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Algorithmic accountability refers to the issue of where accountability should be apportioned for the consequences of real-world actions that were taken on account of algorithms used to reach a decision.[1]
In principle, an algorithm should be designed in such a way that there is no bias behind the decisions that are made during its execution process. That is, the algorithm should evaluate only essential characteristics of the inputs presented, without making distinctions based on characteristics that usually should not be used in a social environment, such as the ethnicity of an individual who is being judged in a court of law. However, this principle may not always respected and on occasions individuals may be deliberately harmed by these outcomes. It is at this point that the debate arises about who should be held responsible for the losses caused by a decision made by the machine: the system itself or the individual who designed it with such parameters, since a decision that harms other individuals due to lack of impartiality or incorrect data analysis will happen because the algorithm was designed to perform that way.[2]
^Shah, H. (2018). "Algorithmic accountability". Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 376 (2128): 20170362. Bibcode:2018RSPTA.37670362S. doi:10.1098/rsta.2017.0362. PMID 30082307. S2CID 51926550.
^Kobie, Nicole. "Who do you blame when an algorithm gets you fired?". Wired. Retrieved March 2, 2023.
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