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AI Safety and Reproducibility: Establishing Robust Foundations for the Neuropsychology of Human Values

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Computer Safety, Reliability, and Security (SAFECOMP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11094))

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Abstract

We propose the creation of a systematic effort to identify and replicate key findings in neuropsychology and allied fields related to understanding human values. Our aim is to ensure that research underpinning the value alignment problem of artificial intelligence has been sufficiently validated to play a role in the design of AI systems.

The views expressed herein are those of the author and do not necessarily reflect the views of Vicarious AI.

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References

  1. Ainley, V., et al.: ‘Bodily precision’: a predictive coding account of individual differences in interoceptive accuracy. Philos. Trans. R. Soc. B 371(1708) (2016)

    Google Scholar 

  2. Amodei, D., Olah, C., Steinhardt, J., Christiano, P., Schulman, J., Mané, D.: Concrete problems in AI safety. arXiv preprint arXiv:1606.06565 (2016)

  3. Barrett, L.F.: How Emotions are Made: The Secret Life of the Brain. Houghton Mifflin Harcourt, Boston (2017)

    Google Scholar 

  4. Baum, S.D.: Reconciliation between factions focused on near-term and long-term artificial intelligence. AI Soc. 1–8 (2017)

    Google Scholar 

  5. Björnsdotter, M., Olausson, H.: Vicarious responses to social touch in posterior insular cortex are tuned to pleasant caressing speeds. J. Neurosci. 31(26), 9554–9562 (2011)

    Article  Google Scholar 

  6. Bostrom, N.: Superintelligence: Paths, Dangers, Strategies. Oxford University Press, Oxford (2014)

    Google Scholar 

  7. Brown, B.B.: Delphi process: a methodology used for the elicitation of opinions of experts. Technical report, Rand Corp, Santa Monica, CA (1968)

    Google Scholar 

  8. Campbell, P. (ed.): Challenges in Irreproducible Research, vol. 526. Nature, London (2015)

    Google Scholar 

  9. Damasio, A.: Self Comes to Mind: Constructing the Conscious Brain. Vintage, New York (2012)

    Google Scholar 

  10. Ekman, P., Friesen, W.V., Ellsworth, P.: Emotion in the Human Face: Guide-lines for Research and an Integration of Findings. Pergamon, Oxford (1972)

    Google Scholar 

  11. Errington, T.M.: Science forum: an open investigation of the reproducibility of cancer biology research. eLife 3, 4333 (2014)

    Article  Google Scholar 

  12. Evans, O., Goodman, N.D.: Learning the preferences of bounded agents. In: NIPS Workshop on Bounded Optimality (2015)

    Google Scholar 

  13. Evans, O., Stuhlmüller, A., Goodman, N.D.: Learning the Preferences of Ignorant, Inconsistent Agents. arXiv:1512.05832 (2015)

  14. Grace, K., Salvatier, J., Dafoe, A., Zhang, B., Evans, O.: When Will AI Exceed Human Performance? Evidence from AI Experts. ArXiv e-prints, May 2017

    Google Scholar 

  15. Harrington, A., Zajonc, A.: The Dalai Lama at MIT. Harvard University Press, Cambridge (2006)

    Google Scholar 

  16. Horton, R.: What’s medicine’s 5 sigma?. Lancet 385(9976) (2015)

    Google Scholar 

  17. LeDoux, J.E., Pine, D.S.: Using neuroscience to help understand fear and anxiety: a two-system framework. Am. J. Psychiatry 173(11), 1083–1093 (2016)

    Article  Google Scholar 

  18. Munafò, M.R.: A manifesto for reproducible science. Nat. Hum. Behav. 1, 0021 (2017)

    Article  Google Scholar 

  19. Panksepp, J.: Affective Neuroscience: The Foundations of Human and Animal Emotions. Oxford University Press, New York (1998)

    Google Scholar 

  20. Porges, S.W., Furman, S.A.: The early development of the autonomic nervous system provides a neural platform for social behaviour: a polyvagal perspective. Infant Child Dev. 20(1), 106–118 (2011)

    Article  Google Scholar 

  21. Russell, S.: Should we fear supersmart robots? Sci. Am. 314(6), 58–59 (2016)

    Article  Google Scholar 

  22. Sarma, G.P.: Doing Things Twice (Or Differently): Strategies to Identify Studies for Targeted Validation. ArXiv e-prints, Mar 2017

    Google Scholar 

  23. Sarma, G.P., Hay, N.J.: Mammalian value systems. Informatica 41(3) (2017)

    Google Scholar 

  24. Solms, M., Turnbull, O.: The Brain and the Inner World: An Introduction to the Neuroscience of Subjective Experience. Karnac Books, London (2002)

    Google Scholar 

  25. Sotala, K.: Defining human values for value learners. In: AAAI Workshop: AI, Ethics, and Society (2016)

    Google Scholar 

  26. Sullins, J.P.: When is a robot a moral agent?. Int. Rev. Inf. Ethics 6 (2006)

    Google Scholar 

  27. The Open Science Collaboration: Estimating the reproducibility of psychological science. Science 349(6251) (2015)

    Google Scholar 

  28. Tomasello, M.: The Cultural Origins of Human Cognition. Harvard University Press, Cambridge (1999)

    Google Scholar 

  29. Wachter, S., Mittelstadt, B., Floridi, L.: Transparent, explainable, and accountable AI for robotics. Sci. Robot. 2 (2006)

    Google Scholar 

  30. Wortham, R.H., Theodorou, A., Bryson, J.J.: What does the robot think? Transparency as a fundamental design requirement for intelligent systems. In: IJCAI 2016 Ethics for AI Workshop (2016)

    Google Scholar 

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Acknowledgements

We would like to thank Owain Evans and several anonymous reviewers for insightful discussions on the topics of value alignment and reproducibility in psychology and neuroscience.

Author information

Authors and Affiliations

  1. School of Medicine, Emory University, Atlanta, GA, USA

    Gopal P. Sarma

  2. Vicarious AI, San Francisco, CA, USA

    Nick J. Hay

  3. Department of Psychology, Northwestern University, Evanston, IL, USA

    Adam Safron

Authors
  1. Gopal P. Sarma
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  2. Nick J. Hay
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  3. Adam Safron
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Corresponding author

Correspondence to Gopal P. Sarma .

Editor information

Editors and Affiliations

  1. Mälardalen University, Västerås, Sweden

    Barbara Gallina

  2. Norwegian University of Science and Technology, Trondheim, Norway

    Amund Skavhaug

  3. AIT Austrian Institute of Technology, Vienna, Austria

    Erwin Schoitsch

  4. Thales Deutschland GmbH, Ditzingen, Germany

    Friedemann Bitsch

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Sarma, G.P., Hay, N.J., Safron, A. (2018). AI Safety and Reproducibility: Establishing Robust Foundations for the Neuropsychology of Human Values. In: Gallina, B., Skavhaug, A., Schoitsch, E., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2018. Lecture Notes in Computer Science(), vol 11094. Springer, Cham. https://doi.org/10.1007/978-3-319-99229-7_45

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  • DOI: https://doi.org/10.1007/978-3-319-99229-7_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99228-0

  • Online ISBN: 978-3-319-99229-7

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