This is a summary of a book titled “The Age of Prediction” written by Christopher Mason and Igor Tulchinsky and published by MIT Press, 2023. This book highlights the potential of AI algorithms and big data to reduce uncertainty and risks in various industries. They suggest that while exponential data growth won't eliminate risk, it can create both dystopian possibilities and life-saving solutions. Future employers could use genetic markers for performance prediction, while AI-enabled weapons could threaten humanity. More accurate predictive polling could lead to voter manipulation, threatening democracy. As humankind's ability to make accurate predictions increases, complex new risks emerge. The COVID-19 pandemic exemplified this, with BioNTech using machine-learning trained algorithms to create a COVID-19 vaccine in just nine months. The exponential growth of data production has led to increased competition and turbulence, requiring companies to embrace flexibility and empiricism. As the world's data continues to grow exponentially, it is essential to leverage diverse perspectives when model building to gain better insights from big data.

Predictive models can be more effective when leveraging diverse data sets, including proxy data from interconnected sources. For example, Kinsa's smart thermometers helped researchers predict COVID-19 outbreaks more accurately. WorldQuant Predictive uses an approach called "idea arbitrage" to apply financial prediction tools across industries. However, exponential data growth won't eliminate risk, as complex systems are constantly in flux. As predictive accuracy increases, "moral hazard" can increase when actors perceive diminished risks. The garden of biology and data is constantly growing and changing, and data scientists must re-analyze older data when newer data emerges. New predictive tools create both dystopian possibilities and life-saving solutions. Scientists can use cell-free DNA analysis to predict health problems, heart transplant success, and detect tissue death. The body's signals can also be interpreted, such as mitochondrial DNA serving as a warning system for stress or suicide.

Predictive technologies have led to a demand for data that many people view as intimate or private. As data-enabled predictions become more ubiquitous, eroding privacy, new risks such as genetic discrimination and weaponizing identity tracing arise. Insurers could easily change life insurance premiums if an individual had genetic markers indicating a vulnerability to certain diseases. As human life is increasingly quantified and scientists collect new forms of data, people are becoming increasingly resistant to sharing data.

Future employers could draw on new forms of data, such as genetic markers, when predicting performance. However, predicting performance accurately is not always easy, and companies rely on external recruiters who often fail to accurately predict which candidates will perform well. In the future, predicting careers based on genetic data may become the norm, as employers may expect workers to modify their genomes. AI-enabled predictions are transforming modern warfare, with militaries exploring how to rapidly analyze nonstop streams of data and make rapid predictions needed for decision-making during combat. Precision-guided bombs and missiles enable militaries to wreak devastation by improving accuracy, using controls similar to those in video games.

The development of autonomous weapons systems raises ethical concerns as machine decision-making could replace human decision-making in selecting human targets. The US Department of Defense is reluctant to give robots full autonomy during warfare, and autonomous weapons could end up on the black market, posing a threat to humanity. Accurate predictive polling can lead to voter manipulation, threatening democracy. As humankind's power to make accurate predictions increases, complex new risks emerge, including economic disruption, job loss, privacy threats, mass surveillance, anti-science sentiments, epistemic confusion, and authoritarianism. As machines become more opaque, it becomes harder for humans to detangle the logic behind predictions. Humans must reflect on what life might be like if machines obtain a monopoly on predictable areas, such as politics and war. The potential benefits of predictive AI algorithms outweigh the risks, as AI could help humans achieve various goals, such as colonizing Mars or extending life expectancy.

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