the long run, there 1s no distinction between arming ourselves and arming our enemies.” (p. 129) The Information Age is also the Dysinformation Age. What can we do? We need to rethink our priorities with the help of the passionate but flawed analyses of Wiener, Weizenbaum, and the other serious critics of our technophilia. A key phrase, it seems to me, is Wiener’s almost offhand observation, above, that “these machines” are “helpless by themselves.” As I have been arguing recently, we’re making tools, not colleagues, and the great danger is not appreciating the difference, which we should strive to accentuate, marking and defending it with political and legal innovations. Perhaps the best way to see what is being missed 1s to note that Alan Turing himself suffered an entirely understandable failure of imagination in his formulation of the famous Turing Test. As everyone knows, it is an adaptation of his “imitation game,” in which a man, hidden from view and communicating verbally with a judge, tries to convince the judge that he is in fact a woman, while a woman, also hidden and communicating with the judge, tries to convince the judge that she is the woman. Turing reasoned that this would be a demanding challenge for a man (or for a woman pretending to be a man), exploiting a wealth of knowledge about how the other sex thinks and acts, what 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 imagined an astute and imaginative (and hence conscious) agent who cunningly designed his responses based on his detailed “theory” of what women are likely to do and say. Top-down intelligent design, in short. He certainly didn’t think that a man, winning the imitation game, would somehow become a woman; he imagined that there w