Kenneth Cukier: Big data is better data

Summary

In this insightful talk, Kenneth Cukier explores the transformative power of big data, illustrating how it enables us to see patterns and insights that were previously invisible. He uses the example of pie preferences to show how data can reveal unexpected truths. Cukier emphasizes the importance of big data in advancing society, addressing global challenges, and revolutionizing fields like machine learning. However, he also cautions about the potential dark sides, including the risk of predictive punishment and job displacement, urging us to harness big data responsibly to enhance our lives without compromising our free will.

Takeaways

• 🍎 The data from supermarket sales indicates that apple pie is America's favorite when considering large pies, but individual preferences shift when smaller pies are sold, revealing different favorites.
• 📊 More data provides deeper insights, allowing us to see not just more of the same, but also new and different patterns that were previously hidden.
• 🌐 Big data is a critical tool for societal advancement, with the potential to address global challenges like food supply, healthcare, energy, and climate change.
• 📚 Historically, data was stored in physical forms like clay discs, but today's data is digital, easily searchable, copyable, shareable, and processable.
• 🚀 The value of big data lies in its ability to enable new uses and applications that were unimaginable at the time of data collection, turning data from a static stock to a dynamic flow.
• 📈 Big data has facilitated advancements in machine learning, where algorithms learn from data rather than being explicitly programmed, leading to breakthroughs in various fields.
• 🚗 Examples of datafication include location tracking and posture analysis, which can be used for applications like anti-theft devices in cars and predictive maintenance.
• 🔮 Machine learning algorithms can identify patterns and make predictions that surpass human capabilities, as seen in the evolution of computer programs from simple games to complex tasks like driving and medical diagnosis.
• ⚠️ There are potential dark sides to big data, such as the risk of being punished based on predictive algorithms before any action is taken, raising ethical and privacy concerns.
• 🏢 Big data may disrupt job markets, as seen in the historical shift from manual labor to automation, suggesting a future where professional knowledge work could be significantly impacted.

Q & A

What is revealed about America's favorite pie when data from the sales of smaller pies is analyzed?

When analyzing data from the sales of smaller, individual-sized pies, apple pie fell to fourth or fifth place, suggesting that America's favorite pie might not be apple when people are choosing for themselves.

Why is more data considered valuable in understanding societal preferences?

More data allows for a more nuanced understanding of preferences by revealing patterns and choices that may not be evident with smaller data sets. It enables the observation of individual preferences rather than just general trends.

How does the concept of 'big data' differ from traditional 'small data' approaches?

Big data refers to the vast amounts of data that can be analyzed to reveal patterns, trends, and associations, whereas small data often involves analyzing smaller, more specific data sets to understand the world. Big data allows for the discovery of new insights that were not possible with small data.

What is the significance of the clay disc discovered on the island of Crete in the context of data storage?

The clay disc symbolizes the ancient method of storing and transmitting information, highlighting the evolution from physical and limited storage to the digital era where vast amounts of data can be stored and processed with ease.

How has the concept of data liquidity changed the way we use information?

Data liquidity refers to the ease with which data can be searched, copied, shared, and processed. This has transformed data from a static stock to a dynamic flow, allowing for its reuse in ways never imagined at the time of collection.

What is an example of how big data can be used to predict and prevent potential crimes?

Big data can be used in predictive policing, where historical crime data is analyzed to predict where future crimes are likely to occur, allowing for more effective allocation of law enforcement resources.

How is big data influencing the field of machine learning?

Big data is a driving force in machine learning, allowing algorithms to learn from vast amounts of data, thereby improving their predictive capabilities and enabling them to identify patterns and make decisions without explicit programming.

What are some potential negative consequences of relying on big data for predictions?

There is a risk of being punished based on predictions rather than actions, as big data can be used to anticipate behavior, potentially infringing on privacy and free will.

How might big data and algorithms impact the job market in the future?

Big data and algorithms could lead to significant job displacement, particularly in white-collar and professional sectors, by automating tasks and decision-making processes that were previously performed by humans.

What is the importance of being the 'master' of big data technology as opposed to its servant?

Being the master of big data technology means using it responsibly and ethically to enhance human lives, rather than being controlled by it, which could lead to misuse and unintended negative consequences.

Why is it crucial for society to adapt and learn how to handle the influx of big data?

Society must learn to handle big data to ensure its benefits are realized while mitigating risks. This includes understanding its implications for privacy, job displacement, and ethical decision-making.