The Fight vs. Bias Data in Artificial Intelligence

The video discusses the pervasive issue of bias in artificial intelligence, highlighting its impact on marginalized communities and various sectors like credit, legal, and healthcare. It emphasizes the need for diversity in AI research to mitigate bias and presents historical cases of AI bias. The challenges in solving AI bias are explored, noting the complexity of AI systems and the efforts by organizations like Google and Microsoft to address these issues.

What is one of the main reasons bias in AI can be problematic?

• It reduces the need for human oversight.

• It makes AI systems faster.

• It can affect marginalized communities negatively.

• It can lead to more accurate predictions.

Which investigation highlighted bias in AI systems used for parole and sentencing?

• A research by Boston University

• A study by Microsoft

• A report by Google

• A ProPublica investigation

What was a significant issue with Google's photo software?

• It misidentified animals.

• It was too slow to process images.

• It tagged black people incorrectly.

• It failed to recognize landscapes.

What is one of the challenges in addressing AI bias?

• AI systems are too simple.

• AI systems are black boxes.

• AI systems are rarely used.

• AI systems are transparent.

What is DARPA focusing on to help solve AI bias?

• Building explainable AI

• Creating more complex AI systems

• Developing faster AI algorithms

• Reducing AI usage in government