TED: The human insights missing from big data | Tricia Wang

The video discusses the historical use of oracles for decision-making and compares it to modern big data systems. It highlights the challenges companies face with big data, using Nokia as a case study of failing to recognize smartphone demand. The concept of quantification bias is introduced, emphasizing the need to integrate thick data, which includes qualitative insights, with big data for more comprehensive decision-making. The video concludes with examples of successful integration, such as Netflix's transformation through understanding binge-watching behavior.

What modern technology is compared to ancient oracles in the video?

• Big Data

• Artificial Intelligence

• Quantum Computing

• Virtual Reality

What percentage of big data projects are reported to be unprofitable?

• 80%

• 73%

• 60%

• 50%

What was the speaker's role at Nokia?

• Marketing Specialist

• Data Scientist

• Technology Ethnographer

• Software Engineer

What did the speaker predict about low-income Chinese consumers?

• They would prefer luxury cars

• They would invest in real estate

• They would desire smartphones

• They would save money

What is the term used to describe the bias of valuing measurable data over immeasurable data?

• Data Bias

• Measurement Bias

• Quantification Bias

• Statistical Bias

What did Netflix discover about their users' viewing habits?

• Users preferred watching movies

• Users disliked recommendations

• Users watched only on weekends

• Users liked to binge-watch

What role do ethnographers play in big data systems?

• They design user interfaces

• They gather thick data

• They develop algorithms

• They manage databases

What is the potential risk of relying solely on big data?

• Increased profits

• Improved customer satisfaction

• Missing critical insights

• Faster decision-making

What is the main benefit of integrating thick data with big data?

• Simplified data models

• Faster data processing

• More comprehensive insights

• Reduced data storage

What industry example is used to illustrate the integration of thick and big data?

• Entertainment

• Retail

• Healthcare

• Automobile