Can We Learn Anything from Brain Simulation?

Rémy Demichelis
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Abstract

If you figure out how machines learn, then you will figure out how the brain works, and what the brain’s functions are. Such an idea is widespread among philosophers and computer scientists who agree with a functionalist reductionist point of view of consciousness. This theory leads to hold that the more accurate the simulation of cognitive behavior is, the more the math behind it must be true – when true means what really happens in our brain. In this article, we aim to show that, on one hand, brain simulation is nothing more than just another simulation, and it offers very little help to understand – nor to produce – the vivid experiences (qualia) of cognitive functions. On the other hand, we would like to emphasize that when it succeeds at predicting a mechanism with less ambiguity and more accuracy than without a simulation nor direct observation, it really develops the knowledge of our brain. As long as brain simulation follows scientific principles, it should be regarded as valuable, even though the knowledge it brings to science must not be confused for the real phenomenon. Brain simulation, like all simulation, cannot fill any reality or epistemic gap. It is a consolation prize.
我们能从大脑模拟中学到什么吗?
如果你弄清楚机器是如何学习的,那么你就会弄清楚大脑是如何工作的,以及大脑的功能是什么。这种观点在哲学家和计算机科学家中广为流传,他们认同功能主义还原论的意识观点。这一理论认为,对认知行为的模拟越精确,其背后的数学原理就越准确——而真实意味着我们大脑中真实发生的事情。在这篇文章中,我们的目标是表明,一方面,大脑模拟只不过是另一种模拟,它对理解——也不是产生——认知功能的生动体验(感觉)提供的帮助很少。另一方面,我们想强调的是,当它成功地预测了一种机制,比没有模拟或直接观察更少的模糊性和更高的准确性时,它真的发展了我们大脑的知识。只要大脑模拟遵循科学原理,它就应该被认为是有价值的,即使它给科学带来的知识也不能与真实现象相混淆。大脑模拟和所有模拟一样,不能填补任何现实或认知上的空白。这是一个安慰奖。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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