An Assessment of the Barriers Impacting Responsible Artificial Intelligence

Mohammad I. Merhi ()
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Mohammad I. Merhi: Indiana University South Bend

Information Systems Frontiers, 2023, vol. 25, issue 3, No 11, 1147-1160

Abstract: Abstract Responsible Artificial Intelligence (AI) has recently gained a lot of attention, especially in the last few years. Scholars have conducted systematic literature reviews to gain more knowledge about responsible AI. However, no study has collected and evaluated the most significant barriers to responsible AI. We filled this gap in the literature by identifying eleven barriers and categorized them, using the Technology-Organization-Environment framework, into three categories. We collected data from seven experts and used the analytical hierarchy process to evaluate the importance of the barriers. The results indicated that technology, as a category, is the most important. The findings also recommended that data quality is the most vital among all eleven barriers. We offered eleven propositions as a theoretical contribution for future researchers in terms of conceptual development. We discussed the implications of the findings for research and practice.

Keywords: Artificial intelligence; Responsible AI; Data quality; Ethics; Analytical hierarchy process (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10796-022-10276-3

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