The Managerial Effects of Algorithmic Fairness Activism

Cowgill, Bo; Dell'Acqua, Fabrizio; Matz, Sandra

doi:10.1257/pandp.20201035

Cited by 14 publications

(4 citation statements)

References 7 publications

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“…Instead, we need to consider them vis-a-vis the status quo and available alternatives. For example, a focus on algorithmic fairness might lead people to reject algorithms in the context of recruiting processes, even if the bias introduced by algorithms might be well below that introduced through the stereotypes held by human resources personnel (Cowgill et al, 2020). Hence, we need to ask what the alternatives to data-driven solutions and particular predictive algorithms are, and whether these alternatives serve us better or worse.…”

Section: Discussionmentioning

confidence: 99%

Privacy and ethics in the age of Big Data.

Matz,

Appel,

Croll

2022

The Psychology of Technology: Social Science Research in the Age of Big Data.

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do not fully understand. As our relationship with technology and data becomes more and more intimate, a major question arises: How can we design ethical technology that uses data generated by our interactions with the digital world responsibly and in a way that benefits-rather than exploits-individuals, and strengthens-rather than undermines-the social fabric of the societies we live in? What is clear from the ongoing debate around the data revolution is that individuals and societies stand to both gain and lose. On the one hand, individuals can benefit from personalized services that make many aspects of everyday life easier than ever before (Matz & Netzer, 2017;Sagiroglu & Sinanc, 2013), and the ability to pool data such as medical records to better understand diseases and ways to combat them holds great promise for the flourishing and health of society as a whole (Tatonetti et al., 2012). On the other hand, Big Data threatens to erode our privacy in unprecedented ways, opening the door for manipulation, polarization, and discrimination (Acquisti et al., 2015;Cohen, 2000;.Depending on your own view of technology, you might have had very different reactions to the previous examples. You might have felt that technology is a wonderful enabler of modern life, or you might have felt that technology is increasingly infringing on our autonomy. Research shows that there is a lot of heterogeneity in the ways that people perceive and feel about technologies, both across different individuals and within individuals. Not only are some people generally more concerned about the extent to which technology infringes on their privacy (e.g.,

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Section: Discussionmentioning

confidence: 99%

Privacy and ethics in the age of Big Data.

Matz,

Appel,

Croll

2022

The Psychology of Technology: Social Science Research in the Age of Big Data.

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show abstract

“…Hence, explanations matter: simply providing information about the accuracy of algorithm is not sufficient to enable observers to accurately judge an algorithm's validity. Indeed, a recent experiment shows that the way an algorithm is explained seems to affect how people perceive it (159).…”

Section: Discussion and Policy Insightsmentioning

confidence: 99%

We and It: An Interdisciplinary Review of the Experimental Evidence on Human-Machine Interaction

Chugunova¹,

Sele²

2020

SSRN Journal

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Today, humans interact with technology frequently and in a variety of settings. Their behavior in these interactions has attracted considerable research interest across several fields, with sometimes little exchange among them and seemingly inconsistent findings. Here, we review over 110 experimental studies on human-machine interaction. We synthesize the evidence from different disciplines, suggest ways to reconcile inconsistencies, and elaborate on political and societal implications. The reviewed studies show that people react to automated agents differently than to humans: They behave more rationally, and are less prone to emotional and social responses. We show that there are several factors which systematically impact the willingness to accept automated decisions: task context, performance expectations and the distribution of decision authority. That is, humans seem willing to (over-)rely on algorithmic support, yet averse to fully ceding their decision authority. These behavioral regularities need to be considered when deliberating the benefits and risks of automation.

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“…In some contexts, the reduced emotional and social response leads to beneficial outcomes such as, for example, increased disclosure of intimate partner violence if reporting to computers (Ahmad et al, 2009;Humphreys et al, 2011). Moreover, algorithms appear to enjoy the perceived "halo" of scientific authority and objectivity (Cowgill et al, 2020). Users also tend to incorporate recommendations from an algorithm more than those from other humans (Logg et al, 2019;Sele and Chugunova, 2022).…”

Section: Related Literaturementioning

confidence: 99%

Human mediation leads to higher compliance in digital mental health: field evidence from India

Chatterjee,

Chugunova,

Ghosh

et al. 2023

Front. Behav. Econ.

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The Managerial Effects of Algorithmic Fairness Activism

Cited by 14 publications

References 7 publications

Privacy and ethics in the age of Big Data.

Privacy and ethics in the age of Big Data.

We and It: An Interdisciplinary Review of the Experimental Evidence on Human-Machine Interaction

Human mediation leads to higher compliance in digital mental health: field evidence from India

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