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
-
Measuring Intelligence and Growth Rate: Variations on Hibbard's Intelligence Measure
Samuel Alexander and Bill Hibbard.
Journal of Artificial General Intelligence 12(1), 1-25. January 2021.
On arxiv.org
- How (Not) to Think About Artificial Intelligence
Bill Hibbard. Talk broadcast on PBS. December 2018.
-
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
Bill Hibbard.
The Fifth Conference on Artificial General Intelligence (AGI-12). 2012.
This paper won the
Singularity Institute's Turing Prize for the Best AGI
Safety Paper at AGI-12 and AGI Impacts.
-
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
- [Message
Contains No Recognizable Symbols].
A story about a technological singularity subject to the constraint
that natural human authors are unable to depict the actions and dialog
of super-intelligent minds. In particular, the languages of
super-intelligent minds will be unintelligible to natural humans. April 2007.
-
Values, Simulation and Symbiosis in the Global Brain
Bill Hibbard. This was written in response to a request from the
organizers of the First Global Brain Workshop for a special edition
of Technological Forecasting and Social Change, but it
is now clear the special edition will never be for reasons known
only to the organizers.
-
Comment on the 2006 Singularity Summit.
The Summit should include an advocate of regulating, but not banning, AI.
-
A Review of Ray Kurzweil's The Singularity is Near.
A good book, but it fails to adequately address the dangers of AI.
-
The Ethics and Politics of Super-Intelligent Machines
Bill Hibbard. Rejected by the 2005 AAAI Fall Symposium on Machine
Ethics, based on a poor reviewing process (however, the organizers
did invite me to present a poster and short abstract). Here are
the reviews and my rebuttals, plus a brief assessment of the symposium
technical report.
-
Consciousness and Souls, letter to the editor of the New York
Times, 12 September 2004.
-
Critique of the SIAI Guidelines on Friendly AI . 2003.
Critique of the SIAI Collective Volition Theory . 2005.
-
Network Diameter and Emotional Values in the Global Brain
Bill Hibbard. First Global Brain Workshop. Brussels. 2001.
More Information
For more information about the SSEC Machine Intelligence Project
please contact
Bill Hibbard.
Also see my
Singularity Notes.