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Algorithmic accountability
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<p>Algorithmic accountability refers to the allocation of responsibility for the consequences of real-world actions influenced by <a href="/facts/Algorithm/fnl5NmRt">algorithms</a> used in decision-making processes. </p><p>Ideally, algorithms should be designed to eliminate bias from their decision-making outcomes. This means they ought to evaluate only relevant characteristics of the input data, avoiding distinctions based on attributes that are generally inappropriate in social contexts, such as an individual's ethnicity in legal judgments. However, adherence to this principle is not always guaranteed, and there are instances where individuals may be adversely affected by algorithmic decisions. Responsibility for any harm resulting from a machine's decision may lie with the algorithm itself or with the individuals who designed it, particularly if the decision resulted from bias or flawed data analysis inherent in the algorithm's design. </p>