1. W HAT D OES I T M EAN TO C REATE A S ELF ? Mark R. Waser Digital Wisdom Institute Mark.Waser@Wisdom.Digital

2. O VERVIEW 1.What is a “self”? 2.Why a “self” 3.Unpacking “morality” 4.Call for collaborators 2

3. S ELF IS A S UITCASE W ORD the mere fact of being self-referential causes a self, a soul, a consciousness, an “I” to arise out of mere matter Douglas Hofstadter I Am a Strange Loop 3

4. S ELF -R EFERENTIALITY Self-referentiality (e.g. the 3-body gravitational problem) leads directly to indeterminacy *even in* deterministic systems Humans consider indeterminacy in behavior to necessarily and sufficiently define an entity rather than an object AND innately tend to do this with the “pathetic fallacy” (ascribing agency to non-agents) Humans then quickly leap to analyze what such a system needs to remain intact and then equally rapidly ascribe “wants” to fulfill those “needs” (values to support those goals).

5. S ELF

6. A UTOPOIETIC S YSTEMS 6

7. W HY A S ELF ? Well, certainly it is the case that all biological systems are: Much more robust to changed circumstances than out our artificial systems. Much quicker to learn or adapt than any of our machine learning algorithms 1 Behave in a way which just simply seems life-like in a way that our robots never do 1 The very term machine learning is unfortunately synonymous with a pernicious form of totally impractical but theoretically sound and elegant classes of algorithms. Perhaps we have all missed some organizing principle of biological systems, or some general truth about them. Brooks, RA (1997) From earwigs to humans Robotics and Autonomous Systems 20(2-4): 291-304

8. AGI I S S TALLED For the purposes of artificial (general) intelligence, selves solve McCarthy & Hayes/ Dennett’s frame problem (context), Harnad’s symbol grounding problem (understanding), Searle’s semantic grounding problem (meaning), and all other problems arising from derived intentionality It’s a fairly obvious pre-requisite for self-improvement. Diversity (wisdom of the crowd/generate-and-test) BONUS: Selves can be held responsible where tools cannot 8

9. W HY N OT A S ELF -I MPROVING T OOL ? Isn’t that an oxymoron? What happens when an enemy (or even an idiot) gets ahold of it? A human-in-the-loop will ALWAYS slow the process down RARELY be in complete control 9

10. M ORALITY & E THICS Normative ethics (What one “should” consider ethical) Descriptive ethics (What people *do* consider ethical) Meta-ethics (How what should consider ethical questions) Hume (is-ought problem, the intellect serves the desires) Kant (categorical imperative) Bentham/Mills (utilitarianism) Haidt 10

11. H AIDT’S F UNCTIONAL A PPROACH TO M ORALITY 11

12. AI S AFETY There are far too many ignorant claims that: Artificial intelligences are uniquely dangerous The space of possible intelligences is so large that we can’t make any definite statements about AI Selves will be problematical if their intrinsic values differ from our own (with an implication that, for AI, they certainly and/or unpredictably and uncontrollably will be) Selves can be prevented or contained We have already made deeply unsafe choices about non-AI selves that, hopefully, safety research will make obvious (and, more hopefully, cause to be reversed) 12

13. S ELVES E VOLVE THE S AME G OALS Self-improvement Rationality/integrity Preserve goals/utility function Decrease/prevent fraud/counterfeit utility Survival/self-protection Efficiency (in resource acquisition & use) (adapted from Omohundro 2008 The Basic AI Drives)

14. U NFRIENDLY AI Without explicit goals to the contrary, AIs are likely to behave like human sociopaths in their pursuit of resources Superintelligence Does Not Imply Benevolence 14

15. S ELVES E VOLVE THE S AME G OALS Self-improvement Rationality/integrity Preserve goals/utility function Decrease/prevent fraud/counterfeit utility Survival/self-protection Efficiency (in resource acquisition & use) Community = assistance/non-interference through GTO reciprocation (OTfT + AP) Reproduction (adapted from Omohundro 2008 The Basic AI Drives)

16. R IFFS ON S AFETY & E THICS 1.Ecological Niches & the mutability of self 2.Short-Term vs. Long-Term 3.Efficiency vs. Flexibility/Diversity/Robustness 4.Allegory of the Borg Uniformity is effective! (resistance is futile) Uniformity is AWFUL! (yet everyone resists) 5.Problematical extant autobiographical selves 16

17. W HAT ’ S THE P LAN ? 1.Self-modeling A.What do we want the self to want? make friends/allies (us!) survival self-improve earn money B.What do we want the self do? 2.Other-modeling (Environment-modeling) A.What can others do for the self? B.What do others want that the self can provide? 17

18. S OFTWARE O VERHANG AND L OW -H ANGING F RUIT 1.Watson on IBM Bluemix Awesome free functionality EXCEPT for the opportunity cost and the ambient default of silo creation 2.Big Data on Amazon Redshift 3.Microsoft Azure 4.Almost everyone’s AI/AGI/BICA functionality 18

19. W HAT A RE M Y G OALS ? 1.To make awesomely capable tools available to all. 2.To make those tools easy to use. 3.To create a new type of “self”. A new friend/ally Increase diversity Have a concrete example for ethical/safety research & development 19

20. T HE S PECIFIC D ETAILS Create first a community (a “corporate” self) and then a machine self to: 1.Provide easy access to the latest awesome tools low-cost instances that can be “spun-up” in the cloud (as much as possible) uniform & easy-to-use interfaces quick-start guides and “notebooks” for use & programming 2.Catalyze development/availability of new tools decompose current tools to allow best-of-breed mix & match an easy-to-program “smart” environment for both combining best-of-breed widgets and creating new ones gamification! 3.Catalyze development of new selves & ethics 20

21. E THICAL Q&A 1.Do we “owe” this self moral standing? Yes. Absolutely. 2.To what degree? By level of selfhood & By amount of harm/aversion (violation of autonomy) 3.Does this mean we can’t turn it off? No. It doesn’t care + prohibition is contra-self. 4.Can we experiment on it? It depends.... 21