Well-roundedness is appropriate in applied STEM curricula to the extent that it rounds out the skills necessary for success as a STEM professional.
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Many Singulatarians hold that their soon-to-be-realized technology will be indistinguishable by the rest of us from magic. Are they serious? Well, in 2005, Kurzweil said that the magical Harry Potter stories “are not unreasonable visions of our world as it will exist only a few decades from now.” when, due to AI, “the entire universe will become saturated with our intelligence.” Keas warns that this type of thing encourages people “to expect the experiential equivalent of occult phenomena.”
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Because Machine Learning is opaque—even experts cannot clearly explain how a system arrived at a conclusion—we treat it as magic. Therefore, we should mistrust the systems until proven innocent (and correct).
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Google is one of the most widely misunderstood success stories of our time. Many of us equate Google with “Big Data,” that is, amassing huge quantities of data and then finding useful statistical patterns. But is that how it succeeded? In Life after Google: The Fall of Big Data and the Rise of the Blockchain Economy, George Gilder criticizes Google primarily on two fronts: First, it is a “walled garden,” a great platform, but inherently isolated and closed. That is a point worth exploring, but not the focus here. The second point, the one I want to touch on, is that Big Data’s day has come and gone. Because Google is a Big Data company, its brightest days are behind it. Read More ›
