AI Accountability: Build Responsible and Transparent Systems (2022)
2h 17mIntermediate2022-11-30
Authors
Barton Poulson
Professor, Designer, Data Analytics Expert
Course details
Artificial intelligence (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 AI, offering potential solutions to 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 in autonomous driving. Barton concludes with recommendations tailored to developers, executives, PR professionals, regulators, and consumers to help them reap the potential of AI in a manner that's worthy of trust and profitable to all.
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.
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
Ethics and LawResponsible AIArtificial Intelligence FoundationsEssential TrainingArtificial Intelligence (AI)Business Analysis and Strategy
Concepts
0. Introduction
- 01 - What is AI accountability
1. The Context for AI
- 02 - The promise of AI
- 03 - General and narrow AI
2. Technical Challenges of AI
- 04 - The challenge of classification errors
- 05 - The causes of classification errors
- 06 - Bias in AI
- 07 - Supervised and unsupervised learning
- 08 - Biased labeling of data
- 09 - Construct validity
- 10 - The absence of meaning
- 11 - Vulnerability to attacks
3. Social Challenges of AI
- 12 - Dimensions of justice
- 13 - Moral and relational reasoning
- 14 - Issues of authenticity
4. Legal Challenges of AI
- 15 - Privacy laws
- 16 - Spurious discrimination
- 17 - The right to explanation
- 18 - Discrimination in data
- 19 - Discrimination in implementation
5. Safety Challenges of AI
- 20 - AI in life and death situations
- 21 - AI in the military
- 22 - The challenges of military AI
6. Confronting the Challenges of AI
- 23 - Strategies for developers
- 24 - Strategies for executives
- 25 - Strategies for public relations
- 26 - Strategies for regulators
- 27 - Strategies for consumers
Conclusion
- 28 - Next steps