Epstein Secrets

abbage — but he was the first to fully understand its power. When we talk about computers today we mean machines, but it is worth noting computers in Turing’s time were more often humans using pencil and paper. The mechanical computers before Turing were elementary at best. Rudimentary calculating machi

not Turing complete and his Analytical Engine has never been built. 19" Century Calculators HOUSE_OVERSIGHT_015706 Mind over Computer 17 In 1935, Turing was made a Fellow of King’s College, Cambridge, and became interested in whether mathematical proofs could be found automatically. He wanted to know

d on interview, rather than practical tests. Could a computer hold a conversation with me and persuade me it is intelligent? Meet Eliza. Invented by Joseph Weizenbaum of the Massachusetts Institute of Technology, and named after George Bernard Shaw’s character in Pygmalion, Eliza runs an algorithm pretending to be

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

owing it to detect dissent and subversion as it arises and make resistance to state power futile. Orwell’s telescreens are the prototype, and in 1976 Joseph Weizenbaum, one of the gloomiest tech prophets of all time, warned my class of graduate students not to pursue automatic speech recognition because government s

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; the Fair Access to Science and Technology Research Act (FASTR); and the Open Humans Foundation. In his 1976 book Computer Power and Human Reason, Joseph Weizenbaum argued that machines should not replace Homo in situations requiring respect, dignity, or care, while others (author Pamela McCorduck and computer sc

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

owing it to detect dissent and subversion as it arises and make resistance to state power futile. Orwell’s telescreens are the prototype, and in 1976 Joseph Weizenbaum, one of the gloomiest tech prophets of all time, warned my class of graduate students not to pursue automatic speech recognition because government s

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; the Fair Access to Science and Technology Research Act (FASTR); and the Open Humans Foundation. In his 1976 book Computer Power and Human Reason, Joseph Weizenbaum argued that machines should not replace Homo in situations requiring respect, dignity, or care, while others (author Pamela McCorduck and computer sc

ere? A dim, honest, slow-multiplying human? Impossible to tell. The distinction between machine and man blurred a bit. Buried in the very premise of Turing’s test was an assumption about what machines could do, and how they might do it. “The idea behind digital computers may be explained by saying that t

government (or our enemies) behave. We are, ina sense, being engineered by the damn opaque systems we are using. In 1965 the MIT computer scientist Joseph Weizenbaum found himself, somewhat unexpectedly, considering this same problem. 175 Weizenbaum had written a primitive computer program to perform what is now k