AI Accountability: Build Responsible and Transparent Systems
2h 57mBeginner2025-08-20
Authors

Barton Poulson
Professor, Designer, Data Analytics Expert
Course details
AI offers businesses the potential for a dramatic increase in functionality and profitability, but it can also spark an array of complex ethical, legal, and social challenges. In this nontechnical, conceptually oriented course, Barton Poulson digs into the hazards of generative AI, offering potential solutions to some of its key concerns. Barton explores the ethical issues posed by AI, including competing concepts of fairness and moral reasoning. He also goes over social concerns and safety challenges for AI, such as potential life-and-death scenarios drawn from medicine and military warfare. Barton concludes with recommendations tailored to developers, executives, PR professionals, regulators, and consumers to help them reap the potential benefits of generative AI in a way that's trustworthy and profitable for everyone involved.
This course includes AI-powered Role Play. Role Play allows you to practice what you’ve learned in interactive simulations of real-world conversations.
Learning objectives
Review the challenges of AI.
Apply narrow AI to a decision.
Define two major approaches used when dealing with AI.
Examine supervised and unsupervised learning.
Explain harassment by AI.
Identify three concepts that distributive justice is based on.
This course includes AI-powered Role Play. Role Play allows you to practice what you’ve learned in interactive simulations of real-world conversations.
Learning objectives
Review the challenges of AI.
Apply narrow AI to a decision.
Define two major approaches used when dealing with AI.
Examine supervised and unsupervised learning.
Explain harassment by AI.
Identify three concepts that distributive justice is based on.
Skills covered
Responsible AIArtificial Intelligence (AI)One-Off
Concepts
0. Introduction
- 01 - Welcome
1. The Context for AI
- 02 - The promise of AI
- 03 - Generative and analytical AI
- 04 - General and narrow AI
- 05 - Artificial general intelligence (AGI)
2. Technical Challenges of AI
- 06 - Technical challenges for generative AI
- 07 - The challenge of classification errors
- 08 - The causes of classification errors
- 09 - Bias in AI
- 10 - Genres of learning
- 11 - Biased training data
- 12 - Construct validity
- 13 - The absence of meaning
- 14 - Vulnerability to attacks
- 15 - Attacking AI
3. Social Challenges of AI
- 16 - Dimensions of justice
- 17 - Moral reasoning
- 18 - Issues of authenticity
4. Legal Challenges of AI
- 19 - GenAI laws
- 20 - Privacy laws
- 21 - Spurious discrimination
- 22 - The right to explanation
- 23 - Discrimination in data
- 24 - Discrimination in implementation
- 25 - Discrimination and misinformation in generative AI
5. Safety Challenges of AI
- 26 - AI in life and death situations
- 27 - AI in the military
- 28 - The challenges of military AI
- 29 - Physical safety and generative AI
6. Confronting the Challenges of AI
- 30 - Strategies for developers
- 31 - Strategies for executives
- 32 - Strategies for public relations
- 33 - Strategies for regulators
- 34 - Strategies for consumers
Conclusion
- 35 - Next steps