The Neuroscience of Decision Making: Are We Foul or Fair? Kimberly Papillon TEDxNashvilleWomen

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Summary

Kimberly Papillon's TEDxNashvilleWomen talk explores how our unconscious mind heavily influences our decision-making, often overriding our conscious values, particularly regarding fairness. She demonstrates this through various scientific studies, highlighting implicit bias in how we perceive names, faces, and voices. Papillon emphasizes that while these biases are deeply ingrained, they are learned and can be unlearned. She concludes by discussing how neuroscience not only reveals these problems but also offers solutions for individuals and systems to become more fair and objective.

Highlights

The Unconscious Mind's Dominance in Decision Making
00:00:14

Scientists theorize that the conscious components of the human brain can process 40 frames of information per second, while the unconscious components process 1.2 million frames. Many scientists believe this unconscious background process drives our decision-making, with conscious thought often serving to rationalize choices already made. This suggests that our perceived control over our brains and decisions, especially regarding fairness, might be limited, leading to surprising and sometimes unfair outcomes, even for those who value fairness most.

Implicit Bias and Names: The Amy Chin Experiment
00:02:28

Decision-making starts with data collection and memory. An experiment with Harvard undergraduates demonstrated implicit bias based on a name. Students conversed via email with an 'Asian American woman named Amy Chin.' When given the email address 'Amy,' they recalled her math score as lower and verbal score as higher than what was stated. Conversely, with the email address 'Chen,' they remembered her math score higher and verbal score lower. This shows how unconscious biases can affect memory and perception at the initial stage of information processing.

Implicit Bias and Faces: The Amygdala's Role
00:05:19

The amygdala, the brain region associated with fear and distrust, lights up when presented with certain faces. Studies showed higher amygdala activation for Black men's faces compared to White men's faces in some groups. This is a learned behavior, not innate, meaning it can be unlearned. The level of amygdala activation correlated with scores on the Implicit Association Test (IAT), suggesting that implicit bias is measurable and linked to physiological responses. Further research identified facial features (forehead size, cheekbones, chin, nasal indentation) that unconsciously influence perceptions of trustworthiness, unbeknownst to the observer.

Implicit Bias and Voices: Dehumanization
00:08:21

Two brain parts, the caudate and putamen, are involved in processing voices and encoding individuals as fully human. To be seen as human, a person must be perceived as both smart/competent (caudate) and nice/warm (putamen). A study analyzing reactions to different accents (Anglo-American, British, Cantonese, Spanish from Mexico) showed that the Spanish speaker consistently ranked last in both 'nice' and 'smart' categories. This dehumanization, or failure to fully encode as human, can lead to decreased empathy and unequal resource allocation. This bias begins as early as nine years old, with children showing preferences and assigning intelligence based on regional accents.

Solutions: Taking Control Through Self-Monitoring and Systemic Change
00:11:24

Neuroscience not only identifies the problem of implicit bias but also offers solutions. The 'shoot/no-shoot' test revealed biases, where participants were more likely to 'shoot' an unarmed Black man than an armed White man. Scientists discovered that activating the rostral anterior cingulate cortex (RACC), a part of the brain responsible for good performance on such tests, could lead to more accurate and fair decisions. This activation occurred simply by informing participants they would be monitored for race-related bias, demonstrating that self-monitoring can prompt conscious control over implicit biases. Papillon concludes that both individual self-monitoring and systemic examination of decision-making are crucial to address implicit bias in areas like hiring, medical treatment, and education.

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