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Ethical & Mathematical Adventures in Coding Better Children

Ethical & Mathematical Adventures in Coding Better Children. Jeff Medina Senior Systems Engineer, Lockheed Martin TSS Associate Director, The Singularity Institute for Artificial Intelligence Fellow, The Institute for Ethics and Emerging Technologies.

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Ethical & Mathematical Adventures in Coding Better Children

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  1. Ethical & Mathematical Adventures in Coding Better Children Jeff MedinaSenior Systems Engineer, Lockheed Martin TSSAssociate Director, The Singularity Institute for Artificial IntelligenceFellow, The Institute for Ethics and Emerging Technologies

  2. But first…A Brief Digressionto Bring Everyone-Less-εto Near-Agreement onthe Presumption of the Moral Significance of Behaviorally-Personish Artificial Beings

  3. Moral Equivalence in Practice [MEIP]An “artificial” being should be treated at least as well as if she were a “natural” being in the nearest cognitive-behavioral class. SO, for example, • treat ‘artificial’ people like people, • and ‘artificial’ puppies like puppies, • but treat ‘artificial’ puppies-with-people-level-minds like people, and so forth. More succinctly, TREAT ALIFE LIKE LIFE.

  4. Why MEIP? A brief argument • P(x in Y | For nearly all F, yF  xF) >> 0,and arguably > 0.5 • If (x in Y) & humans act as if (x not in Y), massive suffering ensues, scaling linearly with C(X), with C(X) itself plausibly growing exponentially. • In the opposite case, the expected neg. utility (from wasted resources) is less than above due to ALife per capita resource efficiency.

  5. What responsibility do we have for the lives we create? • Parents…Gods…and A.G.I. developers?All quite similar, as it turns out…

  6. Procreative Beneficence(Savulescu 2001)Parents “should select the child, of the possible children they could have, who is expected to have the best life, or at least as good a life as the others, based on the relevant, available information.” Case 1:The responsibility of parents toward their children

  7. Analogue to Case 1:For those who would build (or birth) A.G.I. • Programmatic Beneficence!(Medina, just now)The A.G.I.-expectant should select the A.G.I., of the possible A.G.I. they could build, who is expected to have the best life, or at least as good a life as the others, based on the relevant, available information.

  8. Case 2:Theodicy – Epicurus et al.’s problem of evil If (insert favorite deity here) is • maximally morally good[wants to help us] • omnipotent[ is capable of helping us] • and omniscient……..[ knows how to help us]

  9. WHY DOES LIFE SUCK?!?(relatively speaking)

  10. This reasoning reverse-implicates obligations for A.G.I. creators… With greater control over a sentient being’s life comes greater responsibility to do right by it.

  11. But how much is enough? • Do we satisfice? Arbitrary! Nooooo… • Do we maximize? Yes! … but how?

  12. Considerations • The intelligence of the A.G.I. designer constrains δI given n resources and t time. • Does finding further improvements require similar intelligence & resources, or more? If more, how much more? Is scaling linear, exponential, … • Create the A.G.I. at intelligence equal to or greater than the creator’s, and provide n resources to the A.G.I. for use in improving herself?(Bad idea in the case of humans, but maybe less so for A.G.I. How malleable is your design after the ‘initial developmental period’?)

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