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“Humanity has entered a new era.” This bold statement opens Igor Tulchinsky and Christopher E Mason’s groundbreaking book, The Age of Prediction, which delves into the transformative impact of predictive algorithms.
The timing of this publication couldn’t be better. In 2016, the world witnessed the AI breakthrough when Google DeepMind’s AlphaGo defeated the reigning Go champion. Four years later, AlphaFold solved the complex puzzle of predicting protein structures. The release of OpenAI’s ChatGPT and other advanced language models further demonstrated the astonishing capabilities of machine learning.
Instead of getting tangled in the AI debate, The Age of Prediction focuses on three key factors driving the recent achievements. First, the explosion of data through the digitization of human life. Second, the development of advanced statistical techniques that effectively analyze big data. Third, the plummeting cost of computing power, supported by cutting-edge hardware like Nvidia’s V100 chip.
This convergence of data, statistical techniques, and computing power has revolutionized the predictive capabilities of statistical models. The comprehensive impact of this transformation is evident across various fields, from headline-grabbing examples like AlphaFold to lesser-known but equally significant disruptions in insurance, the arms industry, and political campaigning.
A significant portion of the analyzed data comes from genetics. With advancements in DNA sequencing technology, genetic data is now readily available for predictive purposes. Start-ups like Craig Venter’s Human Longevity claim to predict individual traits, like voice, height, and facial features, solely from trace DNA. Moreover, the integration of non-human genetic information, such as microbes, raises possibilities for precise identification.
The dystopian future portrayed in the film Gattaca, where genomes dictate individuals’ lives and roles in society, is becoming increasingly plausible. However, this future poses a range of challenges and paradoxes. Can predictive models effectively account for the adaptive nature of human behavior? How can privacy concerns be addressed as predictive algorithms become more invasive? And if everything becomes predictable, what happens to free will?
Tulchinsky and Mason raise thought-provoking questions about the implications of entering this new era. If predictability becomes the norm, uncertainty and free will may cease to exist. In such a scenario, distinguishing between true prediction and the mere elimination of other possibilities becomes challenging.
Indeed, while we embrace this new era, it is essential to confront the fundamental questions that have puzzled humanity for centuries.
The Age of Prediction: Algorithms, AI, and the Shifting Shadows of Risk by Igor Tulchinsky and Christopher E Mason, published by MIT Press.
Felix Martin is the author of ‘Money: The Unauthorised Biography’
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