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AI Risk Mitigation and Legal Strategies

via Coursera

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 1 hour a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

English

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Overview

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Welcome to AI Risk Mitigation and Legal Strategies . This course covers 4 modules: Introduction to AI Risk and AI Washing: Definitions, SEC and FTC Enforcement; IP Infringement in AI: Getty, New York Times, and Music Publishers Cases; IP Hypothetical Cases and Strategic Actions: Open-Source Licenses and Audit Questions; and Data Privacy in AI: BIPA Lawsuits, Privacy Risk Assessment, and Vendor Management. Each module includes video lessons, key-takeaway readings, a practice quiz, and a hands-on activity. By the end, you'll be able to define AI washing as a deceptive marketing practice misrepresenting AI capabilities, and apply Section 5 of the FTC Act and SEC enforcement standards (Gensler 2023; Delphia and Global Predictions $400K fines) to evaluate when AI claims cross into actionable misrepresentation. You'll also distinguish IBM's four types of AI (reactive, limited-memory, theory-of-mind, self-aware) and use the distinction to test whether a company's AI claims qualify as 'genuine...

Syllabus

Introduction to AI Risk and AI Washing: Definitions, SEC and FTC Enforcement
- This module of AI Risk Mitigation and Legal Strategies — Introduction to AI Risk and AI Washing: Definitions, SEC and FTC Enforcement — covers 1 lesson: Introduction to AI Risk and AI Washing: Definitions, SEC and FTC Enforcement.By the end of this module, you'll be able to define AI washing and identify common patterns (loose 'AI' labeling, exaggerated predictive claims, predefined-script chatbots marketed as natural-language AI). You'll also apply SEC Gensler 2023 enforcement stance and Section 5 of the FTC Act to evaluate AI-marketing claims for risk of regulatory action.How to engage: Start with the first lesson and proceed in order. Read the per-lesson takeaways after each video. Take the practice quiz at the end of the module to check your understanding before moving on.
IP Infringement in AI: Getty, New York Times, and Music Publishers Cases
- This module of AI Risk Mitigation and Legal Strategies — IP Infringement in AI: Getty, New York Times, and Music Publishers Cases — covers 1 lesson: IP Infringement in AI: Getty, New York Times, and Music Publishers Cases.By the end of this module, you'll be able to analyze the case-law landscape (Getty Images v. Stability AI, New York Times v. Microsoft/OpenAI, Music Publishers v. Anthropic) to identify the IP-infringement risk patterns in AI training data. You'll also differentiate copyright infringement, DMCA CMI removal, open-source license violations, and unfair competition as distinct legal theories applicable to AI training data.How to engage: Start with the first lesson and proceed in order. Read the per-lesson takeaways after each video. Take the practice quiz at the end of the module to check your understanding before moving on.
IP Hypothetical Cases and Strategic Actions: Open-Source Licenses and Audit Questions
- This module of AI Risk Mitigation and Legal Strategies — IP Hypothetical Cases and Strategic Actions: Open-Source Licenses and Audit Questions — covers 1 lesson: IP Hypothetical Cases and Strategic Actions: Open-Source Licenses and Audit Questions.By the end of this module, you'll be able to apply the IP risk-audit framework to a hypothetical scenario (open-source GPL license analysis, AI voice-modification copyright analysis) and identify the specific compliance gaps. You'll also recommend strategic actions for IP risk mitigation: training-data audits, vendor indemnification, open-source-license compliance documentation, and CMI preservation across the AI pipeline.How to engage: Start with the first lesson and proceed in order. Read the per-lesson takeaways after each video. Take the practice quiz at the end of the module to check your understanding before moving on.
Data Privacy in AI: BIPA Lawsuits, Privacy Risk Assessment, and Vendor Management
- This module of AI Risk Mitigation and Legal Strategies — Data Privacy in AI: BIPA Lawsuits, Privacy Risk Assessment, and Vendor Management — covers 1 lesson: Data Privacy in AI: BIPA Lawsuits, Privacy Risk Assessment, and Vendor Management.By the end of this module, you'll be able to evaluate FTC enforcement risk (Cambridge Analytica deletion remedy, Ever Album, WW International) and BIPA biometric-privacy litigation (Facebook Texas, Vimeo, Macy's vendor-tainted data) for a representative AI deployment. You'll also construct a data-privacy compliance program with the five strategic actions Kempe recommends — data governance program, AI-specific privacy policies, privacy impact assessments, DPA/vendor-contract amendments, and employee training.How to engage: Start with the first lesson and proceed in order. Read the per-lesson takeaways after each video. Take the practice quiz at the end of the module to check your understanding before moving on.