This kind of hype has contributed to a frenzy of misunderstandings about what AI actually is and what it can and cannot do. Crucially, generative AI is a seductive distraction from the type of AI that is most likely to make your life better, or even save it: Predictive AI. In contrast to AI designed for generative tasks, predictive AI involves tasks with a finite, known set of answers; the system just has to process information to say which answer is right. A basic example is plant recognition: Point your phone camera at a plant and learn that it’s a Western sword fern. Generative tasks, in contrast, have no finite set of correct answers: The system must blend snippets of information it’s been trained on to create, for example, a novel picture of a fern.
The generative AI technology involved in chatbots, face-swaps, and synthetic video makes for stunning demos, driving clicks and sales as viewers run wild with ideas that superhuman AI will be capable of bringing us abundance or extinction. Yet predictive AI has quietly been improving weather prediction and food safety, enabling higher-quality music production, helping to organize photos, and accurately predicting the fastest driving routes. We incorporate predictive AI into our everyday lives without evening thinking about it, a testament to its indispensable utility.
To get a sense of the immense progress on predictive AI and its future potential, we can look at the trajectory of the past 20 years. In 2005, we couldn’t get AI to tell the difference between a person and a pencil. By 2013, AI still couldn’t reliably detect a bird in a photo, and the difference between a pedestrian and a Coke bottle was massively confounding (this is how I learned that bottles do kind of look like people, if people had no heads). The thought of deploying these systems in the real world was the stuff of science fiction.
Yet over the past 10 years, predictive AI has not only nailed bird detection down to the specific species; it has rapidly improved life-critical medical services like identifying problematic lesions and heart arrhythmia. Because of this technology, seismologists can predict earthquakes and meteorologists can predict flooding more reliably than ever before. Accuracy has skyrocketed for consumer-facing tech that detects and classifies everything from what song you’re thinking of when you hum a tune to which objects to avoid while you’re driving—making self-driving cars a reality.
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