A systematic review of artificial intelligence impact assessments

Artificial intelligence (AI) is producing highly beneficial impacts in many domains, from transport to healthcare, from energy distribution to marketing, but it also raises concerns about undesirable ethical and social consequences. AI impact assessments (AI-IAs) are a way of identifying positive an...

Full description

Saved in:
Bibliographic Details
Published in:The Artificial intelligence review 2023-11, Vol.56 (11), p.12799-12831
Main Authors: Stahl, Bernd Carsten, Antoniou, Josephina, Bhalla, Nitika, Brooks, Laurence, Jansen, Philip, Lindqvist, Blerta, Kirichenko, Alexey, Marchal, Samuel, Rodrigues, Rowena, Santiago, Nicole, Warso, Zuzanna, Wright, David
Format: Article
Language:English
Subjects:
Artificial Intelligence
Assessments
Computer Science
Deforestation
Energy distribution
Ethical standards
Organizational aspects
Qualitative analysis
Systematic review
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Artificial intelligence (AI) is producing highly beneficial impacts in many domains, from transport to healthcare, from energy distribution to marketing, but it also raises concerns about undesirable ethical and social consequences. AI impact assessments (AI-IAs) are a way of identifying positive and negative impacts early on to safeguard AI’s benefits and avoid its downsides. This article describes the first systematic review of these AI-IAs. Working with a population of 181 documents, the authors identified 38 actual AI-IAs and subjected them to a rigorous qualitative analysis with regard to their purpose, scope, organisational context, expected issues, timeframe, process and methods, transparency and challenges. The review demonstrates some convergence between AI-IAs. It also shows that the field is not yet at the point of full agreement on content, structure and implementation. The article suggests that AI-IAs are best understood as means to stimulate reflection and discussion concerning the social and ethical consequences of AI ecosystems. Based on the analysis of existing AI-IAs, the authors describe a baseline process of implementing AI-IAs that can be implemented by AI developers and vendors and that can be used as a critical yardstick by regulators and external observers to evaluate organisations’ approaches to AI.
ISSN:0269-2821
1573-7462
DOI:10.1007/s10462-023-10420-8