The viewpoints by Alan Bundy "Smart Machines Are Not a Threat to Humanity" and Devdatt Dubhashi and Shalom Lappin "AI Dangers: Imagined and Real" (both Feb. 2017) argued against the possibility of a near-term singularity wherein super-intelligent AIs exceed human capabilities and control. Both relied heavily on the lack of direct relevance of Moore's Law, noting raw computing power does not by itself lead to human-like intelligence. Bundy also emphasized the difference between a computer's efficiency in working an algorithm to solve a narrow, well-defined problem and human-like generalized problem-solving ability. Dubhashi and Lappin noted incremental progress in machine learning or better knowledge of a biological brain's wiring do not automatically lead to the "unanticipated spurts" of progress that characterize scientific breakthroughs.
These points are valid, but a more accurate characterization of the situation is that computer science may well be just one conceptual breakthrough away from being able to build an artificial general intelligence. The considerable progress already made in computing power, sensors, robotics, algorithms, and knowledge about biological systems will be brought to bear quickly once the architecture of "human-like" general intelligence is articulated. Will that be tomorrow or in 10 years? No one knows. But unless there is something about the architecture of human intelligence that is ultimately inaccessible to science, that architecture will be discovered. Study of the consequences is not premature.
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