Skip to main content

Who’s in Control? Human Agency & AI

As AI agents become more capable and independent, maintaining meaningful human oversight is critical. This video explores the role human agency plays in ethical AI decision-making.

Discussion Questions

[Note: these questions were written in the summer of 2026. It seems that every aspect of AI’s development, usage, and impact is evolving at a rapid pace. Take that into account and use relevant, recent information in formulating your answers and arguments.]

 

  1. One of the speakers points out that humans often (and sensibly) delegate their decision making regarding their cars to mechanics and regarding their health to doctors. He suggests that delegating decisions to AI is “a step further.” Do you agree? Is it a step further or is it pretty much the same thing if the AI has expertise in that arena? Explain.
  2. People often seek second opinions after being diagnosed by a physician. Is keeping a human in the loop with AI the same thing as keeping a second human in the loop when a doctor was the initial decision maker in a matter of great import? Why or why not?
  3. Is it sensible to try to keep a human “in the loop” when the AI’s advantage over humans is not that it is more accurate than the human brain, but that it is 1,000 times faster? Explain.
  4. There is much evidence today that even the engineers designing current AI models do not fully understand how they work, how they “think” (if indeed they do). One of the speakers warns us against delegating too much agency to machines we do not fully understand. Is this sound advice? What would worry you the most about delegating an important decision to AI?
  5. As one speaker points out, there is a well-established phenomenon called “automation bias,” whereby people tend to trust information produced by a machine over contradictory information provided by other humans or even by their own senses. Given this bias, will people truly manage to “keep a human in the loop” whenever they make important decisions via AI? Do you think it’s possible to compensate for automation bias? If so, how?
  6. A civil engineer has stated that he can’t imagine civil engineers leaving full supervision and control to AI. But haven’t you read about lawyers and judges getting into trouble by leaving it to AI to write their legal briefs and judicial opinions only to have the AI model hallucinate–making up and citing cases that do not exist? If lawyers delegate so fully in that way to AI, might doctors, architects, civil engineers and others do the same? How big a worry should this be for us? What are the risks, in your opinion, of delegating control to AI?
  7. One speaker says that the value humans bring to “the loop” is their empathy, their emotional understanding, and their understanding of the “big picture.” She further suggests that humans’ real value is the ability to go beyond the logic of step-by-step thinking. How can humans know when jettisoning logic will lead to better, not worse, decisions?
  8. Is it realistic to think that humans can improve on AI decision making when they do not truly understand how the AI models “think”? Without a detailed and thorough understanding of how AI “thinks,” how can a human diagnose and remedy an AI’s errors? Can having a human “in the loop” then truly improve AI decision making? If not, are we not relying totally on the AI? Is that a scary proposition? If so, why? Support with evidence.
  9. Several speakers suggest that it is human ethics that “humans in the loop” can bring that will truly improve an AI’s decision making. Do you agree? If so, what gives you confidence in that claim?
  10. One of the speakers argues that “it’s the big picture of what we want our lives to look like, what we want society to look like, how we want people to be treated. We can’t stop making those decisions.” Do you agree or disagree with this statement? Can having a human “in the loop” practically produce this result? Why or why not?
  11. When designing AI systems, we often speak of the “alignment problem.” How do we “align” an AI tool’s goals with human goals? How can we ensure that the AI tool will make decisions consistent with human morals and values? Are we more likely to obtain the best decisions by solving the alignment problem, by keeping a human “in the loop,” or by doing our best to achieve both? Explain.
Running with Scissors: AI and the Race for the Future

Running with Scissors: AI and the Race for the Future

The race to develop and deploy AI has led innovation to outpace ethical inquiry. As part of our AI Ethics Docuseries, this documentary explores the risks of prioritizing speed over responsibility and the ethical safeguards that can ensure a better future for humanity.

View

Human Mind Traps: Behavioral Ethics & AI

Human Mind Traps: Behavioral Ethics & AI

Human decision-making is influenced by mental biases and shortcuts, social pressures, and situational factors. This video explains some of the tricks our minds play on us that can cause us to act unethically and the impact these tricks may have on our interactions with AI.

View

Outsourcing Thought: Overreliance & AI

Outsourcing Thought: Overreliance & AI

AI can improve efficiency and decision-making, but excessive reliance on these systems can diminish critical thinking and independent judgment. This video examines the ethical risks of overreliance on AI.

View

Fact vs. Fiction: Information Integrity & AI

Fact vs. Fiction: Information Integrity & AI

Artificial intelligence is changing how information is created, shared, and consumed. This video explores the importance of information integrity in an era of increasingly realistic AI-generated media.

View

Is That Fair? Bias & AI

Is That Fair? Bias & AI

AI can reflect and amplify biases found in society, in the humans who create AI, in the data used to train AI systems. This video examines AI fairness and what AI bias means for our world.

View

Meet Your New Coworker: Employment & AI

Meet Your New Coworker: Employment & AI

Artificial intelligence is transforming the workplace by automating tasks, replacing humans, and changing job roles. This video explores the ethical implications of AI’s impact on the workforce and employment.

View

Racing to… Where? Regulation & AI

Racing to… Where? Regulation & AI

AI is evolving faster than many existing laws and policies. This video examines the role of regulation, the need for effective guardrails, and the challenges of governing a rapidly changing technology.

View

The Black Box: Transparency, Trust & AI

The Black Box: Transparency, Trust & AI

Understanding how AI systems make decisions is essential for building trust in their use. This video examines why transparency matters in the ethical development and deployment of artificial intelligence.

View

The Blueprint for AI? Social Media & AI

The Blueprint for AI? Social Media & AI

The rapid rise of social media offers valuable lessons for the development of artificial intelligence. This video examines how past experiences with emerging technologies can inform the future of AI design and governance.

View

The Hidden Cost of AI: Energy & the Environment

The Hidden Cost of AI: Energy & the Environment

Training and operating AI systems requires significant computing power. This video explores the energy consumption and environmental impacts of AI and the importance of considering sustainability in its development.

View

Wait, I Made That! Creativity, Copyright & AI

Wait, I Made That! Creativity, Copyright & AI

AI-generated content is challenging traditional ideas of creativity, authorship, and ownership. This video examines the ethical and legal questions surrounding creativity and copyright in the age of AI.

View

AI Ethics

AI Ethics

AI ethics focuses on ensuring that AI is developed and deployed responsibly, promoting fairness, transparency, accountability, and societal well-being while minimizing harm.

View

Algorithmic Bias

Algorithmic Bias

Algorithmic bias occurs when AI algorithms reflect human prejudices due to biased data or design, leading to unfair or discriminatory outcomes.

View

Artificial Intelligence

Artificial Intelligence

Artificial intelligence (AI) describes machines that can think and learn like human beings. AI is continually evolving, and includes subfields such as machine learning and generative AI.

View

Technological Somnambulism

Technological Somnambulism

Technological somnambulism refers to the unreflective, blind creation and adoption of new technologies without consideration for their long-term societal and ethical impacts.

View

Moral Agent

Moral Agent

A Moral Agent is a person who can be held accountable for his or her actions because he or she has the ability to tell right from wrong.

View

AI Ethics: The Case for ‘AI for Good’

AI Ethics: The Case for ‘AI for Good’

Ethical decision making must always be based upon a strong and accurate factual foundation. Good people wanting to act ethically in the face of the rapid developments in the realm of artificial intelligence must therefore keep pace with those developments. Should they adopt AI tools or not? Should they lobby for or against government regulation […]

View

AI Ethics: The Atomic Human

AI Ethics: The Atomic Human

Sound moral judgments must be based on facts. People court disaster when they make morally-tinged decisions based on nothing more than speculation. We believe that at this particular point in time, artificial intelligence (AI) presents the world with several of its most critical moral issues.  We have addressed AI ethics in several recent blog posts […]

View

AI Ethics: As If Human

AI Ethics: As If Human

Oxford University computer scientist Nigel Shadbolt and co-author Roger Hampson (S&H), like so many others these days, believe that we must think carefully about the ethical issues surrounding the development of artificial intelligence (AI), so they’ve written As If Human: Ethics and Artificial Intelligence (2025). S&H are AI Doubters. S&H point out a litany of […]

View

Companion e-book

link to open book

AI Ethics Companion Handbook

This e-book compiles all the resources on AI ethics available on the Ethics Unwrapped website. It will continue to be updated as new materials are published.

Additional Resources

A recent resource from Ethics Unwrapped is a book, Behavioral Ethics in Practice: Why We Sometimes Make the Wrong Decisions, written by Cara Biasucci and Robert Prentice. This accessible book is amply footnoted with behavioral ethics studies and associated research. It also includes suggestions at the end of each chapter for related Ethics Unwrapped videos and case studies. Some instructors use this resource to educate themselves, while others use it in lieu of (or in addition to) a textbook.

The most recent article written by Cara Biasucci and Robert Prentice describes the basics of behavioral ethics and introduces Ethics Unwrapped videos and supporting materials along with teaching examples. It also includes data on the efficacy of Ethics Unwrapped for improving ethics pedagogy across disciplines. Published in Journal of Business Law and Ethics Pedagogy (Vol. 1, August 2018), it can be downloaded here: “Teaching Behavioral Ethics (Using “Ethics Unwrapped” Videos and Educational Materials).”

Cara Biasucci also wrote a chapter on integrating Ethics Unwrapped in higher education, which can be found in the latest edition of Teaching Ethics: Instructional Models, Methods and Modalities for University Studies. The chapter includes examples of how Ethics Unwrapped is used at various universities.

An article written by Ethics Unwrapped authors Minette Drumwright, Robert Prentice, and Cara Biasucci introduce key concepts in behavioral ethics and approaches to effective ethics instruction—including sample classroom assignments. Published in the Decision Sciences Journal of Innovative Education, it can be downloaded here: “Behavioral Ethics and Teaching Ethical Decision Making.”

A detailed article written by Robert Prentice, with extensive resources for teaching behavioral ethics, was published in Journal of Legal Studies Education and can be downloaded here: “Teaching Behavioral Ethics.”

Another article by Robert Prentice, discussing how behavioral ethics can improve the ethicality of human decision-making, was published in the Notre Dame Journal of Law, Ethics & Public Policy. It can be downloaded here: “Behavioral Ethics: Can It Help Lawyers (And Others) Be their Best Selves?

A dated (but still serviceable) introductory article about teaching behavioral ethics can be accessed through Google Scholar by searching: Prentice, Robert A. 2004. “Teaching Ethics, Heuristics, and Biases.” Journal of Business Ethics Education 1 (1): 57-74.

Shares