Ten Hard Problems in Artificial Intelligence We Must Get Right

Fuente: arXiv
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Autori principali: Leech, Gavin, Garfinkel, Simson, Yagudin, Misha, Briand, Alexander, Zhuravlev, Aleksandr
Natura: Preprint
Pubblicazione: 2024
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author Leech, Gavin
Garfinkel, Simson
Yagudin, Misha
Briand, Alexander
Zhuravlev, Aleksandr
author_facet Leech, Gavin
Garfinkel, Simson
Yagudin, Misha
Briand, Alexander
Zhuravlev, Aleksandr
contents We explore the AI2050 "hard problems" that block the promise of AI and cause AI risks: (1) developing general capabilities of the systems; (2) assuring the performance of AI systems and their training processes; (3) aligning system goals with human goals; (4) enabling great applications of AI in real life; (5) addressing economic disruptions; (6) ensuring the participation of all; (7) at the same time ensuring socially responsible deployment; (8) addressing any geopolitical disruptions that AI causes; (9) promoting sound governance of the technology; and (10) managing the philosophical disruptions for humans living in the age of AI. For each problem, we outline the area, identify significant recent work, and suggest ways forward. [Note: this paper reviews literature through January 2023.]
format Preprint
id arxiv_https___arxiv_org_abs_2402_04464
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Ten Hard Problems in Artificial Intelligence We Must Get Right
Leech, Gavin
Garfinkel, Simson
Yagudin, Misha
Briand, Alexander
Zhuravlev, Aleksandr
Artificial Intelligence
Computers and Society
We explore the AI2050 "hard problems" that block the promise of AI and cause AI risks: (1) developing general capabilities of the systems; (2) assuring the performance of AI systems and their training processes; (3) aligning system goals with human goals; (4) enabling great applications of AI in real life; (5) addressing economic disruptions; (6) ensuring the participation of all; (7) at the same time ensuring socially responsible deployment; (8) addressing any geopolitical disruptions that AI causes; (9) promoting sound governance of the technology; and (10) managing the philosophical disruptions for humans living in the age of AI. For each problem, we outline the area, identify significant recent work, and suggest ways forward. [Note: this paper reviews literature through January 2023.]
title Ten Hard Problems in Artificial Intelligence We Must Get Right
topic Artificial Intelligence
Computers and Society
url https://arxiv.org/abs/2402.04464