This unit examines legal, ethical, and organizational practices for building and sustaining trustworthy AI, focusing on accountability, corporate responsibility, and practical steps to cultivate trust. Students will synthesize laws and leading practices to design governance, measurement, and implementation plans that balance innovation and responsible use.
Learning Objectives
- Analyze relevant laws, liability risks, and regulatory considerations affecting AI deployment and recommend compliance and risk-mitigation strategies for organizational contexts
- Apply leading practices and governance frameworks to design a documented accountable AI program that integrates people, processes, and technologies
- Demonstrate creation of a stakeholder-focused trust plan by identifying relevant dimensions of trust, selecting measurable metrics and controls, and mapping actions across good/better/best phases
- Evaluate corporate responsibility and change-management strategies to motivate responsible AI use and propose prioritized next steps and guidelines for organizational adoption
Curriculum
- 1 Section
- 17 Lessons
- 30 hours
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- Unit 4 — Accountability and Trust in AI17
- 1.1Balancing Innovation and Accountability20 mins
- 1.2Laws, Lawsuits, and Liability20 mins
- 1.3Leading Practices in Accountable AI20 mins
- 1.4Accounting for Trust in AI20 mins
- 1.5Notes20 mins
- 1.6Corporate Responsibility in the AI Era20 mins
- 1.7Motivating Responsible AI Use20 mins
- 1.8Balancing Good, Better, and Best20 mins
- 1.9Leading Practices in the Responsible Use of AI20 mins
- 1.10Trust Emerging from Responsibility20 mins
- 1.11Notes20 mins
- 1.12Step 1 – Identify the Relevant Dimensions of Trust20 mins
- 1.13Step 2 – Cultivating Trust Through People, Processes, and Technologies20 mins
- 1.14Guidelines for Action on Trustworthy AI20 mins
- 1.15Taking the Next Steps20 mins
- 1.16Note20 mins
- 1.17Note20 mins
Instructor
Free
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