Interview with Mahzarin Banaji, 17th Frontiers of Knowledge Award in Social Sciences скачать в хорошем качестве

Interview with Mahzarin Banaji, 17th Frontiers of Knowledge Award in Social Sciences

The BBVA Foundation Frontiers of Knowledge Award in Social Sciences has gone in this seventeenth edition to social psychologists Icek Ajzen, Dolores Albarracín, Mahzarin Banaji, Anthony Greenwald and Richard Petty for “revolutionizing the way we understand and measure attitudes" with an influence that extends to “psychology, sociology, political science, education, health, economics and other areas.” Mahzarin Banaji’s research focuses on the disparities between people’s conscious expressions of their values, attitudes and beliefs and the less conscious representation of their mind’s content. When, in 1998, she convinced Yale University to put the implicit association test (IAT, created by Anthony Greenwald) online, they got 40,000 responses in one month, a reception which would revolutionize the study of implicit bias. Banaji has corroborated the IAT’s results with neuroimaging techniques, observing that the amygdala – the part of the brain that responds to the new or strange – reacts more strongly to black versus white faces the greater the racial bias revealed by the IAT. And she has also been able to show that such biases may not be innate but are nonetheless acquired at a very young age, given that six-year-old children have the same levels of implicit bias as adults. More recently, she has analyzed the presence of these biases in online texts. Using a database of 840,000 words she found that the most frequent associations for “man” or “male” had to do with war and sports, while “woman” and “female” were predominantly associated with abuse and pornography, as well as cooking and motherhood. Motivated by these conclusions, she has turned her attention to analyzing bias in generative artificial intelligence models such as Chat-GPT. 00:04 Professor Banaji, as the committee has highlighted in its citation, together with Professor Greenwald, you developed the Implicit Association Test, which allows for reliable measurement of implicit bias and its effects on decision making. Could you describe what this test consists of and why you developed it? 01:39 To what extent can we modify our own implicit biases, and how can we make that happen? 02:33 Why is mandatory diversity training at work counterproductive, and how can we make voluntary training attractive enough so decision-makers engage? 03:42 How has the knowledge about implicit biases evolved since the implicit association test was first developed in 1998? Discover more here: https://www.frontiersofknowledgeaward... Follow us and learn about all our initiatives: https://www.fbbva.es/en/