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Towards A Calibrated Trust-Based Approach To The Use Of Facial Recognition Technology, Gary Kok Yew Chan
Towards A Calibrated Trust-Based Approach To The Use Of Facial Recognition Technology, Gary Kok Yew Chan
Research Collection Yong Pung How School Of Law
The use of facial recognition technology has given rise to much debate relating to issues concerning privacy infringements, bias and inaccuracies of data and outputs, possibilities of covert use, the lack of data security and the problem of function creep. Certain states and jurisdictions have called for bans and moratoria on the use of facial recognition technology. This paper argues that a blanket ban on facial recognition technology would be overly precautionary without fully considering the wide range of uses and benefits of the innovation. To promote its acceptance, trust in facial recognition technology should be developed in a calibrated …
Biographical Data And Black Box Empiricism: Lessons Learned For Algorithmic Assessments In Personnel Selection, Ketaki Sodhi, Marc Cubrich
Biographical Data And Black Box Empiricism: Lessons Learned For Algorithmic Assessments In Personnel Selection, Ketaki Sodhi, Marc Cubrich
Psychology from the Margins
As the popularity of biodata in selection assessments grew in the 1980s and into the 1990s, the field of industrial and organizational psychology witnessed many attempts to develop biodata theories and guide the development of biodata items. The insights that emerged from this body of research are increasingly relevant in the current era of big data, artificial intelligence (AI), and machine learning. More than ever, AI and machine learning are being used to score candidates and make hiring recommendations. Many organizations are using data-driven approaches to develop machine learning and AI algorithms, which are frequently atheoretical, based on correlations or …
Powered By Ai, Christopher J. Smiley
Powered By Ai, Christopher J. Smiley
The Journal of the Michigan Dental Association
Artificial Intelligence (AI) is revolutionizing dental practice through its ability to process vast amounts of data, enhance diagnosis, and improve patient care. However, AI introduces the challenge of bias and ethical considerations. Dentists and dental benefit providers are utilizing AI for early disease detection and efficient data management, but transparency and fairness in AI algorithms are vital. The Rome Call for AI Ethics emphasizes ethical, non-biased AI development. In the broader context, AI-driven marketing and predictive behavior raise concerns about privacy and ethical data use. The dental community must embrace AI's power while upholding ethical standards and transparency.