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Coursera

Advising Business Clients on Their Use of AI

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Overview

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Welcome to Advising Business Clients on Their Use of AI . This course covers 4 modules: Foundations: Introduction to AI and IP Issues in AI Training Data; Data Privacy in AI: Risk Assessment, Lawsuits, and Compliance; AI Bias in Employment: Lawsuits, Federal Law, and Mitigation Strategies; and AI Contracts and AI Policy: Governance, Liability, and Compliance. Each module includes video lessons, key-takeaway readings, a practice quiz, and a hands-on activity. By the end, you'll be able to distinguish the four IBM-defined types of AI (reactive, limited-memory, theory-of-mind, self-aware) and identify which type applies to common business AI deployments. You'll also analyze the IP-infringement risk landscape — Getty Images v. Stability AI, Doe v. GitHub, DMCA copyright-management-information rules, and open-source license attribution — to determine when an organization's AI training data creates litigation exposure. Key milestones: Module practice quizzes (formative) · Module activities (...

Syllabus

  • Foundations: Introduction to AI and IP Issues in AI Training Data
    • This module of Advising Business Clients on Their Use of AI — Foundations: Introduction to AI and IP Issues in AI Training Data — covers 1 lesson: Foundations: Introduction to AI and IP Issues in AI Training Data.By the end of this module, you'll be able to distinguish IBM's four types of AI and identify which type applies to common business AI deployments. You'll also analyze the Getty Images v. Stability AI and Doe v. GitHub cases to determine when AI training data creates IP-infringement exposure under copyright law, the DMCA, and open-source license terms.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: Risk Assessment, Lawsuits, and Compliance
    • This module of Advising Business Clients on Their Use of AI — Data Privacy in AI: Risk Assessment, Lawsuits, and Compliance — covers 1 lesson: Data Privacy in AI: Risk Assessment, Lawsuits, and Compliance.By the end of this module, you'll be able to evaluate FTC enforcement risk patterns (Cambridge Analytica, Ever Album, WW International) and biometric-privacy litigation under BIPA (Clearview AI / Macy's class actions). You'll also apply Kempe's data privacy principles (purpose specification, data minimization) and the privacy-risk-assessment + vendor-questionnaire framework to a representative AI deployment.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.
  • AI Bias in Employment: Lawsuits, Federal Law, and Mitigation Strategies
    • This module of Advising Business Clients on Their Use of AI — AI Bias in Employment: Lawsuits, Federal Law, and Mitigation Strategies — covers 1 lesson: AI Bias in Employment: Lawsuits, Federal Law, and Mitigation Strategies.By the end of this module, you'll be able to identify AI-bias-in-employment risks using the Amazon hiring algorithm, Mobley v. Workday, and iTutor Group cases as exemplars of the federal anti-discrimination statutes (Title VII, ADEA, ADA) that apply to AI tools. You'll also apply EEOC 2022 guidance and state/local laws (Illinois AI Video Interview Act, NYC Local Law 144) to design an audit-and-mitigation plan for an AI-driven employment decision tool.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.
  • AI Contracts and AI Policy: Governance, Liability, and Compliance
    • This module of Advising Business Clients on Their Use of AI — AI Contracts and AI Policy: Governance, Liability, and Compliance — covers 1 lesson: AI Contracts and AI Policy: Governance, Liability, and Compliance.By the end of this module, you'll be able to construct an AI-vendor contract covering Kempe's six key provisions: data ownership (training data, input prompts, output), AI governance, regulatory compliance, vendor indemnification, uncapped liability for reputational damage, AI-specific security and privacy. You'll also recommend an AI policy with the six critical components — clear roles/responsibilities, risk management, transparency, fairness, data privacy, and human oversight — including a routine auditing cadence rather than a one-time check.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.

Taught by

NBI - National Business Institute

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