Abstract
This essay highlights some aspects, core themes and controversies regarding causality from a historical-philosophical perspective with special attention to their role in the AI-data science debate. Firstly, it outlines the contours of this debate and subsequently addresses the aporia of causality in statistics, AI and the philosophy and science. In view of the prevalent crisis some key themes and controversies are identified, and a frame of reference is proposed, that may clarify historical controversies and the current state of “agreeing to disagree” in science and philosophy. Secondly, the essay highlights the historical scope of the concept, outlines some early perspectives and “key moments”, that involved main conceptual shifts. Thirdly, the essay outlines the rise of statistics and its role in attempting to defuse the crises by entering a sort of progressing liaison with causality. Finally, it is shown how research in AI has further shaped the concept and how and why causality is about to play a crucial role in the current quest for responsible, explainable and transparent AI and data science.
| Original language | English |
|---|---|
| Pages (from-to) | 4-41 |
| Journal | Journal de la SFdS |
| Volume | 161 |
| Issue number | 1 |
| Publication status | Published - 2020 |
Keywords
- Artificial Intelligence (AI)
- Causality
- Data Science
- Philosophy
- Statistics