Error

Category: When Analytics Does Not Work

Analytics can fail because of error, and this raises ethical concerns. "Analytics results are always based on the data available and the outputs and predictions obtained may be imperfect or incorrect. Questions arise about who is responsible for the consequences of an error, which may include ineffective or misdirected educational interventions" (Griffiths, et.al., 2016:4).

The concern about error is large enough that many argue in favour of a corresponding 'Right to Rectification' - that is, "the right of data subjects to amend or modify information held by a data controller if it is incorrect or incomplete." (Fjeld, et.al., 2020: 24) We find it, for example, in article 16 of the European General Data Protection Regulation (EU, 2016). Even so, errors may go undetected in data, they may be detected but ignored by practitioners or they may be detected by people who are denied permission to rectify them. Consequently, ethical questions arise around the need for oversight and error-prevention.

Analytics systems can be based on good data but produce incorrect results. For example, in case where the Metropolitan Police in London deployed facial recognition cameras to detect wanted suspects, it was accurate only 70% of the time, according to the department. "But an independent review of six of these deployments, using different methodology, found that only eight out of 42 matches were 'verifiably correct." Either way (and the veracity of published reports raises ethical concerns of its own) the cameras were frequently wrong. (Shaw, 2020;Fusset and Murray, 2019)

Examples and Articles

29 Common Google Analytics Data Errors And How To Fix Them
"However, even with the most skilled of talent, errors can occur in the data that can throw out results, often unknown to the analytics team.... Hereâ€™s 29 of the most common errors, likely causes and ways you can correct them." Direct Link

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