Moreover, insurance organizations are leveraging AI, ensuring ethical integration, and fostering a workforce that's adaptable, skilled, and ready for the evolving landscape of tech-infused business models.
ETHICS
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OpenAI’s vague data usage policies raise transparency concerns
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OpenAI have been infuriatingly vague about what "using ChatGPT conversations to help improve our models" actually means They have various opt-out options even for free usage these days but it's hard to keep track of where they are and how they work
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Lack of transparency in AI model training data usage
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Right, the most frustrating thing about this is that the complete lack of of transparency about how training works (and how the data is used) means it's impossible to confidently state how it all really works
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Common Misconceptions About How AI Models Learn
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I wonder how common it is for people to confidently hold an inaccurate idea of how AI models work where they believe that anything they show the model is instantly memorized and added to its "knowledge" of the world
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AI as Software Process Not Conscious Entity Anthropomorphism
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I think a lot of the problem is that people see AI as an entity, rather than a software process that runs on text to produce an output. Entities remember what they see, even if they pretend they are keeping secrets. Anthropomorphism can be a problem at times!
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Regulated Industries Legal Obligations for AI Training Data
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And of course:
1) Regulated industries & service firms have legal obligations that supersede these agreements (though some systems are HIPAA compliant, etc.)
2) Even if your data is used for training, it probably couldn't be used to reconstruct the original document in any case -
LLM Privacy Concerns: Training Data Usage and Enterprise Trust
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Privacy still comes up as a big issue when I talk to firms about AI. But the privacy risk is if your inputs are used as training data. Of course, all the big LLMs have plans where they agree not to do that. People are suspicious of LLMs in way they aren't for other cloud apps.
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Algorithmic Transparency Essential for Protecting Democratic Institutions
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@vonderleyen @pierrepinna @ipfconline1 We need algorithmic transparency on platforms to prevent democracy being dismantled brick by brick.
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Politics of AI Power: Precision Matters in Partisan Debates
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These powers *are* politics. Politics doesn't stop and end with partisan side-taking. And if we can't be precise then we can't win.
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Big Tech’s Ad-Surveillance Model and Media Centralization Problem
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It's the business model, the ad-surveillance driven incentives, and the centralization of our media ecosystem that need to be addressed. This does none of that, it simply gives a large co the ability to define "nuance" "evidence based reasoning" etc..