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As companies rush to implement AI and automated decision-making tools, they may be walking into a legal minefield. On this episode of Today in Tech, host Keith Shaw speaks with attorney Rob Taylor from Carstens, Allen & Gourley about the growing legal risks tied to agentic AI, automated hiring, and the rise of ADM (automated decision-making) regulations.
Rob breaks down:
* Why AI tools used in hiring and insurance may trigger liability
* How companies are getting ADM compliance wrong
* What laws already apply even without new AI regulations
* Real-world examples like credit scoring, job screening, and sentiment analysis
* Why disclosure, explainability, and data retention are essential
* Who’s liable: the company or the AI developer?
Chapters
00:00 Legal risks in AI and ADM
01:00 Common mistakes companies make
06:00 High-risk use cases: hiring, credit, insurance
10:00 Disclosure and consent pitfalls
15:00 Explainability and record-keeping laws
20:00 Unintentional bias in hiring algorithms
28:00 Who is liable: developer or deployer?
34:00 What future lawsuits might target
37:00 Fixing flawed AI governance
41:00 Litigation as the great teacher
By Foundry3.4
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As companies rush to implement AI and automated decision-making tools, they may be walking into a legal minefield. On this episode of Today in Tech, host Keith Shaw speaks with attorney Rob Taylor from Carstens, Allen & Gourley about the growing legal risks tied to agentic AI, automated hiring, and the rise of ADM (automated decision-making) regulations.
Rob breaks down:
* Why AI tools used in hiring and insurance may trigger liability
* How companies are getting ADM compliance wrong
* What laws already apply even without new AI regulations
* Real-world examples like credit scoring, job screening, and sentiment analysis
* Why disclosure, explainability, and data retention are essential
* Who’s liable: the company or the AI developer?
Chapters
00:00 Legal risks in AI and ADM
01:00 Common mistakes companies make
06:00 High-risk use cases: hiring, credit, insurance
10:00 Disclosure and consent pitfalls
15:00 Explainability and record-keeping laws
20:00 Unintentional bias in hiring algorithms
28:00 Who is liable: developer or deployer?
34:00 What future lawsuits might target
37:00 Fixing flawed AI governance
41:00 Litigation as the great teacher

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