How AI Preserves Systemic Racism

The video discusses the intersection of artificial intelligence and race, focusing on systemic racism's impact on black communities. It highlights how AI can perpetuate existing biases due to historical data and institutional structures. Examples include credit systems, facial recognition, and healthcare, where AI algorithms have shown bias against black individuals. The video emphasizes the need for awareness and improvement in AI systems to address these issues.

What historical event is highlighted to emphasize the ongoing impact of systemic racism?

• Juneteenth

• The Voting Rights Act

• The Emancipation Proclamation

• The Civil Rights Act

How is systemic racism different from individual racism?

• It is based on personal beliefs

• It only affects certain races

• It is expressed through institutions

• It is less harmful

What is a major challenge in making AI decisions transparent?

• Data is always biased

• AI decisions are always correct

• AI models are too complex

• Algorithms don't think like humans

Which of the following is NOT a characteristic of AI systems?

• They are visible to users

• They amplify data patterns

• They often work behind the scenes

• They can be hard to question

What historical practice in banking exemplified explicit discrimination?

• Redlining

• Credit scoring

• Interest rate adjustment

• Loan approval

What issue does facial recognition technology face due to historical biases?

• Inaccurate identifications

• High cost of implementation

• Lack of data storage

• Over-reliance on human input

In healthcare, what assumption led to biased algorithmic decisions?

• Lower spending indicates better health

• All patients have equal access to care

• Healthcare costs are irrelevant

• Higher spending indicates better health