kghe3X
There is recent research in this area.
First, Pascal's wager is flawed in that it assumes there are two known outcomes, when the outcomes are unknown in both quality and quantity. For example, there might be a god that punishes belief with infinite negative reward.
Second, killing the chicken humanely isn't without cost. Consider how cheap it is to toss the male chicks straight into the meat grinder at the hatchery facilities. As an aside, I'm surprised you went with "killing humanely" as opposed to not killing in the first place. I'm not sure how that fits into your model of ethics.
Third, I disagree that there is no downside to treating "non-sentient" AI well. There's yet no well-defined boundary for sentience, so have fun treating every grain of sand "well" under some yet-to-be-specified definition of "well". It's not even clear that shutting down an AI is unethical, especially if it feels no pain and can be started up again, or cloned, or stuck in a simulation...
Finally, designing an intelligence at all seems fraught with ethical dilemmas (see designer babies), but engineering a reward (presumably, a priori, against the AI's will) into the termination routine seems particularly twisted to me.
https://www.ietf.org/archive/id/draft-peabody-dispatch-new-u...
But how did GPT-3 come up with this paragraph? By generating a word that fit the context we provided. And then another one. And then another one. The model never saw, touched or tasted pineapples—it just processed all the texts on the Internet that mention them.
Up to this point, the article sticks to its thesis that humans have a tendency to ascribe real-world experience to the agents generating fluent text.
And yet reading this paragraph can lead the human mind – even that of a Google engineer – to imagine GPT-3 as an intelligent being that can reason about peanut butter and pineapple dishes.
And with this line they jump past that thesis into an implication that AI can't reason about concepts it hasn't experienced physically with a human body. This is obviously incorrect, we humans reason all the time about things we haven't directly experienced.
I think important concepts in evaluating different types of intelligence are the model learning abstraction, mapping between concepts, and reasoning correctly given the information available in its training data. Does GPT-3 have an understanding of abstractions like objects, combinations, food, flavor? Why does it need to have tasted pineapple to infer that sentence? It seems to know that peanut butter and savory are associated.
Can an educated person, blind from birth, not infer that if it is day time and it is not cloudy, then the sky is blue? Surely they can be considered to possess intelligence, despite never experiencing color directly.
1. If simulation of a mental phenomenon is not equivalent, in essence, to the phenomenon itself, then what's a meaningful difference between the two? What is this elusive essence of the phenomenon and why is it a requirement in any meaningful definition of intelligence, consciousness, sentience, etc? If we build a silicon brain some day that passes as human, does it matter that its essence is different from a carbon-based brain? 2. Searle's Chinese Room neglects to acknowledge that the room itself is what would be exhibiting intelligence, not the homonculus within. His argument fails by presuming without evidence that consciousness is not an emergent phenomenon. 3. Of course we don't expect the computer to urinate on the desk, just as we don't expect a silicon mind to produce serotonin. That's irrelevant to the question of whether or not it exhibits the qualities or behaviors that we associate with consciousness.
I guess I just don't understand why there needs to be this added, untestable, metaphysical requirement attached to all of these words. And my question to those who suggest this is, what would it convince you otherwise?