step in the right direction, although the field is moving so rapidly that we would recommend shortening the reporting timeline from 540 days to 180 days. Waiting nearly two years for a committee report will certainly result in missed opportunities and a lack of action on important issues. Given rapid advances in the field, having a much quicker turnaround time on the committee analysis would be quite beneficial.

Engage with state and local officials

States and localities also are taking action on AI. For example, the New York City Council unanimously passed a bill that directed the mayor to form a taskforce that would “monitor the fairness and validity of algorithms used by municipal agencies.” 60 The city employs algorithms to “determine if a lower bail will be assigned to an indigent defendant, where firehouses are established, student placement for public schools, assessing teacher performance, identifying Medicaid fraud and determine where crime will happen next.” 61

According to the legislation’s developers, city officials want to know how these algorithms work and make sure there is sufficient AI transparency and accountability. In addition, there is concern regarding the fairness and biases of AI algorithms, so the taskforce has been directed to analyze these issues and make recommendations regarding future usage. It is scheduled to report back to the mayor on a range of AI policy, legal, and regulatory issues by late 2019.

Some observers already are worrying that the taskforce won’t go far enough in holding algorithms accountable. For example, Julia Powles of Cornell Tech and New York University argues that the bill originally required companies to make the AI source code available to the public for inspection, and that there be simulations of its decisionmaking using actual data. After criticism of those provisions, however, former Councilman James Vacca dropped the requirements in favor of a task force studying these issues. He and other city officials were concerned that publication of proprietary information on algorithms would slow innovation and make it difficult to find AI vendors who would work with the city. 62 It remains to be seen how this local task force will balance issues of innovation, privacy, and transparency.

Regulate broad objectives more than specific algorithms

The European Union has taken a restrictive stance on these issues of data collection and analysis. 63 It has rules limiting the ability of companies from collecting data on road conditions and mapping street views. Because many of these countries worry that people’s personal information in unencrypted Wi-Fi networks are swept up in overall data collection, the EU has fined technology firms, demanded copies of data, and placed limits on the material collected. 64 This has made it more difficult for technology companies operating there to develop the high-definition maps required for autonomous vehicles.

The GDPR being implemented in Europe place severe restrictions on the use of artificial intelligence and machine learning. According to published guidelines, “Regulations prohibit any automated decision that ‘significantly affects’ EU citizens. This includes techniques that evaluates a person’s ‘performance at work, economic situation, health, personal preferences, interests, reliability, behavior, location, or movements.’” 65 In addition, these new rules give citizens the right to review how digital services made specific algorithmic choices affecting people.

By taking a restrictive stance on issues of data collection and analysis, the European Union is putting its manufacturers and software designers at a significant disadvantage to the rest of the world.

If interpreted stringently, these rules will make it difficult for European software designers (and American designers who work with European counterparts) to incorporate artificial intelligence and high-definition mapping in autonomous vehicles. Central to navigation in these cars and trucks is tracking location and movements. Without high-definition maps containing geo-coded data and the deep learning that makes use of this information, fully autonomous driving will stagnate in Europe. Through this and other data protection actions, the European Union is putting its manufacturers and software designers at a significant disadvantage to the rest of the world.

It makes more sense to think about the broad objectives desired in AI and enact policies that advance them, as opposed to governments trying to crack open the “black boxes” and see exactly how specific algorithms operate. Regulating individual algorithms will limit innovation and make it difficult for companies to make use of artificial intelligence.

Take biases seriously

Bias and discrimination are serious issues for AI. There already have been a number of cases of unfair treatment linked to historic data, and steps need to be undertaken to make sure that does not become prevalent in artificial intelligence. Existing statutes governing discrimination in the physical economy need to be extended to digital platforms. That will help protect consumers and build confidence in these systems as a whole.

For these advances to be widely adopted, more transparency is needed in how AI systems operate. Andrew Burt of Immuta argues, “The key problem confronting predictive analytics is really transparency. We’re in a world where data science operations are taking on increasingly important tasks, and the only thing holding them back is going to be how well the data scientists who train the models can explain what it is their models are doing.” 66

Maintaining mechanisms for human oversight and control

Some individuals have argued that there needs to be avenues for humans to exercise oversight and control of AI systems. For example, Allen Institute for Artificial Intelligence CEO Oren Etzioni argues there should be rules for regulating these systems. First, he says, AI must be governed by all the laws that already have been developed for human behavior, including regulations concerning “cyberbullying, stock manipulation or terrorist threats,” as well as “entrap[ping] people into committing crimes.” Second, he believes that these systems should disclose they are automated systems and not human beings. Third, he states, “An A.I. system cannot retain or disclose confidential information without explicit approval from the source of that information.” 67 His rationale is that these tools store so much data that people have to be cognizant of the privacy risks posed by AI.

In the same vein, the IEEE Global Initiative has ethical guidelines for AI and autonomous systems. Its experts suggest that these models be programmed with consideration for widely accepted human norms and rules for behavior. AI algorithms need to take into effect the importance of these norms, how norm conflict can be resolved, and ways these systems can be transparent about norm resolution. Software designs should be programmed for “nondeception” and “honesty,” according to ethics experts. When failures occur, there must be mitigation mechanisms to deal with the consequences. In particular, AI must be sensitive to problems such as bias, discrimination, and fairness. 68

A group of machine learning experts claim it is possible to automate ethical decisionmaking. Using the trolley problem as a moral dilemma, they ask the following question: If an autonomous car goes out of control, should it be programmed to kill its own passengers or the pedestrians who are crossing the street? They devised a “voting-based system” that asked 1.3 million people to assess alternative scenarios, summarized the overall choices, and applied the overall perspective of these individuals to a range of vehicular possibilities. That allowed them to automate ethical decisionmaking in AI algorithms, taking public preferences into account. 69 This procedure, of course, does not reduce the tragedy involved in any kind of fatality, such as seen in the Uber case, but it provides a mechanism to help AI developers incorporate ethical considerations in their planning.

Penalize malicious behavior and promote cybersecurity

As with any emerging technology, it is important to discourage malicious treatment designed to trick software or use it for undesirable ends. 70 This is especially important given the dual-use aspects of AI, where the same tool can be used for beneficial or malicious purposes. The malevolent use of AI exposes individuals and organizations to unnecessary risks and undermines the virtues of the emerging technology. This includes behaviors such as hacking, manipulating algorithms, compromising privacy and confidentiality, or stealing identities. Efforts to hijack AI in order to solicit confidential information should be seriously penalized as a way to deter such actions. 71

In a rapidly changing world with many entities having advanced computing capabilities, there needs to be serious attention devoted to cybersecurity. Countries have to be careful to safeguard their own systems and keep other nations from damaging their security. 72 According to the U.S. Department of Homeland Security, a major American bank receives around 11 million calls a week at its service center. In order to protect its telephony from denial of service attacks, it uses a “machine learning-based policy engine [that] blocks more than 120,000 calls per month based on voice firewall policies including harassing callers, robocalls and potential fraudulent calls.” 73 This represents a way in which machine learning can help defend technology systems from malevolent attacks.

To summarize, the world is on the cusp of revolutionizing many sectors through artificial intelligence and data analytics. There already are significant deployments in finance, national security, health care, criminal justice, transportation, and smart cities that have altered decisionmaking, business models, risk mitigation, and system performance. These developments are generating substantial economic and social benefits.

The world is on the cusp of revolutionizing many sectors through artificial intelligence, but the way AI systems are developed need to be better understood due to the major implications these technologies will have for society as a whole.

Yet the manner in which AI systems unfold has major implications for society as a whole. It matters how policy issues are addressed, ethical conflicts are reconciled, legal realities are resolved, and how much transparency is required in AI and data analytic solutions. 74 Human choices about software development affect the way in which decisions are made and the manner in which they are integrated into organizational routines. Exactly how these processes are executed need to be better understood because they will have substantial impact on the general public soon, and for the foreseeable future. AI may well be a revolution in human affairs, and become the single most influential human innovation in history.

Note: We appreciate the research assistance of Grace Gilberg, Jack Karsten, Hillary Schaub, and Kristjan Tomasson on this project.

The Brookings Institution is a nonprofit organization devoted to independent research and policy solutions. Its mission is to conduct high-quality, independent research and, based on that research, to provide innovative, practical recommendations for policymakers and the public. The conclusions and recommendations of any Brookings publication are solely those of its author(s), and do not reflect the views of the Institution, its management, or its other scholars.

Support for this publication was generously provided by Amazon. Brookings recognizes that the value it provides is in its absolute commitment to quality, independence, and impact. Activities supported by its donors reflect this commitment. 

John R. Allen is a member of the Board of Advisors of Amida Technology and on the Board of Directors of Spark Cognition. Both companies work in fields discussed in this piece.

• Thomas Davenport, Jeff Loucks, and David Schatsky, “Bullish on the Business Value of Cognitive” (Deloitte, 2017), p. 3 (www2.deloitte.com/us/en/pages/deloitte-analytics/articles/cognitive-technology-adoption-survey.html).
• Luke Dormehl, Thinking Machines: The Quest for Artificial Intelligence—and Where It’s Taking Us Next (New York: Penguin–TarcherPerigee, 2017).
• Shubhendu and Vijay, “Applicability of Artificial Intelligence in Different Fields of Life.”
• Andrew McAfee and Erik Brynjolfsson, Machine Platform Crowd: Harnessing Our Digital Future (New York: Norton, 2017).
• Portions of this paper draw on Darrell M. West, The Future of Work: Robots, AI, and Automation , Brookings Institution Press, 2018.
• PriceWaterhouseCoopers, “Sizing the Prize: What’s the Real Value of AI for Your Business and How Can You Capitalise?” 2017.
• Dominic Barton, Jonathan Woetzel, Jeongmin Seong, and Qinzheng Tian, “Artificial Intelligence: Implications for China” (New York: McKinsey Global Institute, April 2017), p. 1.
• Nathaniel Popper, “Stocks and Bots,” New York Times Magazine , February 28, 2016.
• Michael Lewis, Flash Boys: A Wall Street Revolt (New York: Norton, 2015).
• Cade Metz, “In Quantum Computing Race, Yale Professors Battle Tech Giants,” New York Times , November 14, 2017, p. B3.
• Executive Office of the President, “Artificial Intelligence, Automation, and the Economy,” December 2016, pp. 27-28.
• Christian Davenport, “Future Wars May Depend as Much on Algorithms as on Ammunition, Report Says,” Washington Post , December 3, 2017.
• John R. Allen and Amir Husain, “On Hyperwar,” Naval Institute Proceedings , July 17, 2017, pp. 30-36.
• Paul Mozur, “China Sets Goal to Lead in Artificial Intelligence,” New York Times , July 21, 2017, p. B1.
• Paul Mozur and John Markoff, “Is China Outsmarting American Artificial Intelligence?” New York Times , May 28, 2017.
• Economist , “America v China: The Battle for Digital Supremacy,” March 15, 2018.
• Rasmus Rothe, “Applying Deep Learning to Real-World Problems,” Medium , May 23, 2017.
• Eric Horvitz, “Reflections on the Status and Future of Artificial Intelligence,” Testimony before the U.S. Senate Subcommittee on Space, Science, and Competitiveness, November 30, 2016, p. 5.
• Jeff Asher and Rob Arthur, “Inside the Algorithm That Tries to Predict Gun Violence in Chicago,” New York Times Upshot , June 13, 2017.
• Caleb Watney, “It’s Time for our Justice System to Embrace Artificial Intelligence,” TechTank (blog), Brookings Institution, July 20, 2017.
• Asher and Arthur, “Inside the Algorithm That Tries to Predict Gun Violence in Chicago.”
• Paul Mozur and Keith Bradsher, “China’s A.I. Advances Help Its Tech Industry, and State Security,” New York Times , December 3, 2017.
• Simon Denyer, “China’s Watchful Eye,” Washington Post , January 7, 2018.
• Cameron Kerry and Jack Karsten, “Gauging Investment in Self-Driving Cars,” Brookings Institution, October 16, 2017.
• Portions of this section are drawn from Darrell M. West, “Driverless Cars in China, Europe, Japan, Korea, and the United States,” Brookings Institution, September 2016.
• Yuming Ge, Xiaoman Liu, Libo Tang, and Darrell M. West, “Smart Transportation in China and the United States,” Center for Technology Innovation, Brookings Institution, December 2017.
• Peter Holley, “Uber Signs Deal to Buy 24,000 Autonomous Vehicles from Volvo,” Washington Post , November 20, 2017.
• Daisuke Wakabayashi, “Self-Driving Uber Car Kills Pedestrian in Arizona, Where Robots Roam,” New York Times , March 19, 2018.
• Kevin Desouza, Rashmi Krishnamurthy, and Gregory Dawson, “Learning from Public Sector Experimentation with Artificial Intelligence,” TechTank (blog), Brookings Institution, June 23, 2017.
• Boyd Cohen, “The 10 Smartest Cities in North America,” Fast Company , November 14, 2013.
• Teena Maddox, “66% of US Cities Are Investing in Smart City Technology,” TechRepublic , November 6, 2017.
• Osonde Osoba and William Welser IV, “The Risks of Artificial Intelligence to Security and the Future of Work” (Santa Monica, Calif.: RAND Corp., December 2017) (www.rand.org/pubs/perspectives/PE237.html).
• Ibid., p. 7.
• Dominic Barton, Jonathan Woetzel, Jeongmin Seong, and Qinzheng Tian, “Artificial Intelligence: Implications for China” (New York: McKinsey Global Institute, April 2017), p. 7.
• Executive Office of the President, “Preparing for the Future of Artificial Intelligence,” October 2016, pp. 30-31.
• Elaine Glusac, “As Airbnb Grows, So Do Claims of Discrimination,” New York Times , June 21, 2016.
• “Joy Buolamwini,” Bloomberg Businessweek , July 3, 2017, p. 80.
• Mark Purdy and Paul Daugherty, “Why Artificial Intelligence is the Future of Growth,” Accenture, 2016.
• Jon Valant, “Integrating Charter Schools and Choice-Based Education Systems,” Brown Center Chalkboard blog, Brookings Institution, June 23, 2017.
• Tucker, “‘A White Mask Worked Better.’”
• Cliff Kuang, “Can A.I. Be Taught to Explain Itself?” New York Times Magazine , November 21, 2017.
• Yale Law School Information Society Project, “Governing Machine Learning,” September 2017.
• Katie Benner, “Airbnb Vows to Fight Racism, But Its Users Can’t Sue to Prompt Fairness,” New York Times , June 19, 2016.
• Executive Office of the President, “Artificial Intelligence, Automation, and the Economy” and “Preparing for the Future of Artificial Intelligence.”
• Nancy Scolar, “Facebook’s Next Project: American Inequality,” Politico , February 19, 2018.
• Darrell M. West, “What Internet Search Data Reveals about Donald Trump’s First Year in Office,” Brookings Institution policy report, January 17, 2018.
• Ian Buck, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” February 14, 2018.
• Keith Nakasone, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Greg Brockman, “The Dawn of Artificial Intelligence,” Testimony before U.S. Senate Subcommittee on Space, Science, and Competitiveness, November 30, 2016.
• Amir Khosrowshahi, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” February 14, 2018.
• James Kurose, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Stephen Noonoo, “Teachers Can Now Use IBM’s Watson to Search for Free Lesson Plans,” EdSurge , September 13, 2017.
• Congress.gov, “H.R. 4625 FUTURE of Artificial Intelligence Act of 2017,” December 12, 2017.
• Elizabeth Zima, “Could New York City’s AI Transparency Bill Be a Model for the Country?” Government Technology , January 4, 2018.
• Julia Powles, “New York City’s Bold, Flawed Attempt to Make Algorithms Accountable,” New Yorker , December 20, 2017.
• Sheera Frenkel, “Tech Giants Brace for Europe’s New Data Privacy Rules,” New York Times , January 28, 2018.
• Claire Miller and Kevin O’Brien, “Germany’s Complicated Relationship with Google Street View,” New York Times , April 23, 2013.
• Cade Metz, “Artificial Intelligence is Setting Up the Internet for a Huge Clash with Europe,” Wired , July 11, 2016.
• Eric Siegel, “Predictive Analytics Interview Series: Andrew Burt,” Predictive Analytics Times , June 14, 2017.
• Oren Etzioni, “How to Regulate Artificial Intelligence,” New York Times , September 1, 2017.
• “Ethical Considerations in Artificial Intelligence and Autonomous Systems,” unpublished paper. IEEE Global Initiative, 2018.
• Ritesh Noothigattu, Snehalkumar Gaikwad, Edmond Awad, Sohan Dsouza, Iyad Rahwan, Pradeep Ravikumar, and Ariel Procaccia, “A Voting-Based System for Ethical Decision Making,” Computers and Society , September 20, 2017 (www.media.mit.edu/publications/a-voting-based-system-for-ethical-decision-making/).
• Miles Brundage, et al., “The Malicious Use of Artificial Intelligence,” University of Oxford unpublished paper, February 2018.
• John Markoff, “As Artificial Intelligence Evolves, So Does Its Criminal Potential,” New York Times, October 24, 2016, p. B3.
• Economist , “The Challenger: Technopolitics,” March 17, 2018.
• Douglas Maughan, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Levi Tillemann and Colin McCormick, “Roadmapping a U.S.-German Agenda for Artificial Intelligence Policy,” New American Foundation, March 2017.

Artificial Intelligence

Governance Studies

Center for Technology Innovation

Artificial Intelligence and Emerging Technology Initiative

Jacob Taylor

May 20, 2024

Mark Schoeman

May 16, 2024

Charles Asiegbu, Chinasa T. Okolo

208 Artificial Intelligence Essay Topics & Research Questions about AI

If you’re looking for interesting AI research questions or essay topics, you’ve come to the right place! In this list, we’ve compiled the latest trending essay topics on artificial intelligence, research questions, and project ideas. It doesn’t matter if you’re a high school student or a Ph.D. holder: here, you will find research questions about artificial intelligence for beginners as well as professionals.

🏆 Best Essay Topics on Artificial Intelligence

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• Artificial Intelligence Pros and Cons: Essay Sample
• Artificial Intelligence and Unemployment
• Ethics of Artificial Intelligence
• Artificial Intelligence and Its Impact on the Future
• Artificial Intelligence Versus Human Intelligence
• Artificial Intelligence in Healthcare
• Artificial Intelligence and Effects of Its Rise
• Artificial Intelligence in the Workplace The paper states that artificial intelligence has enabled many companies to achieve their dreams. It has also improved the human knowledge of AI.
• Artificial Intelligence: Effects on Business Artificial intelligence is a wide range of technological advancements that deal with current and future effects on the business sector to enhance profitability.
• Will Artificial Intelligence Replace Humans? The paper discusses whether artificial intelligence replaces humans. There is no single answer to the question because it affects several areas of human life.
• Artificial Intelligence as a Potential Threat to Humanity Artificial intelligence (AI) demonstrates immense potential in terms of improving society as long it is developed and implemented properly.
• Artificial Intelligence and Its Role in Business The paper looks into the peculiarities of replacing human work with AI to define its potential for development and issues associated with such implementation.
• Impact of Artificial Intelligence on the Education System The paper analyzes how the education system can maximize the advantages of Artificial Intelligence. It compares the traditional education system.
• Artificial Intelligence in the Labor Market The paper states that the continuous improvements in terms of developing artificial intelligence make render this technology close to reality.
• Artificial Intelligence and Music The paper discusses use of Artificial Intelligence is rapidly expanding, with several innovative companies adopting it to create music.
• Artificial Intelligence in Hospitality Industry The purpose of this paper is to explore the use application of AI in the hospitality industries. The paper focuses on the utilization of booking engines and hotel software systems.
• Artificial Intelligence as an Enhancer of Human Abilities The paper states that using Artificial Intelligence to enhance human capabilities is a trending factor that is growing and receiving attention.
• Artificial Intelligence Economy This annotated bibliography aims to discuss seven articles devoted to the topic of the artificial intelligence economy.
• AI In Accounting Essay Example Introducing artificial intelligence (AI) into accounting is viewed by many researchers as a promising practice, which has been the subject of numerous studies.
• Helpmewrite.AI Software’s Business Feasibility The report offers research on Helpmewrite.ai software, which is a product that helps writers, lawyers, and paralegals to compose distinct legal pamphlets promptly.
• The Dawn of Artificial Intelligence: Robots Robots were created by people to satisfy their large insatiable appetites. Such a sacrilegious act against the miracle of creation may cost a lot.
• Technologies & Artificial Intelligence Challenges For innovative organizations, new technologies introduce not only benefits but also new challenges as the use of artificial intelligence (AI) changes the way organizations work.
• Artificial Intelligence in the Hotel Industry The results of the analysis have shown that, overall, Artificial Intelligence proves to have a positive impact on the quality of hotel services and risk management.
• Artificial Intelligence: Use and Potential Risks Automation and intelligent algorithms can significantly benefit business owners by inducing substantial savings.
• Artificial Intelligence in Supply Chain Management This paper establishes the benefits, opportunities, and challenges of adopting machine learning technologies in logistics to help SMEs boost their performance.
• The Promises and Perils of Artificial Intelligence Artificial intelligence is a powerful technology that can generate economic gains; therefore, it is critical to explore its prehistory and practical and ethical concerns.
• Artificial Intelligence in Healthcare: Pros & Cons Rapidly advancing artificial intelligence technologies are gradually changing health care practices and bring a paradigm shift to the medical system.
• Artificial Intelligence: Ethical, Social, Legal Issues The field of artificial intelligence indeed brings numerous ethical, social, professional and legal issues; but are those so disturbing as some people claim?
• Game Playing in Artificial Intelligence The 9th of March, 2016, was a watershed moment in the development of artificial intelligence when the Go champion Lee Sedol was beaten by AlphaGo.
• Artificial Intelligence Threat for Employees The article “U.S. Lost Over 60 Million Jobs” published focuses on the ongoing unrest around the future of the job market and AI presence within.
• Artificial Intelligence in Economics Currently, the amount of data available to businesses continues to grow at an exceptional rate due to the developments in artificial intelligence and big data.
• Usage of AI and Robotics in Project Management Technological progress has allowed humanity to use the technologies they could not implement in the past centuries.
• The Fundamental Role of Artificial Intelligence in the IT Industry Artificial intelligence is aimed at machine learning and providing software to address the problems in a way similar to human intelligence.
• Artificial Intelligence in the Oil and Gas Industry Construction, mining, and oil and gas companies are the latecomers in this digitalization, increasingly depending on AI and machine learning (ML) based solutions frenzy.
• Artificial Intelligence in Accounting ​Artificial Intelligence is already replacing some accounting operations, and research indicates that automating these processes is a cost-effective option.
• E-Commerce: The Role of Artificial Intelligence Though the implementation of artificial intelligence within e-commerce continues to develop rapidly, there are several areas in which it affects the experiences of customers.
• Artificial Intelligence and the Future of Nursing The benefits of AI technologies include time and cost efficiency, as well as a high level of care consistency and comprehensiveness.
• Artificial Intelligence: Article Review Review of an article by Vinyals, Gaffney & Ewalds (2017) discussing the use of the StarCraft II video game as a platform for AI development and testing.
• Artificial Intelligence in Self-Driving Cars The paper states that artificial intelligence in self-driving vehicles cannot conclude several favorable outcomes – or, the “least bad” effects.
• Could Artificial Intelligence ‘End Mankind’ or Is It All Alarmist Nonsense? The idea of AI ending humankind and leading to a global catastrophe does not represent modern reality accurately.
• Artificial Intelligence in Business Management The use of artificial intelligence in business management is a sound practice due to many benefits that this technology offers and an opportunity to secure operational controls.
• How AI and Machine Learning Influence Marketing in the Fashion Industry The study aims to determine if the perception of AI in fashion is a novel concept and whether it holds enough appeal to impact the purchasing decisions of fashion consumers.
• Artificial Intelligence in Aviation and Human-Machine Interfaces The following study analyzes the research results to determine the impact of artificial intelligence (AI) on aviation.
• Business Model Canvas and Artificial Intelligence The nine blocks in the business model canvas, which include vital partners, cost structure, and others in relation to AI, can be summarized to explain their role in business.
• Algorithmic Bias of Artificial Intelligence Artificial intelligence is a rapidly developing technology which is already extensively utilized in different spheres, yet it has many considerable issues.
• Artificial Intelligence and Global Societal Issues Examination of the latest trends in the sphere of development of manufacturing processes indicates significant growth in the interest in artificial intelligence.
• Artificial Intelligence: Integrated in Healthcare This paper aims to talk about AI as an innovative idea that can be integrated into healthcare. It will detail the strategies used in executing AI.
• Artificial Intelligence as a Part of Imperialism: Challenges and Solutions Artificial intelligence is part of the process of imperialism, its offshoot, which is commonly called information imperialism.
• New Technology in the Air Cargo Industry: Artificial Intelligence The article “Transport logistic: Artificial Intelligence at Air cargo” discusses how artificial intelligence will revolutionize the air cargo industry.
• Artificial Intelligence and Big Data Impacts on Citizens The concept of artificial intelligence is complex and broad. However, researchers, theorists, and writers contribute to the creation of a clear and factual definition of this term in different ways.
• Artificial Intelligence and Human Intelligence Comparison AI performs many tasks that are impossible for humans to perform and can be equal to human tasks in interpreting CT scans, recognizing faces and voices, and playing games.
• Marketing Artificial Intelligence Problems The alignment problem when applying artificial intelligence in marketing occurs when managers ask a question that does not align with the set objectives.
• The Impact of Artificial Intelligence on the Future of Work Artificial intelligence is requested in the modern business world because it can lead to many positive outcomes when applied to employee monitoring.
• AI System in Smart Energy Consumption The primary aim of the paper is to expose the significant impacts of AI integration in intelligent energy consumption methods.
• Artificial Intelligence Implementation in Accounting Processes Artificial intelligence seems to be a prospective technology, and its implementation in accounting processes is inevitable.
• Using Information Technology and Artificial Intelligence in Critical Care Medicine Artificial Intelligence in critical care is helping to care for patients faster, supervise more patients, calculate the exact dosage for patients, and collect more detailed data.
• Artificial Intelligence and Its Usage in Modern Warfare and Healthcare This paper discusses the question of AI usage in modern warfare, and the usage of Artificial Intelligence used in healthcare in the current situation with the ongoing pandemic.
• Companies’ Reputation and Artificial Intelligence This paper discusses companies’ reputations and whether artificial intelligence (AI) has the capacity to predict customer and competitor behavior.
• Medical Innovations: 3D Bioprinting Artificial Intelligence This paper will discuss two medical technological innovations that are significant for the future of a medical organization and how different stakeholders could benefit from them.
• Artificial Intelligence: Pros and Cons Artificial intelligence is definitely a huge step in global technological progress, and like any other technology, it can be both a weapon and a lifesaver.
• The Portrayal of Artificial Intelligence Artificial intelligence seems to be Frankenstein’s monster of the new age. Different sources provide significant insight into the portrayal of AI as monstrosity.
• The Future of Artificial Intelligence in Fiction and Science Although there are numerous technological advancements, not many of them have caused such a tremendous controversy as artificial intelligence.
• The Limits of Global Inclusion in AI (Artificial Intelligence) Development This article is devoted to the theme of the development and implementation of elements of artificial intelligence (AI) in the context of various countries.
• AI Development, Unemployment, and Universal Basic Income The theme of AI-human relationships takes an important place in science fiction literature, movies, and video games, but it is not limited by them.
• AI in Customer Service: Argument Flaws Analyzing AI’s comprehensive functionality can provide sufficient arguments for a variety of options to implement to attract and retain customers.
• Artificial Intelligence Bias and Ethical Algorithms The paper argues in order to solve the problem of lack of diversity and assessing human needs correctly, there is a need to implement better guidelines for Artificial Intelligence.
• Fire Scene Investigation: Artificial Intelligence Each container should be labeled uniquely, including the investigator’s name, date and time, sample number, case number, and location of recovery.
• Artificial Intelligence and How It Affects Hospitality The main challenge in regards to Artificial Intelligence is its current state, which still requires extensive development in order for it to become practical and useful.
• Artificial Intelligence Projects Failed The research paper provides a detailed worldwide timeline of artificial intelligence projects that were attempted and failed and the threats they have caused.
• Artificial Intelligence in Medical Field The medical field constantly innovates and develops new technologies to improve patient care. Societies, in general, are significantly impacted by technological innovations.
• Artificial Intelligence: Emergence of Employment Issues Artificial intelligence has become particularly widespread in the modern world, but there are significant controversies about the benefits of this technology in people’s lives.
• Comparing Artificial Intelligence to Human Intelligence Intelligence is essential for humanity, as it can isolate important information from the environment and systematize it into knowledge used to solve specific problems.
• Customer’s Brand Engagement: The Use of Artificial Intelligence Marketers are currently using artificial intelligence in marketing to automate procedures and provide clients with a distinctive brand experience.
• Risks of Artificial Intelligence Data-Mining by Tech Corporations With the exponential advancement of Artificial Intelligence, the notion of data being valuable regarding marketability has permeated the cultural zeitgeist.
• Integrated Apple Home-Based Artificial Intelligence System Integrated Apple Home-based Artificial Intelligence system is an artificial intelligence system that has been tailored to meet the end-users’ home needs.
• The Turing Test and Development of Artificial Intelligence The Turing test is conducted with two people and a program, in which the program and one person communicate with a judge.
• Artificial Intelligence and the Future of Business AI’s modern field came into being in the 1950s; still, decades were spent on making serious progress in the development of an AI system and turning it from a dream into a reality.
• Artificial Intelligence, Insurtech, and Virtual Reality from a Market Perspective AI, Insurtech, and Virtual reality will be presented and discussed in relation to their impact on the market, as well as the disruptions and benefits they may cause.
• Artificial Intelligence: Impact on Labor Workforce The development of artificial intelligence often affects drivers and retail workers, healthcare workers, lawyers, accountants, and financial professionals.
• The Issue of Artificial Intelligence Integration in Private Health Sector It is possible to develop a particular insight into the perspectives of Artificial Intelligence integration in the private health sector.
• What Will Happen When AI Picks Up Social Biases About Gender? Social biases on gender will not have room when Artificial Intelligence takes over and the systems are put into everyday life.
• Enabling Successful AI Implementation in the Department of Defense This paper seeks to provide a summary and discuss three main points of the article “Enabling Successful AI Implementation in the Department of Defense.”
• Can the World Have a Fair Artificial Intelligence? It is important to consider issues to do with AI because the matter has adverse effects on the depreciation of human labor, information protection, and manipulation of people.
• AI-Improved Management Information System This paper evaluates a current management information system and directs on ways to improve it using artificial intelligence and machine learning.
• Artificial Intelligence and the Labor Market This essay will argue that although the use of AI is a controversial issue, AI could be implemented positively, allowing the effective cooperation of people and robots.
• Artificial Intelligence: Human Trust in Healthcare In the modern epoch of digitalization, artificial intelligence (AI) is widely utilized in education, transportation, media, banking, navigation, and healthcare.
• Artificial Intelligence: The Monstrous Entity The conversation around the artificial intelligence as a monstrous entity can provide new perspectives for all discourse communities revolving around this topic.
• Implementing Artificial Intelligence and Managing Change in Nursing This paper is going to talk about a planned change, namely the implementation of Artificial Intelligence (AI) in perception, thinking, planning, learning, etc.
• AI and Transitional Management The article presented the two sides of artificial intelligence from an objective perspective since the general implementation of AI is almost inevitable.
• Artificial Intelligence in Machinery This essay explores an operation case, discussing the tools in AI, particularly TensorFlow and Theano, and their implementation issues.
• Artificial Intelligence and Related Ethical Concerns Technological progress allows people to use AI capabilities increasingly, but this concept is also related to many ethical issues about human rights.
• Thinking Processes of Artificial Intelligence This essay will discuss the topic of artificial intelligence in whether artificial intelligence can be capable of thinking processes.
• The Finance Portfolio Management: Impact of Artificial Intelligence Despite the existing limitations, various artificial intelligence applications can make portfolio management much more accessible.
• AI, Human Control and Safety The given evaluative analysis will primarily focus on the topic of artificial intelligence, human control, and safety.
• Artificial Intelligence: The Articles Review This paper presents the annotated bibliography dedicated the artificial intelligence technologies, their safety or harm to society.
• Impact of Artificial Intelligence on the Labor Market The document presents annotated article in question considers the impact the spread of artificial intelligence technology may have on the labor market.
• How to Create a Fair Artificial Intelligence The current research aims to find possible ways to create a fair AI: exploring power concentration, mass manipulation, depreciation of human labor, and information protection.
• Artificial Intelligence in Scientific and Fiction Works I decided to research what possible benefits can come from cooperation between scientists and science fiction writers regarding the negative image of artificial intelligence.
• Artificial Intelligence: Advantages and Applications The advantages mentioned above introduce multiple opportunities for applying AI to acquire improved outcomes. Discussion of such applications.
• Artificial Intelligence (AI) and Universal Basic Income Articles included in the annotated bibliography describe problems of Automation and the spread of Artificial Intelligence (AI)-based technologies.
• Artificial Intelligence and Emerging Ethical Risks Technological progress went far beyond our imagination, and Artificial Intelligence became an indispensable companion in everyday life.
• AI and Hardware Integration in Business Work Processes AI-driven hardware within businesses has little competition as it is the leading tool for time-saving, cost-reduced, and efficient method processes.
• Artificial Intelligence and Singularity Technological development will inevitably shift humanity’s future in a highly radical way. It is especially true in the case of artificial intelligence (AI).
• Artificial Intelligence: Potential Problems and Threats Artificial intelligence can be used for unsuitable purposes, but this is not a scientific problem but rather a moral and ethical one.
• Implementation of AI in Law Practice There are many benefits of AI application to large firms that have a lot of unprocessed data or smaller firms that do not have the staff to cover all the tasks.
• AI: Agent Human Interactions In this case study a system that detects the status of the baby, that is, if the baby is awake, and it has an interface implemented with agent human interaction is considered.
• Artificial Intelligence in Business Administration Changes The current state of AI technology does not allow launching ambitious projects that will completely change the way businesses operate.
• Artificial Intelligence in the Working Process The purpose of this paper is to describe the impact of artificial intelligence (AI) on the job and its results. AI can do the job that was done by the employee for decades.
• Artificial Intelligence. Unmanned Mission Communications Communication networks are essential in facilitating the operations of autonomous systems as they are used in monitoring, collecting data, and exploring hard-to-reach areas.
• Artificial Intelligence: Its Potential and Use Artificial intelligence has been presented as a technology that will not replace human beings, but help them perform tasks better.
• Artificial Intelligence: Science Fiction Novels Many writers created stories and novels in the science fiction genre in an attempt to predict how the life where robots are not just machines but equal members of society would be.
• “Artificial Intelligence: A Competitive Advantage for the US Army” Review The document offers a substantial review of how the implementation of artificial intelligence (AI) may become a crucial competitive advantage for the US military.
• The Use of Starcraft II Video Games for AI Research The article is devoted to the rules for writing effective thesises, for each rule there are examples of good and bad writing.
• AI and Machine Self-Learning Machine self-learning has become a perfect solution for complex business problems that cannot be solved by software engineering or human judgment.
• Explainable Artificial Intelligence in Accounting The broad implementation of AI in such fields as accounting lays the ground for the drastic changes in management and methods that are utilized by specialists.
• Blockchain and Other Artificial Intelligence Systems The project describes the basic features of blockchain and AI technologies, along with the possibilities for their future use in different spheres of human activity.
• Artificial Intelligence (AI) in Health Care The use of AI has increased over the past decades, making it easier for researchers to investigate the most complicated issues.
• Artificial Intelligence in Enterprise Processes AI affects ERP systems even though AI-driven solutions are not implemented by the majority of businesses. AI is integrated into ERP systems to increase customer satisfaction
• Artificial Intelligence, Internet of Things, and the Impact on Facilities’ Environments The use of AI and IoT is unlikely to replace facilities’ teams because the decision-making process still requires human input.
• Artificial Intelligence and Ethical Implications If we create artificial intelligence based on human intelligence, some of the less needed qualities will be omitted during the process of abstraction.
• Artificial Intelligence Through Human Inquiry Much about the possible uses of A.I. and its potential capacities and abilities remains uncertain, which raises many questions as to what the future of A.I. will hold for humans.
• The Artificial Intelligence Machine AlphaGo Zero The selected technology is an artificial intelligence (AI) machine by the name of AlphaGo Zero. It is an evolution of previous well-known machines from the company Deep Mind.
• Artificial Intelligence in Strategic Business Management Artificial intelligence basically refers to the intelligence that is created in the software or machines by mankind.
• Regional Employment and Artificial Intelligence in Japan
• Artificial Intelligence and the Human Race
• Medicine and Artificial Intelligence
• Artificial Intelligence and Machine Learning Applied at the Point of Care
• Difference Between Artificial Intelligence and Human
• The Four Debatable Viewpoints One May Have About Artificial Intelligence
• Artificial Intelligence and Its Impact on Accounting
• Rational Choice and Artificial Intelligence
• The Ethics and Its Relation To Artificial Intelligence
• Artificial Intelligence and Medicine
• Privacy, Algorithms, and Artificial Intelligence
• Artificial Intelligence: Can Computers Think
• Cognitive Science and Its Link to Artificial Intelligence
• Artificial Intelligence Replacing the Art of Traditional Selling
• The Beauty and Danger of Artificial Intelligence
• Digital Devices for Artificial Intelligence Applications
• Artificial Intelligence and the Field of Robotics
• Could Artificial Intelligence Replace Teachers
• Artificial Intelligence and Neuromorphic Engineering
• Artificial Intelligence Based Improvised Explosive Devices
• Big Data Technologies and Artificial Intelligence
• Artificial Intelligence and Its Effects on Business
• Modern Technology and Artificial Intelligence
• Multilayered Perceptron and Artificial Intelligence
• Distributed, Decentralized, and Democratized Artificial Intelligence
• Artificial Intelligence and Video Games
• Some Considerations About Artificial Intelligence and Its Implications
• Comparing Human Intelligence With Artificial Intelligence
• Artificial Intelligence During the World Today
• Artificial Intelligence and the Future of Human Rights
• Economic Policy for Artificial Intelligence
• Artificial Intelligence for Human Intelligence and Industrial
• The Morality and Utility of Artificial Intelligence
• Artificial Intelligence and Behavioral Economics
• Blockchain and Artificial Intelligence Technologies
• The Effects Artificial Intelligence Has Had on Society and Business
• Marketing and Artificial Intelligence
• Artificial Intelligence and Machines Automation
• People Copy the Actions of Artificial Intelligence
• Artificial Intelligence for Healthcare in Africa
• Healthcare System Using Artificial Intelligence
• Artificial Intelligence for the Future Radiology Diagnostic Service
• Artificial Intelligence and Marketing
• Copyright Protection for Artificial Intelligence
• The Potential and Future of Artificial Intelligence
• Artificial Intelligence and the Human Mind
• Expert Systems and Its Relationship With Artificial Intelligence
• Artificial Intelligence and Its Effect on Mankind
• The Nexus Between Artificial Intelligence and Economics
• Artificial Intelligence, Based Training and Placement Management
• Artificial Intelligence and Its Implications for Income Distribution and Unemployment
• Machine Learning and Artificial Intelligence in Finance
• The Pros and Cons of Artificial Intelligence
• Artificial Intelligence and the Legal Profession
• Continual Learning: The Next Generation of Artificial Intelligence
• Artificial Intelligence and Its Uses
• Regulation Within the Development of Artificial Intelligence
• Artificial Intelligence and Computer Science
• Mysteries, Epistemological Modesty, and Artificial Intelligence in Surgery
• Artificial Intelligence and Cognitive Reasoning
• Can Artificial Intelligence Become Smarter Than Humans?
• Should Humanity Fear Advances in Artificial Intelligence?
• How Does Artificial Intelligence Affect the Retail Industry?
• What Are Some of the Ethical Challenges Posed by the Use of Artificial Intelligence for Hiring?
• Does Artificial Intelligence Impact the Creative Industries?
• Can Artificial Intelligence Change the Way in Which Companies Recruit, Train, Develop, and Manage Human Resources in Workplace?
• Will Artificial Intelligence Defeat Human Intelligence?
• How Can Artificial Intelligence Help Modern Society?
• Can Artificial Intelligence Lead to a More Sustainable Society?
• What Role Will Artificial Intelligence Play in Human Affairs in the Next Few Decades?
• How Can Artificial Intelligence Help Us Understand Human Creativity?
• Will Artificial Intelligence Devices Become Human Best Friend?
• Why Must Artificial Intelligence Be Regulated?
• Should Artificial Intelligence Have Human Rights?
• Why Artificial Intelligence Won’t Dominate the Future?
• How Does Artificial Intelligence Impact Today’s Society?
• Will Artificial Intelligence Overpower Human Beings?
• Should Artificial Intelligence Take Over the Jobs of the Tertiary Sector?
• How Will Artificial Intelligence Impact the World?
• Should People Develop Artificial Intelligence?
• How Does Mary Shelley’s Depiction Show the Threats of Artificial Intelligence?
• What Can Artificial Intelligence Offer Coral Reef Managers?
• How Will Artificial Intelligence Affect the Job Industry in the Future?
• Should the Innovative Evolution of Artificial Intelligence be Regulated?
• Will Artificial Intelligence Have a Progressive or Retrogressive Impact on Our Society?

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StudyCorgi. (2022, March 1). 208 Artificial Intelligence Essay Topics & Research Questions about AI. https://studycorgi.com/ideas/artificial-intelligence-essay-topics/

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StudyCorgi . 2022. "208 Artificial Intelligence Essay Topics & Research Questions about AI." March 1, 2022. https://studycorgi.com/ideas/artificial-intelligence-essay-topics/.

These essay examples and topics on Artificial Intelligence were carefully selected by the StudyCorgi editorial team. They meet our highest standards in terms of grammar, punctuation, style, and fact accuracy. Please ensure you properly reference the materials if you’re using them to write your assignment.

This essay topic collection was updated on March 8, 2024 .

The College Essay Is Dead

Nobody is prepared for how AI will transform academia.

Suppose you are a professor of pedagogy, and you assign an essay on learning styles. A student hands in an essay with the following opening paragraph:

The construct of “learning styles” is problematic because it fails to account for the processes through which learning styles are shaped. Some students might develop a particular learning style because they have had particular experiences. Others might develop a particular learning style by trying to accommodate to a learning environment that was not well suited to their learning needs. Ultimately, we need to understand the interactions among learning styles and environmental and personal factors, and how these shape how we learn and the kinds of learning we experience.

Pass or fail? A- or B+? And how would your grade change if you knew a human student hadn’t written it at all? Because Mike Sharples, a professor in the U.K., used GPT-3, a large language model from OpenAI that automatically generates text from a prompt, to write it. (The whole essay, which Sharples considered graduate-level, is available, complete with references, here .) Personally, I lean toward a B+. The passage reads like filler, but so do most student essays.

Sharples’s intent was to urge educators to “rethink teaching and assessment” in light of the technology, which he said “could become a gift for student cheats, or a powerful teaching assistant, or a tool for creativity.” Essay generation is neither theoretical nor futuristic at this point. In May, a student in New Zealand confessed to using AI to write their papers, justifying it as a tool like Grammarly or spell-check: ​​“I have the knowledge, I have the lived experience, I’m a good student, I go to all the tutorials and I go to all the lectures and I read everything we have to read but I kind of felt I was being penalised because I don’t write eloquently and I didn’t feel that was right,” they told a student paper in Christchurch. They don’t feel like they’re cheating, because the student guidelines at their university state only that you’re not allowed to get somebody else to do your work for you. GPT-3 isn’t “somebody else”—it’s a program.

The world of generative AI is progressing furiously. Last week, OpenAI released an advanced chatbot named ChatGPT that has spawned a new wave of marveling and hand-wringing , plus an upgrade to GPT-3 that allows for complex rhyming poetry; Google previewed new applications last month that will allow people to describe concepts in text and see them rendered as images; and the creative-AI firm Jasper received a $1.5 billion valuation in October. It still takes a little initiative for a kid to find a text generator, but not for long.

The essay, in particular the undergraduate essay, has been the center of humanistic pedagogy for generations. It is the way we teach children how to research, think, and write. That entire tradition is about to be disrupted from the ground up. Kevin Bryan, an associate professor at the University of Toronto, tweeted in astonishment about OpenAI’s new chatbot last week: “You can no longer give take-home exams/homework … Even on specific questions that involve combining knowledge across domains, the OpenAI chat is frankly better than the average MBA at this point. It is frankly amazing.” Neither the engineers building the linguistic tech nor the educators who will encounter the resulting language are prepared for the fallout.

A chasm has existed between humanists and technologists for a long time. In the 1950s, C. P. Snow gave his famous lecture, later the essay “The Two Cultures,” describing the humanistic and scientific communities as tribes losing contact with each other. “Literary intellectuals at one pole—at the other scientists,” Snow wrote. “Between the two a gulf of mutual incomprehension—sometimes (particularly among the young) hostility and dislike, but most of all lack of understanding. They have a curious distorted image of each other.” Snow’s argument was a plea for a kind of intellectual cosmopolitanism: Literary people were missing the essential insights of the laws of thermodynamics, and scientific people were ignoring the glories of Shakespeare and Dickens.

The rupture that Snow identified has only deepened. In the modern tech world, the value of a humanistic education shows up in evidence of its absence. Sam Bankman-Fried, the disgraced founder of the crypto exchange FTX who recently lost his $16 billion fortune in a few days , is a famously proud illiterate. “I would never read a book,” he once told an interviewer . “I don’t want to say no book is ever worth reading, but I actually do believe something pretty close to that.” Elon Musk and Twitter are another excellent case in point. It’s painful and extraordinary to watch the ham-fisted way a brilliant engineering mind like Musk deals with even relatively simple literary concepts such as parody and satire. He obviously has never thought about them before. He probably didn’t imagine there was much to think about.

The extraordinary ignorance on questions of society and history displayed by the men and women reshaping society and history has been the defining feature of the social-media era. Apparently, Mark Zuckerberg has read a great deal about Caesar Augustus , but I wish he’d read about the regulation of the pamphlet press in 17th-century Europe. It might have spared America the annihilation of social trust .

These failures don’t derive from mean-spiritedness or even greed, but from a willful obliviousness. The engineers do not recognize that humanistic questions—like, say, hermeneutics or the historical contingency of freedom of speech or the genealogy of morality—are real questions with real consequences. Everybody is entitled to their opinion about politics and culture, it’s true, but an opinion is different from a grounded understanding. The most direct path to catastrophe is to treat complex problems as if they’re obvious to everyone. You can lose billions of dollars pretty quickly that way.

As the technologists have ignored humanistic questions to their peril, the humanists have greeted the technological revolutions of the past 50 years by committing soft suicide. As of 2017, the number of English majors had nearly halved since the 1990s. History enrollments have declined by 45 percent since 2007 alone. Needless to say, humanists’ understanding of technology is partial at best. The state of digital humanities is always several categories of obsolescence behind, which is inevitable. (Nobody expects them to teach via Instagram Stories.) But more crucially, the humanities have not fundamentally changed their approach in decades, despite technology altering the entire world around them. They are still exploding meta-narratives like it’s 1979, an exercise in self-defeat.

Read: The humanities are in crisis

Contemporary academia engages, more or less permanently, in self-critique on any and every front it can imagine. In a tech-centered world, language matters, voice and style matter, the study of eloquence matters, history matters, ethical systems matter. But the situation requires humanists to explain why they matter, not constantly undermine their own intellectual foundations. The humanities promise students a journey to an irrelevant, self-consuming future; then they wonder why their enrollments are collapsing. Is it any surprise that nearly half of humanities graduates regret their choice of major ?

The case for the value of humanities in a technologically determined world has been made before. Steve Jobs always credited a significant part of Apple’s success to his time as a dropout hanger-on at Reed College, where he fooled around with Shakespeare and modern dance, along with the famous calligraphy class that provided the aesthetic basis for the Mac’s design. “A lot of people in our industry haven’t had very diverse experiences. So they don’t have enough dots to connect, and they end up with very linear solutions without a broad perspective on the problem,” Jobs said . “The broader one’s understanding of the human experience, the better design we will have.” Apple is a humanistic tech company. It’s also the largest company in the world.

Despite the clear value of a humanistic education, its decline continues. Over the past 10 years, STEM has triumphed, and the humanities have collapsed . The number of students enrolled in computer science is now nearly the same as the number of students enrolled in all of the humanities combined.

And now there’s GPT-3. Natural-language processing presents the academic humanities with a whole series of unprecedented problems. Practical matters are at stake: Humanities departments judge their undergraduate students on the basis of their essays. They give Ph.D.s on the basis of a dissertation’s composition. What happens when both processes can be significantly automated? Going by my experience as a former Shakespeare professor, I figure it will take 10 years for academia to face this new reality: two years for the students to figure out the tech, three more years for the professors to recognize that students are using the tech, and then five years for university administrators to decide what, if anything, to do about it. Teachers are already some of the most overworked, underpaid people in the world. They are already dealing with a humanities in crisis. And now this. I feel for them.

And yet, despite the drastic divide of the moment, natural-language processing is going to force engineers and humanists together. They are going to need each other despite everything. Computer scientists will require basic, systematic education in general humanism: The philosophy of language, sociology, history, and ethics are not amusing questions of theoretical speculation anymore. They will be essential in determining the ethical and creative use of chatbots, to take only an obvious example.

The humanists will need to understand natural-language processing because it’s the future of language, but also because there is more than just the possibility of disruption here. Natural-language processing can throw light on a huge number of scholarly problems. It is going to clarify matters of attribution and literary dating that no system ever devised will approach; the parameters in large language models are much more sophisticated than the current systems used to determine which plays Shakespeare wrote, for example . It may even allow for certain types of restorations, filling the gaps in damaged texts by means of text-prediction models. It will reformulate questions of literary style and philology; if you can teach a machine to write like Samuel Taylor Coleridge, that machine must be able to inform you, in some way, about how Samuel Taylor Coleridge wrote.

The connection between humanism and technology will require people and institutions with a breadth of vision and a commitment to interests that transcend their field. Before that space for collaboration can exist, both sides will have to take the most difficult leaps for highly educated people: Understand that they need the other side, and admit their basic ignorance. But that’s always been the beginning of wisdom, no matter what technological era we happen to inhabit.

IB CompSci Hub

Extended Essay

Extended Essays in Computer Science are not easy to do. Computer Science is counted as an experimental science by the IB and thus requires you to do some kind of experiment in the realm of computer science and then report your findings.

As so few students attempt a CS EE every year, coming up with a ‘good’ CS EE topic will be half your struggle.

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General IB Extended Essay

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Examples of Topics 

Below are some examples of what topics our students have been doing recently (including the grade they received from the IB). Obviously, you cannot take any of these topics as it would flag as cheating; they are posted to give you an idea of the TYPE of topic that gets a good grade.

Past essays  

Because of plagiarism concerns, we cannot share any essays from past students on this site, but you are welcome to visit LD Anderson’s CS EE world site:  CS EE World

How to Write an Essay using Artificial Intelligence?

Mar 14 2024

Artificial intelligence has made remarkable strides in recent years, and its applications have extended to the realm of essay writing. AI-powered tools and techniques have the potential to revolutionize the way we approach the writing process. This essay will explore the concept of AI-assisted essay writing, its benefits, and the strategies for effectively leveraging AI to enhance the quality and efficiency of your writing.

Artificial Intelligence Essay

500+ words essay on artificial intelligence.

Artificial intelligence (AI) has come into our daily lives through mobile devices and the Internet. Governments and businesses are increasingly making use of AI tools and techniques to solve business problems and improve many business processes, especially online ones. Such developments bring about new realities to social life that may not have been experienced before. This essay on Artificial Intelligence will help students to know the various advantages of using AI and how it has made our lives easier and simpler. Also, in the end, we have described the future scope of AI and the harmful effects of using it. To get a good command of essay writing, students must practise CBSE Essays on different topics.

Artificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. It is concerned with getting computers to do tasks that would normally require human intelligence. AI systems are basically software systems (or controllers for robots) that use techniques such as machine learning and deep learning to solve problems in particular domains without hard coding all possibilities (i.e. algorithmic steps) in software. Due to this, AI started showing promising solutions for industry and businesses as well as our daily lives.

Importance and Advantages of Artificial Intelligence

Advances in computing and digital technologies have a direct influence on our lives, businesses and social life. This has influenced our daily routines, such as using mobile devices and active involvement on social media. AI systems are the most influential digital technologies. With AI systems, businesses are able to handle large data sets and provide speedy essential input to operations. Moreover, businesses are able to adapt to constant changes and are becoming more flexible.

By introducing Artificial Intelligence systems into devices, new business processes are opting for the automated process. A new paradigm emerges as a result of such intelligent automation, which now dictates not only how businesses operate but also who does the job. Many manufacturing sites can now operate fully automated with robots and without any human workers. Artificial Intelligence now brings unheard and unexpected innovations to the business world that many organizations will need to integrate to remain competitive and move further to lead the competitors.

Artificial Intelligence shapes our lives and social interactions through technological advancement. There are many AI applications which are specifically developed for providing better services to individuals, such as mobile phones, electronic gadgets, social media platforms etc. We are delegating our activities through intelligent applications, such as personal assistants, intelligent wearable devices and other applications. AI systems that operate household apparatus help us at home with cooking or cleaning.

Future Scope of Artificial Intelligence

In the future, intelligent machines will replace or enhance human capabilities in many areas. Artificial intelligence is becoming a popular field in computer science as it has enhanced humans. Application areas of artificial intelligence are having a huge impact on various fields of life to solve complex problems in various areas such as education, engineering, business, medicine, weather forecasting etc. Many labourers’ work can be done by a single machine. But Artificial Intelligence has another aspect: it can be dangerous for us. If we become completely dependent on machines, then it can ruin our life. We will not be able to do any work by ourselves and get lazy. Another disadvantage is that it cannot give a human-like feeling. So machines should be used only where they are actually required.

Students must have found this essay on “Artificial Intelligence” useful for improving their essay writing skills. They can get the study material and the latest updates on CBSE/ICSE/State Board/Competitive Exams, at BYJU’S.

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