Risk Management of AI in Industry: a Literature Review

EasyChair Preprint no. 10639

Abstract

The fourth industrial revolution (Industry 4.0) is significantly changing industrial work by introducing interconnected machines and leveraging Artificial Intelligence (AI) to collect and analyze vast amounts of data. This technological advancement has led to increased reliance on AI systems, with some decisions being made automatically. However, the opaque nature of AI presents significant risks, demanding the development of suitable risk management approaches tailored to industrial settings. Currently, there is a lack of comprehensive research in this area, highlighting the need to conduct a structured literature review (SLR) to bridge this gap. Through the SLR, we identified various risk management approaches, including algorithm regulation, governance, certification, and auditing. Building upon these findings, we propose a research agenda for the management of AI risks in industrial settings.

Keyphrases: AI governance, Artificial Intelligence (AI), De-risking AI, Industry 4.0, Regulation of AI

@Booklet{EasyChair:10639,
  author = {Paul Somer and Stefan Thalmann},
  title = {Risk Management of AI in Industry: a Literature Review},
  howpublished = {EasyChair Preprint no. 10639},

  year = {EasyChair, 2023}}