4
Shared Docs
4
Same-Page
8 / 4
Mentions
at they tend to favor or ignore. Surely (ding!)?, any man who could beat a woman at being perceived to be a woman would be an intelligent agent. What Turing did not foresee is the power of deep-learning AI to acquire this wealth of information in an exploitable form without having to understand it. Turing
the CIRL framework, one can formulate and solve the off-switch problem—that is, the problem of how to prevent a robot from disabling its off-switch. (Turing may rest easier.) A robot that’s uncertain about human preferences actually benefits from being switched off, because it understands that the human w
nd the Bureaucratization of the Senses; Machine in the Studio: Constructing the Postwar American Artist; and The Global Work of Art. David Kaiser is Germeshausen Professor of the History of Science and professor of physics at MIT, and head of its Program in Science, Technology & Society. He is the author of Ho
a topic absent from a typical computer-science education: the physical configuration of a 118 HOUSE_OVERSIGHT_016921 computation. Von Neumann and Turing posed their questions as theoretical studies, because it was beyond the technology of their day to realize them. But with the convergence of communic
ce in terms of feedback, exploring the cultural rather than engineering uptake of this idea. She begins with primary readings by Wiener, Shannon, and Turing and then pivots from the scientists and engineers to the work and ideas of artists, feminists, postmodern theorists. Her goal: to come up with a new
e need a new set of guiding metaphors?” 108 HOUSE_OVERSIGHT_016911 “INFORMATION” FOR WIENER, FOR SHANNON, AND FOR US David Kaiser David Kaiser is Germeshausen Professor of the History of Science and professor of Physics at MIT, and head of its Program in Science, Technology & Society. He is the author of Ho
at they tend to favor or ignore. Surely (ding!)?, any man who could beat a woman at being perceived to be a woman would be an intelligent agent. What Turing did not foresee is the power of deep-learning AI to acquire this wealth of information in an exploitable form without having to understand it. Turing
the CIRL framework, one can formulate and solve the off-switch problem—that is, the problem of how to prevent a robot from disabling its off-switch. (Turing may rest easier.) A robot that’s uncertain about human preferences actually benefits from being switched off, because it understands that the human w
nd the Bureaucratization of the Senses; Machine in the Studio: Constructing the Postwar American Artist; and The Global Work of Art. David Kaiser is Germeshausen Professor of the History of Science and professor of physics at MIT, and head of its Program in Science, Technology & Society. He is the author of Ho
a topic absent from a typical computer-science education: the physical configuration of a 118 HOUSE_OVERSIGHT_016338 computation. Von Neumann and Turing posed their questions as theoretical studies, because it was beyond the technology of their day to realize them. But with the convergence of communic
ce in terms of feedback, exploring the cultural rather than engineering uptake of this idea. She begins with primary readings by Wiener, Shannon, and Turing and then pivots from the scientists and engineers to the work and ideas of artists, feminists, postmodern theorists. Her goal: to come up with a new
e need a new set of guiding metaphors?” 108 HOUSE_OVERSIGHT_016328 “INFORMATION” FOR WIENER, FOR SHANNON, AND FOR US David Kaiser David Kaiser is Germeshausen Professor of the History of Science and professor of Physics at MIT, and head of its Program in Science, Technology & Society. He is the author of Ho
Entities connected to both Turing and Germeshausen

Stephen Hawking
PERSON
Alan Dershowitz
PERSON
Samantha Power
PERSON
George W. Bush
PERSON
Marvin Minsky
PERSON
Earth
LOCATION
Harvey Weinstein
PERSON
Marc Rich
PERSON
Wilbur Ross
PERSON
Seth Lloyd
PERSON
Bill Gates
PERSON
Alan Turing
PERSON
Robert Gates
PERSON
Daniel Dennett
PERSON
Crick
PERSON
John Brockman
PERSON
Elon Musk
PERSON
Prince Andrew
PERSON
Richard Dawkins
PERSON
Martha Stewart
PERSON