Bias

Bias is a disproportionate weight in favor of or against an idea or thing, usually in a way that is closed-minded, prejudicial, or unfair. Biases can be innate or learned. People may develop biases for or against an individual, a group, or a belief. In science and engineering, a bias is a systematic error. Statistical bias results from an unfair sampling of a population, or from an estimation process that does not give accurate results on average. The word appears to derive from Old Provençal into Old French biais, "sideways, askance, against the grain". Whence comes French biais, "a slant, a slope, an oblique". It seems to have entered English via the game of bowls, where it referred to balls made with a greater weight on one side. Which expanded to the figurative use, "a one-sided tendency of the mind", and, at first especially in law, "undue propensity or prejudice". Cognitive bias and List of cognitive biases A cognitive bias is a repeating or basic misstep in thinking, assessing, recollecting, or other cognitive processes. That is, a pattern of deviation from standards in judgment, whereby inferences may be created unreasonably. People create their own "subjective social reality" from their own perceptions, their view of the world may dictate their behaviour. Thus, cognitive biases may sometimes lead to perceptual distortion, inaccurate judgment, illogical interpretation, or what is broadly called irrationality. However some cognitive biases are taken to be adaptive, and thus may lead to success in the appropriate situation. Furthermore, cognitive biases may allow speedier choices when speed is more valuable than precision. Other cognitive biases are a "by-product" of human processing limitations, coming about because of an absence of appropriate mental mechanisms, or just from human limitations in information processing. Anchoring Anchoring is a psychological heuristic that describes the propensity to rely on the first piece of information encountered when making decisions.

Exploiting the Signal-Leak Bias in Diffusion Models

It’s All Relative: Learning Interpretable Models for Scoring Subjective Bias in Documents from Pairwise Comparisons

Biases in Information Selection and Processing: Survey Evidence from the Pandemic

It’s All Relative: Learning Interpretable Models for Scoring Subjective Bias in Documents from Pairwise Comparisons

Biases in Information Selection and Processing: Survey Evidence from the Pandemic

Exploiting the Signal-Leak Bias in Diffusion Models