What can the implicit social cognition literature teach us about implicit social cognition?

Kurdi, Benedek; Dunham, Yarrow

doi:10.1017/s0140525x21000595

Cited by 3 publications

(2 citation statements)

References 117 publications

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“…At first sight, it seems self-evident that one elegant way to address the consequences of implicit and explicit biases in important welfare and social decisions making (Greenwald & Lai, 2020;Kurdi & Dunham, 2022) would be to delegate important decisions-for instance, on allocating benefits, resources, or opportunities-to algorithms.…”

Section: Discussionmentioning

confidence: 99%

“…These implicit biases matter. Many injustices, inequities, and discriminatory behaviors, including police shootings of Black Americans, the gender pay gap, health care inequities, and discriminatory hiring practices are thought to be due in part to, of course, explicit but also implicit biases (for findings shedding light on the relationship between implicit social cognition and real-world inequality, see Kurdi & Dunham, 2022).…”

Section: Institutions and Machines Implicit Biases: A Public Policy P...mentioning

confidence: 99%

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Blinding to circumvent human biases: Deliberate ignorance in humans, institutions, and machines

Hertwig¹,

Kozyreva²,

Herzog³

2022

Preprint

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Persistent inequalities and injustices are a blight on modern liberal societies. Examples abound, from the gender gap in pay to sentencing disparities between Black, Hispanic, and White defendants to allocation disparities in medical resources between Black and White patients. One cause of these and other inequalities is implicit social biases. In a process thought to be outside conscious control, human cognition is assumed to make associations between social groups and attributions such as "nurturing," "lazy," or "uneducated." Such associations can result in explicit unequal treatment. In theory, one way to circumvent implicit but, of course, also explicit biases is to delegate important decisions—for instance, on allocating benefits, resources, or opportunities—to algorithms, which are assumed to be free of human biases. However, evidence shows that algorithms can perpetuate and even amplify existing inequalities and injustices. We discuss how a philosophical thought experiment, Rawls's "veil of ignorance," and a psychological phenomenon, "deliberate ignorance" (the choice to not know), can shield people, institutions, and algorithms from biases. We explore the advantages and ways of blinding human and artificial decision makers to information that could result in biases and consider the practical problems of successfully blinding algorithms.

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Section: Discussionmentioning

confidence: 99%

Section: Institutions and Machines Implicit Biases: A Public Policy P...mentioning

confidence: 99%

Blinding to circumvent human biases: Deliberate ignorance in humans, institutions, and machines

Hertwig¹,

Kozyreva²,

Herzog³

2022

Preprint

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What Implicit Measures of Bias Can Do

Melnikoff

Kurdi

2022

Psychological Inquiry

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Blinding to Circumvent Human Biases: Deliberate Ignorance in Humans, Institutions, and Machines

Hertwig,

Herzog,

Kozyreva

2023

Perspect Psychol Sci

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Inequalities and injustices are thorny issues in liberal societies, manifesting in forms such as the gender–pay gap; sentencing discrepancies among Black, Hispanic, and White defendants; and unequal medical-resource distribution across ethnicities. One cause of these inequalities is implicit social bias—unconsciously formed associations between social groups and attributions such as “nurturing,” “lazy,” or “uneducated.” One strategy to counteract implicit and explicit human biases is delegating crucial decisions, such as how to allocate benefits, resources, or opportunities, to algorithms. Algorithms, however, are not necessarily impartial and objective. Although they can detect and mitigate human biases, they can also perpetuate and even amplify existing inequalities and injustices. We explore how a philosophical thought experiment, Rawls’s “veil of ignorance,” and a psychological phenomenon, deliberate ignorance, can help shield individuals, institutions, and algorithms from biases. We discuss the benefits and drawbacks of methods for shielding human and artificial decision makers from potentially biasing information. We then broaden our discussion beyond the issues of bias and fairness and turn to a research agenda aimed at improving human judgment accuracy with the assistance of algorithms that conceal information that has the potential to undermine performance. Finally, we propose interdisciplinary research questions.

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What can the implicit social cognition literature teach us about implicit social cognition?

Cited by 3 publications

References 117 publications

Blinding to circumvent human biases: Deliberate ignorance in humans, institutions, and machines

Blinding to circumvent human biases: Deliberate ignorance in humans, institutions, and machines

What Implicit Measures of Bias Can Do

Blinding to Circumvent Human Biases: Deliberate Ignorance in Humans, Institutions, and Machines

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