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Enabling Artificial Intelligence Adoption through Assurance

Virginia Polytechnic Institute, State University (Virginia Tech), 900 N. Glebe Road, Arlington, VA 22203, USA
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Academic Editor: Nigel Parton
Soc. Sci. 2021, 10(9), 322; https://doi.org/10.3390/socsci10090322
Received: 29 June 2021 / Revised: 3 August 2021 / Accepted: 19 August 2021 / Published: 25 August 2021
The wide scale adoption of Artificial Intelligence (AI) will require that AI engineers and developers can provide assurances to the user base that an algorithm will perform as intended and without failure. Assurance is the safety valve for reliable, dependable, explainable, and fair intelligent systems. AI assurance provides the necessary tools to enable AI adoption into applications, software, hardware, and complex systems. AI assurance involves quantifying capabilities and associating risks across deployments including: data quality to include inherent biases, algorithm performance, statistical errors, and algorithm trustworthiness and security. Data, algorithmic, and context/domain-specific factors may change over time and impact the ability of AI systems in delivering accurate outcomes. In this paper, we discuss the importance and different angles of AI assurance, and present a general framework that addresses its challenges. View Full-Text
Keywords: AI assurance; data quality; operating envelopes; validation and verification; XAI; AI trustworthiness; data democracy AI assurance; data quality; operating envelopes; validation and verification; XAI; AI trustworthiness; data democracy
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MDPI and ACS Style

Freeman, L.; Rahman, A.; Batarseh, F.A. Enabling Artificial Intelligence Adoption through Assurance. Soc. Sci. 2021, 10, 322. https://doi.org/10.3390/socsci10090322

AMA Style

Freeman L, Rahman A, Batarseh FA. Enabling Artificial Intelligence Adoption through Assurance. Social Sciences. 2021; 10(9):322. https://doi.org/10.3390/socsci10090322

Chicago/Turabian Style

Freeman, Laura, Abdul Rahman, and Feras A. Batarseh 2021. "Enabling Artificial Intelligence Adoption through Assurance" Social Sciences 10, no. 9: 322. https://doi.org/10.3390/socsci10090322

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