Review of the governance, risk and compliance approaches for artificial intelligence

• Main Authors: Lau, David Keat Jin, Narayana Samy, Ganthan, Abdul Rahim, Fiza, Selvananthan, Mahiswaran, Maarop, Nurazean, Hassan, Noor Hafizah
• Format: Article
• Language: English
• Published: Penerbit UTM Press 2023
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/108682/1/LauKeatJin2023_ReviewoftheGovernanceRiskandCompliance.pdf; http://eprints.utm.my/108682/; http://dx.doi.org/10.11113/oiji2023.11n2.266

Advancement in the domain of big data, computing power and internet of things continue to spur the development of algorithmic models that morphed into artificial intelligence. Notable achievements have been made in the application of artificial intelligence in image recognition, natural language processing, smart farming, personal learning assistance, and autonomous systems. As its adoption increases and proliferates into every sphere of activities, governments, businesses and organizations begin to formulate strategies and measures to facilitate its adoption even as it is still rapidly progressing. Meanwhile, artificial intelligence’s impact to the individual, organizational and societal levels as well as the mechanisms to ensure realization of its benefits and minimization of its drawbacks are actively being pursued by the academic communities. This study endeavours to aggregate the perspectives from multiple review studies to shed light on the approaches pertaining to the governance, risk management and compliance of artificial intelligence. The concepts, elements and practices relevant to the three aspects are presented together with the proposed way forward to facilitate artificial intelligence adoption by the organizations.