High-impact AI: How to achieve business goals while making the world a better place
Michael Griffin,
Hailey Kotvis,
Josephine Miner and
Kayla Poulsen
Additional contact information
Michael Griffin: Chief Data Scientist, Insight, USA
Hailey Kotvis: Associate Software Engineer, Insight, USA
Josephine Miner: Data and Artificial Intelligence Intern, Insight, USA
Kayla Poulsen: Data and Artificial Intelligence Intern, Insight, USA
Journal of AI, Robotics & Workplace Automation, 2022, vol. 2, issue 1, 37-48
Abstract:
A vast amount of wealth has been generated by the explosive growth of artificial intelligence (AI)-enabled applications, and that wealth generation is accelerating. This paper describes how both monetary and non-monetary wealth — the kind of wealth that makes the world a better place — can be generated by the same intelligent application. The paper introduces the term ‘high-impact AI’, which is the practice of achieving business goals while simultaneously benefiting society. Novel and practical examples of achieving this lofty goal are described in the areas of manufacturing, where AI-powered software enables people with disabilities to perform jobs they would otherwise not be qualified to perform; healthcare, where the incredible complexity of practising medicine has been simplified to potentially improve the health and prolong the lives of millions of people; and psychology, where a tremendous variety of human interactions can be quantified and optimised in real time to assist strengthening and enhancing relationships of all kinds. Finally, this paper makes the case that practising high-impact AI will help businesses attract and retain talented people by giving them meaningful work that matters.
Keywords: ethical artificial intelligence (AI); assisted communication; manufacturing; healthcare; psychology; enhanced order fulfilment; automated inventorying (search for similar items in EconPapers)
JEL-codes: G2 M15 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:aza:airwa0:y:2022:v:2:i:1:p:37-48
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