Raw LLM Responses

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Comment
I don't think the world is made better by hiding the truth, not in the long run. I also find myself wondering how this idea might shift the Overton window - should algorithmic fairness apply to research data? For that matter, how do you imagine researchers will be affected by a world wherein 'algorithmic fairness' is the status quo? What questions might they not ask, when everything appears fair? To gain knowledge, we must be curious. Curiosity is expressed in the form of a question, and questions arise when we see something 'odd.' We only get to live our one life, with our personal experiences. If everything we're presented with shows a 'fair' world to us, how would we know if there's a problem? And without popular support, how do you imagine things will get done? How many people could I rally to my cause when my cause is effectively hidden from them? Who would believe me, when everything they've seen shows a contrary picture to what I present? For these reasons, I do not think 'algorithmic fairness' will have the results that the ostensibly well-intentioned people who seek it may wish for. At least not limited thereto. I think everyone needs a world without blinders in order that they can navigate reality to the best of their ability.
youtube AI Harm Incident 2019-12-14T23:3… ♥ 3
Coding Result
DimensionValue
Responsibilitynone
Reasoningmixed
Policyunclear
Emotionmixed
Coded at2026-04-27T06:26:44.938723
Raw LLM Response
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