2025-01-21 One-Minute Post
A global benchmark for AI regulation emphasizing privacy, while data privacy professionals face severe underfunding. HR’s use of AI raises ethical concerns about fairness and privacy. Recent employment law updates highlight the potential for biased outcomes. AI’s trust problem is linked to bias, with healthcare facing challenges of AI bias and health inequity.
Articles we found interesting:
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1. Protect your company's data privacy in the age of AI - Technical.ly link Highlight: Taken together, these landmark pieces of legislation set a global benchmark for AI regulation that emphasizes the need for privacy-preserving …
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2. Data privacy professionals are severely underfunded – and it's only going to get worse link Highlight: … AI Act. “As the threat landscape continues to evolve in complexity, privacy is becoming a sector which is increasingly difficult to operate in …
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3. The ethics of AI in HR: Balancing efficiency with fairness and privacy - People Matters link Highlight: The use of AI in HR raises significant ethical concerns, especially regarding fairness, privacy, and transparency. HR professionals must carefully …
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4. Recent Employment Law Updates in Artificial Intelligence | Lerch, Early & Brewer - JDSupra link Highlight: Inputs and models may embed assumptions and datasets that disparately impacts certain protected classes or produce biased outcomes in ways that are …
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5. Using Blockchain to Build Customer Trust in AI - Harvard Business Review link Highlight: And bias is just one of a multitude of reasons why AI is considered a “black box” with a trust problem. Last year Pew Research found that 52% of …
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6. How to Make Healthcare With AI More Equitable - Gastroenterology & Endoscopy News link Highlight: … AI into healthcare practice is AI bias and health inequity, Dr. Hightower said “bias occurs throughout the AI life cycle.” Clinicians involved in …
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