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The SSEC Machine Intelligence Project

"It is all too evident that our moral thinking simply has not been able to keep pace with the speed of scientific advancement. Yet the ramifications of this progress are such that it is no longer adequate to say that the choice of what to do with this knowledge should be left in the hands of individuals." - Tenzin Gyatso, the 14th Dalai Lama, in the New York Times on 12 November 2005, the day he spoke to the annual meeting of the Society for Neuroscience. The technology of mind will have profound consequences for humanity, and humanity must be educated about and exercise collective, democratic control over this technology. The Machine Intelligence Project at the Space Science and Engineering Center (SSEC) of the University of Wisconsin-Madison focuses on how to create machine intelligence, and on the social consequences of machine intelligence. My approach is to look for connections between neuroscience, the analysis of how human brains work, and computer science, the synthesis of artificial solutions to the problem of intelligence. The understanding of how intelligence works is critical for analyzing the social consequences of machine intelligence.

There are three great scientific questions facing humanity: how does physics work, how does life work, and how does intelligence work? An answer to the question of how intelligence works, and a consequent ability to build intelligent machines, will help answer the other two great questions and help solve many practical problems facing humanity.

Publications

  • Self-Modeling Agents and Reward Generator Corruption
    • Bill Hibbard. AAAI-15 Workshop on AI and Ethics. January 2015.
  • Ethical Artificial Intelligence
    • Bill Hibbard. Book draft. November 2014.
  • Exploratory Engineering in AI
    • Luke Muehlhauser and Bill Hibbard. Communications of the ACM. 7(9) , 32-34. 2014.
  • Self-Modeling Agents Evolving in Our Finite Universe
    • Bill Hibbard. The Seventh Conference on Artificial General Intelligence (AGI-14). 2014.
  • Avoiding Unintended AI Behaviors
  • Decision Support for Safe AI Design
    • Bill Hibbard. The Fifth Conference on Artificial General Intelligence (AGI-12). 2012.
    • Turing Tests with Turing Machines.
    • Jose Hernandez-Orallo, Javier Insa, David Dowe and Bill Hibbard. Turing-100. The Alan Turing Centenary, ed. Andrei Voronkov. 140-156. June 2012.
    • Model-based Utility Functions.
    • Bill Hibbard. The Journal of Artificial General Intelligence. 3 , 1-24. 2012.
  • Measuring Agent Intelligence via Hierarchies of Environments
    • Bill Hibbard. The Fourth Conference on Artificial General Intelligence (AGI-11). 2011.
  • Societies of Intelligent Agents
    • Bill Hibbard. The Fourth Conference on Artificial General Intelligence (AGI-11). 2011.
  • Nietzsche's Overhuman is an Ideal Whereas Posthumans Will be Real
    • Bill Hibbard. Journal of Evolution & Technology 21 , No. 1, 9-12. 2010.
  • Bias and No Free Lunch in Formal Measures of Intelligence
    • Bill Hibbard. The Journal of Artificial General Intelligence. 1 , 54-61. 2009.
  • Distribution of Environments in Formal Measures of Intelligence
    • Bill Hibbard. The Second Conference on Artificial General Intelligence (AGI-09). 2009.
  • Adversarial Sequence Prediction
    • Bill Hibbard. The First Conference on Artificial General Intelligence (AGI-08). 2008.
  • Open Source AI
    • Bill Hibbard. AGI-08 Workshop on the Sociocultural, Ethical and Futurological Implications of Artificial General Intelligence. 2008.
  • The Technology of Mind and a New Social Contract
    • Bill Hibbard. Journal of Evolution & Technology 17 , No. 1, 13-22. 2008.
  • Reinforcement Learning as a Context for Integrating AI Research
    • Bill Hibbard. 2004 AAAI Fall Symposium on Achieving Human-Level Intelligence through Integrated Systems and Research.
  • Should Standard Oil Own the Roads?
    • Bill Hibbard. Computer Graphics 37 , No. 1, 5-6. 2003.
  • Super-Intelligent Machines
    • Bill Hibbard. New York. Kluwer Academic/Plenum Publishers. 2002.
  • Emotions Versus Laws as the Keys to the Ethical Design of Intelligent Machines
    • W. L. Hibbard. Proc. 6th World Multiconference on Systemics, Cybernetics and Informatics, Vol. XIII, 469-472. 2002.
  • Super-intelligent Machines
    • Bill Hibbard. Computer Graphics 35 , No. 1, 11-13. 2001.

Posters and Presentations

On-line Publications

More Information

For more information about the SSEC Machine Intelligence Project please contact Bill Hibbard.

Also see my Singularity Notes.