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Predictable Artificial Intelligence

9 October 2023
Lexin Zhou
Pablo Antonio Moreno Casares
Fernando Martínez-Plumed
John Burden
Ryan Burnell
Lucy G. Cheke
Cesar Ferri
Alexandru Marcoci
Behzad Mehrbakhsh
Yael Moros-Daval
Seán Ó hÉigeartaigh
Danaja Rutar
Wout Schellaert
Konstantinos Voudouris
José Hernández-Orallo
ArXiv (abs)PDFHTML
Abstract

We introduce the fundamental ideas and challenges of Predictable AI, a nascent research area that explores the ways in which we can anticipate key indicators of present and future AI ecosystems. We argue that achieving predictability is crucial for fostering trust, liability, control, alignment and safety of AI ecosystems, and thus should be prioritised over performance. While distinctive from other areas of technical and non-technical AI research, the questions, hypotheses and challenges relevant to Predictable AI were yet to be clearly described. This paper aims to elucidate them, calls for identifying paths towards AI predictability and outlines the potential impact of this emergent field.

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