The Psychiatry of Stereotyping, Prejudice, and Resilience
“You cannot control the behavior of others, but you can always choose how you respond to it.” ― Roy T. Bennett (Zimbabwe)
Both stereotypes and prejudice are learned and can be unlearned. Neuroscience has confirmed a differnce between stereotypes and prejudice. Stereotypes are more like guesses when we don’t have enough information. Prejudice is a preconceived opinion that is not based on reason or actual experience and is usually tied to emotions like hate or fear. Understanding how they develop is the first step in trying to change.
When faced with opposition, individuals may defend their prejudices with false data or conspiracy theories. Prejudices, ranging from racism to climate denial, are emotionally charged and resistant to change, impacting victims significantly. Epley's "Mindwise" outlines prejudice as a human tendency.
Transference involves projecting one's feelings onto an analyst, while countertransference is the reverse. These psychological phenomena stem from our unconscious efforts to find familiar patterns. Such biases can distort relationships, requiring awareness to address them. Upcoming blogs will explore techniques to mitigate these biases.
Psychological defenses help manage stress and anxiety, altering perception to ease discomfort when direct action isn't possible. These unconscious mechanisms, as outlined in the Harvard Grant Study, range from immature to mature, to defend against anxiety but also lead to prejudices. Cognitive dissonance theorizes that conflicting beliefs lead to changed attitudes to relieve guilt. Insight and reflection are crucial to tackling prejudice.
Prejudices are learned behaviors, acquired unconsciously through associative learning mechanisms like classical conditioning. Conscious efforts to question our assumptions can mitigate prejudice. The role of media, family, and peers is critical in shaping or challenging these learned associations.
Artificial Intelligence (AI) and AI models such as GPT-4 are changing our understanding of tasks traditionally performed by humans, including problem-solving and language generation. GPT-4 can mimic human text but lacks "common sense" and can exhibit biases. Fact-checking should be done before publication, but data for AI may not be. Its decision-making is only as reliable as its training data. Limited by the data it's given, AI like GPT-4 cannot completely comprehend complex social issues. It may also "hallucinate" or produce information that is not grounded in its training. Complete and accurate information are needed to enhance AI's predictive accuracy and reduce stereotypical biases.