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Artificial Intelligence – Extending the Automation Spectrum

In: AI and Analytics for Public Health

Author

Listed:
  • Stephen K. Kwan

    (Lucas College & Graduate School of Business, San José State University)

  • Maria Cristina Pietronudo

    (Parthenope University of Naples)

Abstract

Recent advances in Artificial Intelligence (AI) is enabling automation of tasks that once seemed only humans could perform. This paper examines the effect of Artificial Intelligence on the spectrum of automation spanning automated, assisted/support, augmented, and extending into autonomous decision-making. At one point in time enterprises were able to automate structured decisions and made headway in automating semi-structured decisions. With AI, enterprises are now able to automate unstructured decisions as well. Furthermore, AI is now being used to augment the individual consumer’s routine and non-routine decision-making. In some cases, automation with AI does not even require the activation of capacity. Some researchers, companies, and policymakers are concerned about the replacement of human labour as they hypothesize irreversible negative consequences in terms of job reduction and social divide. A traditional view of automating decision-making is provided to frame recent perspectives of AI in the literature including those that are less pessimistic and a more proactive vision for the future in a variety of decision-making environment.

Suggested Citation

  • Stephen K. Kwan & Maria Cristina Pietronudo, 2022. "Artificial Intelligence – Extending the Automation Spectrum," Springer Proceedings in Business and Economics, in: Hui Yang & Robin Qiu & Weiwei Chen (ed.), AI and Analytics for Public Health, pages 405-417, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-75166-1_30
    DOI: 10.1007/978-3-030-75166-1_30
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