Artificial Intelligence: 70 Years Down the Road

TL;DR

This paper reviews the nearly century-long history of AI, analyzing development patterns, successes, failures, and proposing future directions emphasizing human-machine collaboration and philosophical insights.

Contribution

It offers a comprehensive historical analysis of AI's development, integrating technical and philosophical perspectives to guide future research and societal impact.

Findings

AI development follows a pattern from rules to statistics to data-driven methods.

Understanding past failures and successes requires systematic and philosophical analysis.

Human-machine collaboration and computing power are key to sustainable AI development.

Abstract

Artificial intelligence (AI) has a history of nearly a century from its inception to the present day. We have summarized the development trends and discovered universal rules, including both success and failure. We have analyzed the reasons from both technical and philosophical perspectives to help understand the reasons behind the past failures and current successes of AI, and to provide a basis for thinking and exploring future development. Specifically, we have found that the development of AI in different fields, including computer vision, natural language processing, and machine learning, follows a pattern from rules to statistics to data-driven methods. In the face of past failures and current successes, we need to think systematically about the reasons behind them. Given the unity of AI between natural and social sciences, it is necessary to incorporate philosophical thinking to understand and solve AI problems, and we believe that starting from the dialectical method of Marx is a feasible path. We have concluded that the sustainable development direction of AI should be human-machine collaboration and a technology path centered on computing power. Finally, we have summarized the impact of AI on society from this trend.