he Wall Street Journal (11/12/15) Pedro Domingos
Within 10 years, people will entrust their data to machine-learning algorithms that build personal digital models of them, writes University of Washington professor Pedro Domingos. He predicts a new kind of company will be conceived to store, safeguard, and apply such data to the construction, maintenance, and interactions of these models. Domingos says it would record a customer's every digital interaction and feed it to the model in exchange for a subscription fee. He notes all this would require on the technical side is a proxy server through which these interactions are routed and recorded. "Once a firm has your data in one place, it can create a complete model of you using one of the major machine-learning techniques: inducing rules, mimicking the way neurons in the brain learn, simulating evolution, probabilistically weighing the evidence for different hypotheses, or reasoning by analogy," Domingos says. He thinks these models could be duplicated almost infinitely to multitask, selecting the best options for the user based on accumulated behavior and preferences. "To offset organizations' data-gathering advantages, like-minded individuals will pool the data in their banks and use the models learned from that information," Domingos says. He predicts cyberspace will evolve into "a vast parallel world that selects only the most promising things to try out in the real one--the new, global subconscious of the human race."
Within 10 years, people will entrust their data to machine-learning algorithms that build personal digital models of them, writes University of Washington professor Pedro Domingos. He predicts a new kind of company will be conceived to store, safeguard, and apply such data to the construction, maintenance, and interactions of these models. Domingos says it would record a customer's every digital interaction and feed it to the model in exchange for a subscription fee. He notes all this would require on the technical side is a proxy server through which these interactions are routed and recorded. "Once a firm has your data in one place, it can create a complete model of you using one of the major machine-learning techniques: inducing rules, mimicking the way neurons in the brain learn, simulating evolution, probabilistically weighing the evidence for different hypotheses, or reasoning by analogy," Domingos says. He thinks these models could be duplicated almost infinitely to multitask, selecting the best options for the user based on accumulated behavior and preferences. "To offset organizations' data-gathering advantages, like-minded individuals will pool the data in their banks and use the models learned from that information," Domingos says. He predicts cyberspace will evolve into "a vast parallel world that selects only the most promising things to try out in the real one--the new, global subconscious of the human race."
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