What would a robot value? An analogy for human values – part 4 of the Valuism sequence

By Spencer Greenberg and Amber Dawn Ace  This post is part of a sequence about Valuism - my life philosophy. This post is the most technical of the sequence. Here are the first, second, third, and fifth parts of the sequence. Image created using the A.I. DALL•E 2 This is the fourth of five posts in my sequence of essays about my life philosophy, Valuism - here are the first, second, third, and fifth parts (though the last link won’t work until that essay is released). I...
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13 metaphors to give the flavor of why sufficiently advanced A.I. could be extremely dangerous

Generated with the A.I. Midjourney
1. Suppose a new species evolves on earth with the same intellectual, planning, and coordination abilities relative to us that we have relative to chimps. Chimps are faster and stronger than most humans - why don't they run the show? 2. Suppose aliens show up on earth that are far smarter than the smartest among us at all cognitive tasks. They have specific goals that aren't fully aligned with ours, are completely unconstrained by human morality, and don't value our survival. What happens ne...
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Mistakes Made by Minds and Machines

Possessed Photography on Unsplash
Written: May 3, 2021 | Released: July 16, 2021 Fascinatingly, human minds and machine learning algorithms are subject to some of the same biases and prediction problems. This is probably not a coincidence - learning has fundamental challenges. Here is a list of some issues that afflict both minds and machines: 1. Recency Bias For both humans and machine learning algorithms, the most recently processed information tends to override what was learned from older data. This is sensibl...
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