Machine Translation: Early Criticisms Revisited

Hubert Dreyfus questioned the foundational ideas of early artificial intelligence research. Challenging the prevailing orthodoxy, he posited that the failure to manifest advancements in areas like language translation and problem-solving stems from a foundational misalignment with the intricacies of human “information processing”. This paper restates Dreyfus’ challenge. Based on case studies it argues that contemporary neural network systems have taken up the challenge by implicitly addressing three distinct philosophical problems, posed by Ludwig Wittgenstein, George Pólya, and Edmund Husserl.