TY - JOUR
T1 - An Eye for Artificial Intelligence
T2 - Insights Into the Governance of Artificial Intelligence and Vision for Future Research
AU - Chhillar, Deepika
AU - Aguilera Vaqués, R.
N1 - Publisher Copyright:
© The Author(s) 2022.
PY - 2022/5
Y1 - 2022/5
N2 - In this 60th anniversary of Business & Society essay, we seek to make three main contributions at the intersection of governance and artificial intelligence (AI). First, we aim to illuminate some of the deeper social, legal, organizational, and democratic challenges of rising AI adoption and resulting algorithmic power by reviewing AI research through a governance lens. Second, we propose an AI governance framework that aims to better assess AI challenges as well as how different governance modalities (architecture, laws, norms, and market) can support AI. At the heart of our framework lies the governance forces that apply to institutions, organizations, and individuals, who ultimately provide, regulate, and use AI decision-making. We discuss how businesses may harness AI’s economic power through governance solutions without creating or amplifying societal biases and inequalities. Third, as part of our section on future research, we identify a set of governance trade-offs in AI adoption, suggest future research avenues to conceptually strengthen research on the governance of AI, and lay out key policy recommendations.
AB - In this 60th anniversary of Business & Society essay, we seek to make three main contributions at the intersection of governance and artificial intelligence (AI). First, we aim to illuminate some of the deeper social, legal, organizational, and democratic challenges of rising AI adoption and resulting algorithmic power by reviewing AI research through a governance lens. Second, we propose an AI governance framework that aims to better assess AI challenges as well as how different governance modalities (architecture, laws, norms, and market) can support AI. At the heart of our framework lies the governance forces that apply to institutions, organizations, and individuals, who ultimately provide, regulate, and use AI decision-making. We discuss how businesses may harness AI’s economic power through governance solutions without creating or amplifying societal biases and inequalities. Third, as part of our section on future research, we identify a set of governance trade-offs in AI adoption, suggest future research avenues to conceptually strengthen research on the governance of AI, and lay out key policy recommendations.
KW - artificial intelligence
KW - big data
KW - governance
KW - institutions
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85131858357&partnerID=8YFLogxK
U2 - 10.1177/00076503221080959
DO - 10.1177/00076503221080959
M3 - Article
AN - SCOPUS:85131858357
SN - 0007-6503
VL - 61
SP - 1197
EP - 1241
JO - Business and Society
JF - Business and Society
IS - 5
ER -