The concept of cognitive biases was introduced and popularized by the work of Amos Tversky and Daniel Kahneman since 1972. Biases are seen as systematic errors and flaws that make humans deviate from the standards of rationality, thus making us inept at making good decisions under uncertainty....
The nationally representative study suggested this may be a result of our culture moving away from expressing explicit negative opinions towards marginalized groups — even though unconscious biases may fester. Stereotypes about bisexual people, according to Flanders' and Anderson's research, include that...
aReally it doesn't matter 正在翻译,请等待...[translate] ahuang jinhui,more time for me 正在翻译,请等待...[translate] aNegative biases toward spirituality and religion are serious but 对灵性和宗教生活的负面偏见是严重的但是[translate]
Negative emotion perception biases are associated with a range of psychiatric and behavioral problems, potentially due or as a result of difficult social interactions. Unfortunately, there is a poor understanding of whether observed negative biases are related to childhood trauma ...
overtly racist, sexist, or homophobic acts or comments because they typically don't have any negative intent or hostility behind them. In fact, the person who makes the comment usually isn't consciously aware that their comment is a microaggression because they're unaware of the...
The second, by Joshua Greenberg, takes a more empirical approach to universality identifying traits ( ' , particularly in word order) shared by many language which are considered to represent biases that result from cognitive constraints. 出自-2012年考研翻译原文 The most famous of these efforts was...
In the space of a few months generative AI models, such as ChatGPT, Google's Bard and Midjourney, have been adopted by more and more people in a variety of professional and personal ways. But growing research is underlining that they are encoding biases and negative stereotypes in their use...
However, given the fundamental importance of empirical evidence to drive an informed climate change policy response, we use aggregation and extrapolation based on available knowledge, while acknowledging the limitations and inherent biases that might detract from the accuracy of such an exercise. Implicitl...
PCA is used to infer the ancestry of individuals for various purposes, however a minimal sample size of one, may be even more subjected to biases than in population studies. We found that such biases can occur when individuals with Green (Fig. 23A) and Yellow (Fig. 23B) ancestries cluste...
Even state-of-the-art proprietary LLMs perpetuate historic biases41, cite inappropriate medical articles42 and fail to perform information-driven administrative tasks like medical coding43. Other attacks against LLMs have been developed and analyzed in recent years. During training or fine-tuning, ...