...this aptitude for cognitive time travel, revealed by the discovery of the default network, may be the defining property of human intelligence. “What best distinguishes our species,” Seligman wrote in a Times Op-Ed with John Tierney, “is an ability that scientists are just beginning to appreciate: We contemplate the future.” He went on: “A more apt name for our species would be Homo prospectus, because we thrive by considering our prospects. The power of prospection is what makes us wise.”Johnson discusses the augmentation of our future predicting by A.I. algorithms:
Accurate weather forecasting is merely one early triumph of software-based time travel: algorithms that allow us to peer into the future in ways that were impossible just a few decades ago...In machine-learning systems, algorithms can be trained to generate remarkably accurate predictions of future events by combing through vast repositories of data from past events. An algorithm might be trained to predict future mortgage defaults by analyzing thousands of home purchases and the financial profiles of the buyers, testing its hypotheses by tracking which of those buyers ultimately defaulted.
Machine-learning systems will also be immensely helpful when mulling decisions that potentially involve a large number of distinct options. Humans are remarkably adept at building imagined futures for a few competing timelines simultaneously: the one in which you take the new job, the one in which you turn it down. But our minds run up against a computational ceiling when they need to track dozens or hundreds of future trajectories. The prediction machines of A.I. do not have that limitation, which will make them tantalizingly adept at assisting with some meaningful subset of important life decisions in which there is rich training data and a high number of alternate futures to analyze.
These algorithms can help correct a critical flaw in the default network: Human beings are famously bad at thinking probabilistically. The pioneering cognitive psychologist Amos Tversky once joked that where probability is concerned, humans have three default settings: “gonna happen,” “not gonna happen” and “maybe.” We are brilliant at floating imagined scenarios and evaluating how they might make us feel, were they to happen. But distinguishing between a 20 percent chance of something happening and a 40 percent chance doesn’t come naturally to us. Algorithms can help us compensate for that cognitive blind spot.
Whether you find the idea of augmenting the default network thrilling or terrifying, one thing should be clear: These tools are headed our way. In the coming decade, many of us will draw on the forecasts of machine learning to help us muddle through all kinds of life decisions: career changes, financial planning, hiring choices. These enhancements could well turn out to be the next leap forward in the evolution of Homo prospectus, allowing us to see into the future with more acuity — and with a more nuanced sense of probability — than we can do on our own. But even in that optimistic situation, the power embedded in these new algorithms will be extraordinary, which is why Ludwig and many other members of the A.I. community have begun arguing for the creation of open-source algorithms, not unlike the open protocols of the original internet and World Wide Web. Drawing on predictive algorithms to shape important personal or civic decisions will be challenging enough without the process’s potentially being compromised or subtly redirected by the dictates of advertisers. If you thought Russian troll farms were dangerous in our social-media feeds, imagine what will happen when they infiltrate our daydreams.
TODAY, IT SEEMS, mind-wandering is under attack from all sides. It’s a common complaint that our compulsive use of smartphones is destroying our ability to focus. But seen through the lens of Homo prospectus, ubiquitous computing poses a different kind of threat: Having a network-connected supercomputer in your pocket at all times gives you too much to focus on. It cuts into your mind-wandering time. The downtime between cognitively active tasks that once led to REST states can now be filled with Instagram, or Nasdaq updates, or podcasts. We have Twitter timelines instead of time travel. At the same time, a society-wide vogue for “mindfulness” encourages us to be in the moment, to think of nothing at all instead of letting our thoughts wander. Search YouTube, and there are hundreds of meditation videos teaching you how to stop your mind from doing what it does naturally. The Homo prospectus theory suggests that, if anything, we need to carve out time in our schedule — and perhaps even in our schools — to let minds drift.
According to Marcus Raichle at Washington University, it may not be too late to repair whatever damage we may have done to our prospective powers. A few early studies suggest that the neurons implicated in the default network have genetic profiles that are often associated with long-term brain plasticity, that most treasured of neural attributes. “The brain’s default-mode network appears to preserve the capacity for plasticity into adulthood,” he told me. Plasticity, of course, is just another way of saying that the network can learn new tricks. If these new studies pan out, our mind-wandering skills will not have been locked into place in our childhood. We can get better at daydreaming, if we give ourselves the time to do it.
What will happen to our own time-traveling powers as we come to rely more on the prediction machines of A.I.? The outcome may be terrifying, or liberating, or some strange hybrid of the two. Right now it seems inevitable that A.I. will transform our prospective powers in meaningful new ways, for better or for worse. But it would be nice to think that all the technology that helped us understand the default network in the first place also ended up pushing us back to our roots: giving our minds more time to wander, to slip the surly bonds of now, to be out of the moment.