Abstract: Although the so-called“Heddeggerian Philosophy of Artificial Intelligence,”thanks to the hard work of Hubert Dreyfus and John Haugeland,has been identified as a stable branch of philosophy of AI in the west,the resources of Hegelian philosophy does not play such a salient role in shaping any identifiable branch in Philosophy of AI,despite the affinity between two philosophers’ writing styles.The core problem in AI which is requiring a Hegelian diagnosis is the so-called “frame problem,”namely,the problem on how to design an artificial agent which can maximize its benefits by automatically avoiding“considering”issues irrelevant to the task which is being handled.From the perspective of philosophy of language and philosophy of logic,this problem is tantamount to a problem on how to catch semantic relevance on a computable platform,and this problem looks so challenging to truth-function semantics-based AI,since semantics of this type is not apt enough to handle“relevance /irrelevance.”As to Hegel’s Logic,it is relevant to the frame problem in that the list of categories discussed by him can be viewed as a toolbox of different conceptual devices for handling semantic relevance on different levels. To be more specific,if the first part of his Logic,namely,“the doctrine of being,”is considered as the exemplar part of Logic for showing the possibility of developing a“Hegelian Philosophy of AI,”then there are at least three morals that one can draw for AI from Hegel’s relevant discussions: ( a) early analytical thinkers’ proposal for splitting“being”into different predicates does not deserve a serious consideration,in that this move would bring about a further problem on how to exhaustively list all of the primary predicates in programing; ( b) the fundamental status that Hegel attributes to the category“becoming”can be viewed as a criticism of the insensitivity to contextual changes in the axiomatic symbolic approach,as well as a criticism of the systematic reduction of cross-contextual inferences in terms of mapping procedures from data of a certain domain to outputs in the same domain in the approach of artificial neural networks or deep learning; (c) the dialectical inference from“being”to“nothing”and to“becoming”is actually not indicating a new logic which is different from formal logic.Rather,it is a flowchart on the same level of the“goal-means”approach in Herbert Simon and Allen Newell’s General Problem Solver Project,or in another way,it is a generalization of the procedures for probing the truth in the world. Hence,it is pointless to formalize the dialectical logic alone if it is detached from potential problem solving contexts. Generally speaking,my research project for correlating Hegel with AI is not only beneficial to AI but also to the study of Hegel. Or put it differently,my strategy of reading Hegel’s notion of“logic”mainly in terms of a cognitive logic can make the disenchantment of the philosophical image of Hegel himself more easily,since my strategy can easily elude all of the metaphysical mysteries traditionally associated with his Logic.Moreover,the introduction of the AI-based perspective into the study of Hegel can also make it possible to demystify Hegelian speculations in terms of computer science.
Key words: Hegel; Artificial Intelligence ( AI) ; category; logic; frame problem; semantic relevance
The Chinese version appeared in Fudan Journal, 2018(06).