人工智能还给人类的思维难题

Artificial Intelligence and the Challenges to Human Thought

当下人工智能的思维采用贝叶斯方法论,因此重新提出了经验论的问题。先验论对休谟因果问题的解决并不成功,贝叶斯方法另外给出了对休谟问题的经验论解决。休谟问题的核心是不确定的“未来”,人工智能将抽象的未来简化为可操作的“预测下一个标识”,在没有借助先验方法的条件下,成功地以贝叶斯方法去保证预测的有效性和可信度。这迫使我们去反思人类思维本身,重新思考经验论与先验论的经典难题。可以期待,如果发展一种属于经验论的动词逻辑,或可解释更多的思维秘密,也或可为人工智能增加一个分析和预测的维度。

Contemporary artificial intelligence(AI)employs Bayesian methodology,thereby reintroducing the problem of empiricism.While transcendental theory was unsuccessful in resolving Hume's problem of causation,Bayesian Analysis offers an empirical solution.At the heart of Hume's problem lies the uncertainty of the"future."AI simplifies and reduces the abstract future into an operable"prediction of the next identifier,"eensuring the validity and credibility of predictions using Bayesian Analysis without relying on a priori methods.This compels us to reflect on human thought itself and reconsider the classic dilemmas of empiricism and transcendentalism.It is anticipated that developing a verb logic based on empiricism could potentially explain more cognitive secrets and add an analytical and predictive dimension to AI.