How bad data keeps us from good AI | Mainak Mazumdar

The video discusses the role of AI in the future economy, highlighting its benefits and limitations, particularly in policy decision-making. It emphasizes the impact of biased data on AI decisions and the need for high-quality data. Case studies, including the 2020 US census, illustrate the consequences of data bias. The video stresses the importance of accurate data collection, especially in rural areas, to ensure fair AI models. It concludes with a call to build better data infrastructure for ethical AI.

What is a major limitation of AI in policy decision-making?

• Limited access to technology

• High cost of implementation

• Biased data leading to unfair decisions

• Lack of computational power

What was the main issue with the AI model from Duke University?

• It was too slow

• It was too expensive

• It required too much data

• It produced biased results due to underrepresented data

Why is the census data crucial for policy decisions?

• It is used for entertainment purposes

• It is updated every year

• It provides a comprehensive count of the population

• It is the only source of population data

What is a common issue with national censuses regarding minorities?

• Overcounting of urban populations

• Inaccurate age data

• Undercounting of minority groups

• Excessive data collection costs

Why is it important to collect data from rural areas?

• To increase data collection costs

• To simplify data analysis

• To reduce urban bias in decision-making

• To focus on urban development

What percentage of Indians live in rural areas according to the International Labour Organization?

• 30%

• 50%

• 80%

• 65%

What is the significance of including diverse data in AI models?

• It reduces the cost of data collection

• It ensures fair and accurate decision-making

• It speeds up data processing

• It simplifies algorithm design

What percentage of US households use over-the-air TV reception according to Nielsen data?

• 20%

• 15%

• 10%

• 5%

Why is it important for marketers to have data from minority populations?

• To focus on urban consumers

• To simplify marketing strategies

• To reach a wider audience and show relevant ads

• To increase advertising costs

What is the ultimate goal of improving data infrastructure for AI?

• To reduce data storage costs

• To make AI more ethical and inclusive

• To make AI faster

• To simplify AI algorithms