ties in the academy and industry. But that could soon change. Global challengers Russia and Chinag recognize the importance of shaping AI technologies and have poured substantial support and funding into boosting their national industries. If the U.S. falls behind, global innovation arbitrageh will kick in and technologists and companies will flock to countries where such creativity is treated more hospitably.

How can the U.S. stay ahead? Part of the reason the U.S. has been so successful with AI deployment is a relatively permissive policy regime. The U.S. houses some of the most successful technology companies in the world due to the federal government’s explicit embrace of permissionless innovation in the 1990s.i Other countries, particularly in Europe,j that pursued a more precautionary approach ended up hemorrhaging talent to other more open environments.

To date, there is no central regulatory authority tasked with reviewing and approving each new instance of AI development in the U.S. Rather, regulators at disparate agencies apply existing rules in accordance with their established authorities—so the FDA oversees applications of health-related AI, the Securities and Exchange Commission (SEC) monitors automated trading, and the National Highway Transportation Safety Administration (NHTSA) is tasked with autonomous vehicle oversight. While imperfect, this approach has the benefit of limiting regulations to a narrow domain.

Case Study: Autonomous Cars

Autonomous transport presents perhaps the most salient example of how AI will fundamentally change our future. Of course, driverless cars and commercial drones also generate some of the greatest anxieties regarding safety and control. As such, they provide a good example of the tensions between onerous regulation and a more permissive policy environment.

Americans in general are a bit worried by the concept of driverless cars. According to an October 2017 Pew g https://bit.ly/2eRiynC h https://bit.ly/2pWKnwy i https://bit.ly/2QZaXRb j https://bit.ly/2CRKi66

higher and take risks in braving the high seas precisely because progress and prosperity—for both them and society at large—depend upon it.

The same holds true for all new innovations. When we fail to consider the upsides new developments could bring, we can end up doing more harm to ourselves than if we allowed a new technique to continue without burden.

Consider drug regulation. On its face, it seems logical for a pharmaceutical regulator like the Food and Drug Administration (FDA) to maintain exacting regulations against new medicines until they can be proven almost entirely safe. After all, the risk of dangerous side effects harming or even killing people in the long term is a formidable one indeed.

But what about the people who could
be saved by an experimental treatment
that is unjustly delayed or prohibited?
We don’t see these people or their
plights as readily, but they are just as
real. Because their suffering or death is
under the radar, the tragic effects of this
kind of error are not accounted for. This
was the unfortunate outcome of the
FDA’s delayed approval of a drug named
Misoprostol to treat gastric ulcers in the
early 1980s. Their dithering ended up
costing up to 15,000 lives.a
Humans are already well aware of
the first-order risks of new technolo-
gies like AI applications. We fear errors
in the opposite direction: that policy-
makers and the public will underrate
the improvements AI can bring, and
will allow fears of worst-case scenarios
to justify policies that ensure best-case
scenarios never come about.

What’s at Stake

After centuries of speculation in both the academy and science fiction, AI is finally shaping our lives in important ways. While we are still far away from the kind of “strong,” self-directing AI first anticipated by Mary Shelley’s Frankenstein almost 200 years ago, narrower applications of machine learning and big data techniques are already integrated into the world around us in subtle but important ways.

Many are unaware of just how prevalent AI techniques already are.b They

a https://bit.ly/1PokgDI
b https://bit.ly/2fpaUQ7
quietly help to more efficiently connect
us with the information that is most
valuable to us, whether the data in
question is related to healthcare, con-
sumer products and services, or just
reconnecting with an old friend.
For example, neural networks can
help doctors to diagnose medical ail-
mentsc and recommend treatments,
thereby saving money on testing and
office visits and potentially improving
the likelihood of recovery and remis-
sion. Yelpd has developed a machine
learning program that translates us-
er-submitted restaurant photos into
searchable data on a restaurant’s
cuisine and atmosphere. And the
rise of AI-powered “virtual personal
assistants”e on social media platforms
will help us to better keep track of our
relationships and obligations with lit-
tle thought required on our parts.

And yet these marginal improvements in efficiency and matching will yield great dividends in our economy and our personal lives. Analystsf project savings and economic growth to exceed hundreds of billions or even trillions of dollars over the coming decade, thanks to improvements in manufacturing, transit, and health. The ease and convenience of tailored artificial assistance will likewise improve our overall qualities of life and leave us more time to do the things that really matter to us.

The U.S. in particular has been a leader in AI development, boasting the world’s most innovative research facili- c https://bit.ly/2RZf7Km d https://bit.ly/2R4SYZZ e https://on.ft.com/2pX38QE f https://on.ft.com/2pX38QE

Part of the reason
the U.S. has been
so successful
with AI deployment
is a relatively
permissive
policy regime.