A brief history of AI: how to prevent another winter (a critical review)

TL;DR

This paper reviews the history of AI, analyzing past 'winters' and 'summers', to identify lessons and strategies for sustaining progress and avoiding future declines in the field.

Contribution

It offers a critical review of AI's historical cycles and proposes measures to prevent another AI winter based on past experiences.

Findings

AI has experienced two major 'winters' after periods of success.

Understanding historical patterns can help prevent future AI setbacks.

Strategic approaches are suggested to sustain AI development.

Abstract

The field of artificial intelligence (AI), regarded as one of the most enigmatic areas of science, has witnessed exponential growth in the past decade including a remarkably wide array of applications, having already impacted our everyday lives. Advances in computing power and the design of sophisticated AI algorithms have enabled computers to outperform humans in a variety of tasks, especially in the areas of computer vision and speech recognition. Yet, AI's path has never been smooth, having essentially fallen apart twice in its lifetime ('winters' of AI), both after periods of popular success ('summers' of AI). We provide a brief rundown of AI's evolution over the course of decades, highlighting its crucial moments and major turning points from inception to the present. In doing so, we attempt to learn, anticipate the future, and discuss what steps may be taken to prevent another 'winter'.