The authors explore how diversity in data sets contributes to bias in artificial intelligence.
Read More...Addressing and Resolving Biases in Artificial Intelligence
The authors explore how diversity in data sets contributes to bias in artificial intelligence.
Read More...Genetic underpinnings of the sex bias in autism spectrum disorder
Here, seeking to identify a possible explanation for the more frequent diagnosis of autism spectrum disorder (ASD) in males than females, they sought to investigate a potential sex bias in the expression of ASD-associated genes. Based on their analysis, they identified 17 ASD-associated candidate genes that showed stronger collective sex-dependent expression.
Read More...Propagation of representation bias in machine learning
Using facial recognition as a use-case scenario, we attempt to identify sources of bias in a model developed using transfer learning. To achieve this task, we developed a model based on a pre-trained facial recognition model, and scrutinized the accuracy of the model’s image classification against factors such as age, gender, and race to observe whether or not the model performed better on some demographic groups than others. By identifying the bias and finding potential sources of bias, his work contributes a unique technical perspective from the view of a small scale developer to emerging discussions of accountability and transparency in AI.
Read More...Determining the Effects of Voice Pitch on Adolescent Perception, Subconscious Bias, and Marketing Success Using Electroencephalography
Voice pitch affects perceived authoritativeness, competency, and leadership capacity. In this study, the authors suggest that examining certain measures of brain activity collected using an affordable EEG could predict advertising effectiveness, which may be invaluable in future neuromarketing research. Understanding voice pitch and other factors that cause implicit bias may allow significant advances in marketing, facilitating business success.
Read More...Do Attractants Bias the Results of Malaise Trap Research?
Malaise traps are commonly used to collect flying insects for a variety of research. In this study, researchers hypothesized the attractants used in these traps may create bias in insect studies that could lead to misinterpreted data. To test this hypothesis two different kinds of attractant were used in malaise traps, and insect diversity was assessed. Attractants were found to alter the dispersion of insects caught in traps. These findings can inform future malaise traps studies on insect diversity.
Read More...Battling cultural bias within hate speech detection: An experimental correlation analysis
The authors develop a new method for training machine learning algorithms to differentiate between hate speech and cultural speech in online platforms.
Read More...The Effect of Statement Biased Popular Media Consumption on Public Perceptions of Nuclear Power
The authors investigate the effects of popular media consumption on the public's opinion on nuclear power. They find that regardless of education level or positive/negative bias of the article, participants are willing to modify their opinions on nuclear power after consuming a single article.
Read More...Racial and gender disparities in the portrayal of lawyers and physicians on television
Powered by the sociological framework that exposure to television bleeds into social biases, limiting media representation of women and minority groups may lead to real-world implications and manifestations of racial and gender disparities. To address this phenomenon, the researchers in this article take a look at primetime fictional representation of minorities and women as lawyers and physicians and compare television representation to census data of the same groups within real-world legal and medical occupations. The authors maintain the hypothesis that representation of female and minority groups as television lawyers and doctors is lower than that of their white male counterparts relative to population demographics - a trend that they expect to also be reflected in actual practice. With fictional racial and gender inequalities and corresponding real-world trends highlighted within this article, the researchers call for address towards representation biases that reinforce each other in both fictional and non-fictional spheres.
Read More...The Role of Corresponding Race, Gender, and Species as Incentives for Charitable Giving
Inherent bias is often the unconscious driver of human behavior, and the first step towards overcoming these biases is our awareness of them. In this article the authors investigate whether race, gender or species affect the choice of charity by middle class Spaniards. Their conclusions serve as a starting point for further studies that could help charities refine their campaigns in light of these biases effectively transcending them or taking advantage of them to improve their fundraising attempts.
Read More...A Data-Centric Analysis of “Stop and Frisk” in New York City
The death of George Floyd has shed light on the disproportionate level of policing affecting non-Whites in the United States of America. To explore whether non-Whites were disproportionately targetted by New York City's "Stop and Frisk" policy, the authors analyze publicly available data on the practice between 2003-2019. Their results suggest African Americans were indeed more likely to be stopped by the police until 2012, after which there was some improvement.
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