Operationalising Responsible AI: From Principles to Engineering Practice
Suman Paria
Dozens of organisations have published Responsible AI (RAI) principle frameworks over the past decade, yet practitioners consistently report that these principles offer little concrete guidance for day-to-day engineering decisions. This short communication reviews recent work on AI governance frameworks, engineering-level pattern catalogues, developer-reported barriers to fairness, and formal accounts of how bias enters systems, and argues that responsible AI must be embedded as an ordinary part of the software development lifecycle rather than treated as a separate ethics or compliance exercise.
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