Artificial Intelligence is now recognized as a general-purpose technology
with ample impact on human life. In this work, we aim to understand the
evolution of AI and Machine learning over the years by analyzing researchers'
impact, influence, and leadership over the last decades. This work also intends
to shed new light on the history and evolution of AI by exploring the dynamics
involved in the field's evolution through the lenses of the papers published on
AI conferences since the first International Joint Conference on Artificial
Intelligence (IJCAI) in 1969. AI development and evolution have led to
increasing research output, reflected in the number of articles published over
the last sixty years. We construct comprehensive citation-collaboration and
paper-author datasets and compute corresponding centrality measures to carry
out our analyses. These analyses allow a better understanding of how AI has
reached its current state of affairs in research. Throughout the process, we
correlate these datasets with the work of the ACM Turing Award winners and the
so-called two AI winters the field has gone through. We also look at
self-citation trends and new authors' behaviors. Finally, we present a novel
way to infer the country of affiliation of a paper from its organization.
Therefore, this work provides a deep analysis of Artificial Intelligence
history from information gathered and analyzed from large technical venues
datasets and suggests novel insights that can contribute to understanding and
measuring AI's evolution.

通过分析人工智能会议上发表的论文，我们深入了解了人工智能和机器学习的演变过程，以及研究人员的影响和领导力，得出了一些对于理解和衡量人工智能演化的新见解。