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  1. Our responsibility to manage evaluative diversity.Christopher Santos-Lang - 2014 - Acm Sigcas Computers and Society 44 (2):16-19.
    The ecosystem approach to computer system development is similar to management of biodiversity. Instead of modeling machines after a successful individual, it models machines after successful teams. It includes measuring the evaluative diversity of human teams (i.e. the disparity in ways members conduct the evaluative aspect of decision-making), adding similarly diverse machines to those teams, and monitoring the impact on evaluative balance. This article reviews new research relevant to this approach, especially the validation of a survey instrument for measuring computational (...)
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  • Ethical artificial intelligence framework for a good AI society: principles, opportunities and perils.Pradeep Paraman & Sanmugam Anamalah - 2023 - AI and Society 38 (2):595-611.
    The justification and rationality of this paper is to present some fundamental principles, theories, and concepts that we believe moulds the nucleus of a good artificial intelligence (AI) society. The morally accepted significance and utilitarian concerns that stems from the inception and realisation of an AI’s structural foundation are displayed in this study. This paper scrutinises the structural foundation, fundamentals, and cardinal righteous remonstrations, as well as the gaps in mechanisms towards novel prospects and perils in determining resilient fundamentals, accountability, (...)
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