ADOPTION OF DISCRIMINATORY BEHAVIOR TOWARDS WOMEN WITH DIFFERENT ETHNO-RELIGIOUS APPEARANCE

Author(s):  
Daria Pogontseva
2021 ◽  
Vol 54 (6) ◽  
pp. 1-35
Author(s):  
Ninareh Mehrabi ◽  
Fred Morstatter ◽  
Nripsuta Saxena ◽  
Kristina Lerman ◽  
Aram Galstyan

With the widespread use of artificial intelligence (AI) systems and applications in our everyday lives, accounting for fairness has gained significant importance in designing and engineering of such systems. AI systems can be used in many sensitive environments to make important and life-changing decisions; thus, it is crucial to ensure that these decisions do not reflect discriminatory behavior toward certain groups or populations. More recently some work has been developed in traditional machine learning and deep learning that address such challenges in different subdomains. With the commercialization of these systems, researchers are becoming more aware of the biases that these applications can contain and are attempting to address them. In this survey, we investigated different real-world applications that have shown biases in various ways, and we listed different sources of biases that can affect AI applications. We then created a taxonomy for fairness definitions that machine learning researchers have defined to avoid the existing bias in AI systems. In addition to that, we examined different domains and subdomains in AI showing what researchers have observed with regard to unfair outcomes in the state-of-the-art methods and ways they have tried to address them. There are still many future directions and solutions that can be taken to mitigate the problem of bias in AI systems. We are hoping that this survey will motivate researchers to tackle these issues in the near future by observing existing work in their respective fields.


2021 ◽  
Vol 22 (2) ◽  
pp. 85-110
Author(s):  
Yuval Feldman ◽  
Yotam Kaplan

Abstract Law and economics scholarship suggests that, in appropriate cases, the law can improve people’s behavior by changing their preferences. For example, the law can curb discriminatory hiring practices by providing employers with information that might change their discriminatory preference. Supposedly, if employers no longer prefer one class of employees to another, they will simply stop discriminating, with no need for further legal intervention. The current Article aims to add some depth to this familiar analysis by introducing the insights of behavioral ethics into the law and economics literature on preference change. Behavioral ethics research shows that wrongdoing often originates from semi-deliberative or non-deliberative cognitive processes. These findings suggest that the process of preference change through the use of the law is markedly more complicated and nuanced than previously appreciated. For instance, even if an employer’s explicit discriminatory stance is changed, and the employer no longer consciously prefers one class of employees over another, discriminatory behavior might persist if it originates from semi-conscious, habitual, or non-deliberative decision-making mechanisms. Therefore, actual change in behavior might necessitate a close engagement with people’s level of moral awareness. We discuss the institutional and normative implications of these insights and evaluate their significance for the attempt to improve preferences through the different functions of the legal system.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Markus Brauer ◽  
Anissa Dumesnil ◽  
Mitchell Robert Campbell

Purpose Despite more than half a century of academic research, relatively few methods have been shown to reliably improve intergroup relations in the real world. This paper aims to use a social marketing approach to design a pro-diversity intervention in a university setting. Design/methodology/approach We conducted extensive qualitative, quantitative and observational background research to identify elements that would increase the effectiveness of the intervention. Focus groups and surveys allowed us to identify a target audience, target behaviors and the relevant barriers and benefits. Findings The background research suggested increasing inclusive behavior would have a greater impact than reducing discriminatory behavior. Based on this research, this paper determined an optimal target audience was students who had relatively positive attitudes toward diversity but engaged in few inclusive behaviors. This paper used relevant theories from the behavioral sciences to design an intervention that promoted a small set of inclusive behaviors and that addressed the relevant barriers and benefits. The intervention took the form of a single page of targeted messages that instructors can add to their course syllabi. The page communicates injunctive and descriptive norms, highlights the benefits of behaving inclusively and provides concrete behavioral advice. Originality/value The research applies the social marketing approach to a novel domain. This approach represents a new way to advance diversity, equity and inclusion through promoting inclusive and reducing discriminatory behavior.


2018 ◽  
Vol 14 (3) ◽  
pp. 193-205
Author(s):  
Rickard Carlsson ◽  
Jens Agerström ◽  
Donald Williams ◽  
Gary N. Burns

2018 ◽  
Author(s):  
S. Michael Gaddis

An audit study is a specific type of field experiment primarily used to test for discriminatory behavior when survey and interview questions induce social desirability bias. In this chapter, I first review the language and definitions related to audit studies and encourage adoption of a common language. I then discuss why researchers use the audit method as well as when researchers can and should use this method. Next, I give an overview of the history of audit studies, focusing on major developments and changes in the overall body of work. Finally, I discuss the limitations of correspondence audits and provide some thoughts on future directions.


1978 ◽  
Vol 21 (4) ◽  
pp. 742-748 ◽  
Author(s):  
S. L. Cohen ◽  
S. Leavengood

2020 ◽  
Vol 48 (3) ◽  
pp. 220-230
Author(s):  
Vanessa Stout ◽  
Eric Earnhart ◽  
Mariam Nagi

Teaching race and ethnicity in various sociology courses, we found students in our classes can be very reluctant to approach the subject of race, discrimination, and racism. Moreover, during class discussion, they often have a hard time defining and analyzing these concepts. In this study, we examine how popular culture can be a useful tool to teach difficult subjects, such as race and ethnicity. Instead of a traditional lecture, we had students watch the popular Cartoon Network series Teen Titans. Using the characters’ interactions from this series as examples, students constructed definitions of racism and discrimination. The result of this study demonstrates that students may be more comfortable recognizing and discussing fictional characters’ racist or discriminatory behavior as a way of entering the conversation. After discussing fictional examples, students effectively link events from the cartoon to the subsequent lecture about race and racism.


2018 ◽  
Vol 19 (3) ◽  
Author(s):  
Josh Ederington ◽  
Jenny Minier ◽  
C. Jill Stowe

Abstract In the traditional Becker model of employer discrimination, discriminatory behavior arises from a utility-maximizing owner who balances firm profits against the disutility of hiring workers from the disadvantaged demographic group. However, in the modern firm, many human resource decisions are made by agents of the owner (managers) whose actions may not reflect the preferences of even profit-maximizing owners. We present a principal-agent model of discrimination with a profit-maximizing owner and a gender-discriminating manager and show that managerial discrimination is increasing with the degree of risk in the firm’s revenue stream. Empirical tests using a Colombian plant-level dataset support a prediction of our model that female workers should be under-represented in more revenue volatile firms and industries.


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