Machine Learning Engineering
Cost-benefit analysis is a systematic approach to evaluating the strengths and weaknesses of alternatives in terms of their costs and benefits. This process helps determine the feasibility and effectiveness of decisions, especially when considering algorithmic fairness and debiasing methods, by weighing the potential positive outcomes against the associated costs, such as resources, time, and social implications. In the context of technology and algorithms, it can help stakeholders understand the trade-offs involved in implementing fairness interventions.
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