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Try to encourage a kid to learn math by paying her for each workbook page she completes—and she’ll almost certainly become more diligent in the short term and lose interest in math in the long term. Take an industrial designer who loves his work and try to get him to do better by making his pay contingent on a hit product—and he’ll almost certainly work like a maniac in the short term, but become less interested in his job in the long term. As one leading behavioral science textbook puts it, “People use rewards expecting to gain the benefit of increasing another person’s motivation and behavior, but in so doing, they often incur the unintentional and hidden cost of undermining that person’s intrinsic motivation toward the activity.”
experts cannot guarantee outcomes. They cannot promise that they will never make mistakes or that they will not fall prey to the same shortcomings that govern all human deliberations. They can only promise to institute rules and methods that reduce the chance of such mistakes and to make those errors far less often than a layperson might. If we are to accept the benefits of a profession’s work, we have to accept something less than perfection, perhaps even a certain amount of risk.
The Death of Expertise
Tom Nichols
Technology has played a central role in revolutionizing many industries and realms of human life. How we work, play, communicate, and travel have been fully transformed by technology in the past one hundred years. And yet, apart from the temporary use of remote learning during the COVID-19 pandemic, a classroom today still resembles a classroom one hundred years ago. We know the flaws of today’s education—it is one-size-fits-all yet we know each student is different, and it is expensive and cannot be scaled to poorer countries and regions with a reasonable student-to-teacher ratio. AI can play a major part in fixing these flaws and transform education.
Ai 2041
Kai-Fu Lee and Chen Qiufan
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