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Bias can emerge from many factors, including but not limited to the design of the algorithm or the unintended or unanticipated use or decisions relating to the way data is coded, collected, selected or used to train the algorithm. [2] For example, algorithmic bias has been observed in search engine results and social media platforms.
Systemic bias is the inherent tendency of a process to support particular outcomes. The term generally refers to human systems such as institutions. Systemic bias is related to and overlaps conceptually with institutional bias and structural bias, and the terms are often used interchangeably.
Bias should be accounted for at every step of the data collection process, beginning with clearly defined research parameters and consideration of the team who will be conducting the research. [2] Observer bias may be reduced by implementing a blind or double-blind technique. Avoidance of p-hacking is essential to the process of accurate data ...
Publication bias is a type of bias with regard to what academic research is likely to be published because of a tendency among researchers and journal editors to prefer some outcomes rather than others (e.g., results showing a significant finding), which leads to a problematic bias in the published literature. [139]
One topic of research and discussion is the definition of fairness, as there is no universal definition, and different definitions can be in contradiction with each other, which makes it difficult to judge machine learning models. [3] Other research topics include the origins of bias, the types of bias, and methods to reduce bias. [4]
The definition can be further expanded upon to include the systematic difference between what is observed due to variation in observers, and what the true value is. [ 2 ] Observer bias is the tendency of observers to not see what is there, but instead to see what they expect or want to see.
The process of data dredging involves testing multiple hypotheses using a single data set by exhaustively searching—perhaps for combinations of variables that might show a correlation, and perhaps for groups of cases or observations that show differences in their mean or in their breakdown by some other variable.
Systematic reviews aim to bridge the research-policy divide by assessing the range of existing evidence on a particular topic, and presenting the information in an accessible format. Like rigorous impact evaluations, they are developed from a study Protocol which sets out a priori the criteria for study inclusion, search and methods of synthesis.