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The necessity of machine learning theory in mitigating AI risk

mishabelkin.substack.com · 2,447 words · saved by 2 readers

Mitigating AI risk has become a topic of intense effort in recent years and months. These well-intentioned efforts grow out of real concern for the uncertain future given the rapid development of AI technologies. In the current form they are unlikely to succeed. The purpose of this document is to make a case that developing a fundamental mathematical theory of deep learning is a prerequisite for managing risk as our society transitions to wide use of AI technology.  Theory in this context refers to identifying precise measurable quantities and mathematically describing their patterns, the way it is used in physics and engineering, rather than proving rigorous theorems. Recent progress in the theory of statistical inference and optimization of neural networks provides hope that such a theory may indeed be possible. Admittedly, even a comprehensive theory of deep learning cannot guarantee a successful AI transition. If we do not have theory, however, we certainly would not be able to con

The necessity of machine learning theory in mitigating AI risk Misha Belkin Jul 29, 2023 31 9 2 Share Mitigating AI risk has become a topic of intense effort in recent years and months. These well-intentioned efforts grow out of real concern for the uncertain future given the rapid development of AI technologies. In the current form they are unlikely to succeed. The purpose of this document is to make a case that developing a fundamental mathematical theory of deep learning is a prerequisite for managing risk as our society transitions to wide use of AI technology. Theory in this context refer

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