Deep Background with Noah Feldman
A Solution for Algorithmic Bias
Sep 7, 2019
Algorithmic bias and its impact on various aspects of daily life are discussed. Examples include targeted ads, credit evaluation, job applications, and crime prediction. The potential of algorithms to address biases in areas like criminal justice and employment decisions is explored, along with concerns about the lack of diligence in algorithm development. The challenges of assessing discrimination and algorithmic bias are discussed, as well as recent developments in British politics regarding Brexit.
36:09
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Quick takeaways
- Algorithmic bias in algorithms used for criminal justice highlights the need for unbiased training data and ethical frameworks in algorithm development.
- Diverse representation in algorithm development teams is crucial to mitigate implicit biases and ensure fair decision-making.
Deep dives
Algorithmic Bias in Society
Algorithms play a significant role in many aspects of our lives, from targeted advertising to determining credit worthiness. However, there is growing concern about algorithmic bias, particularly when it comes to perpetuating racial discrimination. Algorithms are trained on large volumes of data, which can sometimes reflect biased or skewed information. For example, the Compass algorithm used in the criminal justice system relied on data that disproportionately affected African-American defendants. It reinforced pre-existing biases and led to lengthier detainment before sentencing for African-Americans. This highlights the challenge of biased training data and the need for more awareness and ethical frameworks in algorithm development.
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