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原文連結
論文資訊
- 類型：已發表論文
- 日期：2021
摘要
Since its beginning in the 1950s, the field of 人工智慧 has cycled several times between periods of optimistic predictions and massive investment (“AI spring”) and periods of disappointment, loss of confi- dence, and reduced funding (“AI winter”). Even with today’s seemingly fast pace of AI breakthroughs, the development of long-promised technologies such as self-driving cars, housekeeping robots, and conversational companions has turned out to be much harder than many people expected. One reason for these repeating cycles is our limited understanding of the nature and complexity of intelligence itself. In this paper I describe four fallacies in common assumptions made by AI researchers, which can lead to overconfident predictions about the field. I conclude by discussing the open questions sp
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