Sentence examples for biased decision making from inspiring English sources

But museums should come with labels too, given that their collections, which are often treated as objective and universally approved, are the results of highly biased decision making.

However, heuristics are biased by nature and can lead to biased decision making.

Millions of dollars are being spent shoring up the pipeline to get more minorities ready for working in technology and corporate America; and yet, so much more needs done to address the biased decision making causing these same candidates to be turned away when they apply for jobs.

Box 1 Example of biased decision making leading to diagnostic failure: case 1 A 55-year-old man presents to a walk-in clinic towards the end of the evening.

Box 2 Example of biased decision making leading to diagnostic failure: case 2 A mildly obese, 19-year-old woman is admitted to a psychiatric hospital for stabilisation and investigation.

At least in rats, impulsivity on the 5CSRTT does not seem to be related to D2/D3 receptor function in the dorsal striatum (Dalley et al., 2007); however, D2/D3 receptor availability in this region has been shown to predict irrational, biased decision making in rats (Cocker et al., 2012), a finding of possible relevance to behavioural addictions such as pathological gambling.

The present experiments tested whether positive and negative linguistic descriptions of alleged partners in a modified Ultimatum Game biased decisions made to the same set of offers, and whether the contextual uncertainty of the game modulated this biasing effect.

It has been demonstrated that sadness plays an important role in biasing decision making [ 19, 23, 24], while anhedonia is related to decreased reward sensitivity, which appears to underlie a failure to maximize potential monetary earnings [ 72].

This may bias decision making in social situations away from other-oriented (e.g., empathy for a child in need) to self-oriented (doing what relevant others expect, out of fear for negative reactions) concerns and may hinder empathic concern, leading to lower levels of prosocial behavior (Kanat-Maymon & Assor, 2010; Koenig, Cicchetti, & Rogosh, 2004).

In that way, we are more likely to diversify our workforce, too, which research shows leads to better, less-biased decision making.

This could potentially prevent unnecessary deaths by reducing biased decision-making in the heat of the chase.