2024-10-16 One-Minute Post
LinkedIn is using user data for AI training, while in-cab AI technology raises privacy concerns. Mitigating the risk of generative AI is crucial for privacy. The World Economic Forum emphasizes fairer data systems, and healthcare AI must address biases. Developing trustworthy AI requires addressing biases embedded in training data.
Articles we found interesting:
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1. Five ways to stop companies from using your data in new ways - Washington Post link Highlight: For LinkedIn using your posts to train its AI: Log into your LinkedIn account and tap or click on your headshot and select Settings → Data privacy → …
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2. Advancements in In-Cab Technology Leads to Privacy Concerns and Litigation | JD Supra link Highlight: However, with the advancement of artificial intelligence (AI) … Drivers are making claims that, without proper disclosure and consent, AI-enabled dash …
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3. Technical Considerations for Business Leaders Operationalizing Gen AI link Highlight: Mitigating the risk of generative AI means implementing technologies and employing techniques that help ensure security, privacy, and responsible AI …
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4. A framework for advancing data equity in a digital world | World Economic Forum link Highlight: As technologies like machine learning and generative artificial intelligence (AI) … Building fairer data systems: Lessons from addressing racial bias …
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5. Bias Awareness helps bridge the gap between human and AI healthcare - News-Medical link Highlight: … biases in mind at all stages of AI proliferation, from development to adoption. Developers of AI systems should both aim to minimize bias inherent …
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6. KAVI PATHER: Can we develop AI that everyone can trust? - BusinessLIVE link Highlight: AI bias refers to the tendency of AI systems to produce skewed outcomes that reflect biases embedded in the data used to train them or in the …
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