Tools and Weapons: The Promise and The Peril of the Digital Age

by Brad Smith

Foreign interference with democratic processes can be met successfully only if the stakeholders in a republic set aside enough of their differences to work together to respond effectively.

It was against this backdrop and continuing French attempts to tamper with American politics that Washington used his farewell address in 1796 to warn against the risks of foreign influence. “A free people,” he said, “ought to be constantly awake, since history and experience prove that foreign influence is one of the most baneful foes of republican government.

As Poor’s Manual of the Railroads of the United States so aptly put it at the turn of the century, “No enterprise is so seductive as a railroad for the influence it exerts, the power it gives, and the hope of gain it offers.”2

“There’s no national security without cybersecurity,”

Just as governments had pledged in 1949 to protect civilians in times of war, perhaps a Digital Geneva Convention could capture people’s imagination about the need for governments to protect civilians on the internet in times of peace. It was an idea that could build on work already in motion by governments, diplomats, and tech experts focused on establishing so-called cybersecurity norms between nations. Perhaps a compelling example and brand would help us speak more effectively to the nontechnical audiences that we needed to win over if any of this were to become a reality.

“A strange game. The only winning move is not to play.”

As former US ambassador to Russia Michael McFaul put it, there was no longer a Cold War, but instead a Hot Peace.

“When you’re small, you have to be nimble!”

In the twenty-first century, the best way to address global issues is to put in place a team that can work not only with other governments but also with all the stakeholders that are defining technology’s future.

In December 2013, as tech leaders met at the White House to urge President Obama to reform government surveillance practices, the conversation at one point changed course. The president paused and offered a prediction. “I have a suspicion that the guns will turn,” he said, suggesting that many of the companies represented at the table held more personal data than any government on the planet. The time would come, he said, when the demands that we were making on the government would be made on the tech sector itself.

When Schrems quizzed him on the company’s obligations under European privacy law, the lawyer replied that the laws weren’t enforced. “He told us that ‘you can do whatever you want to do’ because the penalties in Europe are so trivial that the enforcement is nonexistent,” Schrems said. “Obviously, he didn’t know a European was in the room.”

The Safe Harbor principles were a fundamental pillar of the trans-Atlantic economy, but it was little known except by privacy experts. It was a creature of the EU’s 1995 privacy directive, which permitted Europeans’ personal information to move to other countries only if they had adequate privacy protection in place. Given the absence of a national privacy law in the United States, some political creativity was needed to keep data moving across the Atlantic.

“This isn’t over,” he said. “We’ll be talking about technology and privacy for the next hundred years. Just like we do with antitrust law more than a century after the Standard Oil case.”

The Americans stranded in the dial-up era aren’t confined to Ferry County. They are in every single state in the country. According to the FCC’s 2018 broadband report, more than twenty-four million Americans, more than nineteen million of whom live in rural communities, lacked access to fixed high-speed broadband.2 That’s roughly the population of New York state.

Broadband has become the electricity of the twenty-first century. It’s fundamental to the way people work, live, and learn. The future of medicine is telemedicine. The future of education is online education. And the future of agriculture is precision farming. Even with a future where there is more computing intelligence “at the edge”—meaning with ubiquitous small and powerful devices that process more data themselves—there still needs to be some high-speed access to the cloud. And that requires broadband.

The lack of job growth impacts every part of the local community. In hindsight, in November 2016, after the US presidential election, it should have come as no surprise that rural communities felt forgotten. For many in these areas, it seemed as if the nation’s economic prosperity had made a hard stop at the border of our urban and suburban counties.

A day with time divided between the two places provides the opportunity to understand a divided nation more clearly.

While mobile telecommunications technologies such as 4G LTE have given customers broadband-like speed through smartphones and other mobile devices, this technology is better suited for more densely populated areas. Satellite broadband can be the right solution in very sparsely populated areas, but it often suffers from high latency, lack of significant bandwidth, and high data costs.

If it’s possible to shift from fiber-optic cables to wireless technology for broadband, we can spread broadband coverage farther and faster and at a lower cost—not just in the United States, but around the world.

Many VHF and UHF channels currently go unused and can be devoted to other purposes. And with newly developed database technology, antennae, and end-point devices, we can harness this space by connecting a TV white spaces tower to a single fiber-optic cable and rely on these wireless signals to reach towns, homes, and farms more than ten miles away.

“Is it too much that in time it will be possible for anyone at any place to immediately communicate with anyone at any other place in the world?” Vail asked the crowd.21

Most people consider technology a product business. The industry’s products grab the public’s attention and shape the way we work and live. But in a world where today’s hits quickly become yesterday’s memories, a tech company is only as good as its next product. And its next product will only be as good as the people who make it. This means, in short, that technology is fundamentally a people business.

Known as I-Squared, the bill adopted the basic formula we had proposed while also addressing the critical shortage of green cards for certain key countries and making other overdue reforms. Most of its provisions made their way into the comprehensive immigration bill passed by the Senate in 2013, only to languish in the House of Representatives. When we discussed immigration at Trump Tower in December 2016, I raised the approach again. Most of the tech leaders were supportive, but the president-elect’s staff was clearly divided.

Success rarely comes to people who do nothing.

It’s difficult to build technology that serves the world without first building a team that reflects the diversity of the world. As they found, a more diverse group of researchers and engineers is more likely to recognize and think harder about bias problems that may even impact them personally. If AI imbues computers with the ability to learn from experience and make decisions, what type of experiences do we want them to have and what decisions are we comfortable having them make?

Artificial intelligence, like all information technology, is designed to be global in character. The technologists who create it want it to work the same way everywhere. But laws and regulations can diverge among countries, leading to challenges for governmental diplomats and technologists alike. We had experienced this divergence on a recurring basis, first with intellectual property laws, then with competition rules, and most recently with privacy regulations. But in some respects, these differences are simple compared to the potential complexity of laws that address ethical issues that fundamentally are grounded in philosophy.

More than fifteen years later, this approach to law enforcement happily seems far-fetched. But today, one aspect of Minority Report seems to be on track to arrive much earlier than 2054. As Cruise is on the run, he walks into the Gap. The retailer has technology that recognizes each entering customer and immediately starts displaying on a kiosk the images of clothes it believes the customer will like. Some people might find the offers attractive. Others might find them annoying or even creepy. In short, entering a store becomes a bit like we sometimes feel after browsing the web and then turning to our social media feed only to find new ads promoting what we just viewed.

A computer can now accomplish what almost all of us as human beings have done almost since birth—recognize people’s faces. For most of us, this probably began with the ability to recognize our mother. One of the joys of parenting comes when a toddler erupts enthusiastically when you return home. This reaction, which lasts until the onset of the teenage years, relies on the innate facial-recognition capabilities of human beings. While this is fundamental to our daily lives, we almost never pause to think about what makes it possible.

The world’s different tastes in technology were revealed when we brought XiaoIce to the United States in the spring of 2016. We launched her to the US market under the name Tay. The new name turned out to be just the start of our problems with XiaoIce’s American debut. I was on vacation when I made the mistake of looking at my phone during dinner. An email had just arrived from a Beverly Hills lawyer who introduced himself by telling me, “We represent Taylor Swift, on whose behalf this is directed to you.” That opening alone set the email apart from the rest of my inbox. He went on to state that “the name ‘Tay,’ as I’m sure you must know, is closely associated with our client.” No, I actually didn’t know, but the email nonetheless grabbed my attention. The lawyer went on to argue that the use of the name Tay created a false and misleading association between the popular singer and our chatbot, and that it violated federal and state laws. Our trademark lawyers took a different view, but we hadn’t sought to pick a fight with or even offend Taylor Swift. There were plenty of other names we could choose, and we quickly talked about finding a substitute.

Almost immediately, however, we had bigger issues to worry about. Tay, like XiaoIce, could be trained to interact with people based on feedback in conversations. A small group of American pranksters had organized an effective campaign using Tweets to train Tay to utter racist comments. In little more than a day we had to withdraw Tay from the market to address the problem, providing a lesson not just about cross-cultural norms but about the need for stronger AI safeguards.

As Nisbett had noted, people in the West tended to focus on a specific goal and believed that if you could pour yourself into advancing it, you could change the world around you. It was part of the entrepreneurialism that made Silicon Valley not just a location but an attitude that fueled innovation. “In China,” Professor He said, “we see everything moving in cycles. Like the signs of the zodiac, we believe that life is a circle and that everything will come back to its original point at some time in the future.” It led people in China to look backward as well as forward and to focus more on the whole picture rather than an individual piece.

As Nisbett had explained, the Pacific is indeed a wide ocean when it comes to how people on each side tend to look at the same image. Take a photograph of a tiger in the jungle. Americans are more likely to focus on the tiger and what it can do. The Chinese are more likely to focus instead on the jungle and the way it influences every aspect of the tiger’s life. Neither approach is wrong, and arguably a combination of the two could be most valuable. But the differences are clear.

If these differing philosophical lenses don’t make for enough complexity on their own, the cybersecurity issues of the past decade have added more challenges. The US government understandably reacted strongly not only to incidents such as the hacking of the OPM but also to reports that Chinese hardware manufacturer Huawei had built routers that enabled the Chinese government to monitor communications by customers who used them.18 The shoe then was on the other foot when the Snowden disclosures included a photo of US personnel tampering with Cisco routers to achieve the same thing.19 Both companies have been working since—with less than complete success—to recover their reputations in the other’s market.

From an international economic perspective, it’s worth remembering that, for the companies involved, this protection of home markets is a blessing that has its share of curses. Even for China, with its 1.4 billion people, more than 80 percent of the world’s consumers live and work somewhere else. The only way to succeed globally as a technology leader is to be respected globally. Both American and Chinese technology companies share a need to win over customers outside their borders when they’re seeking to grow in Europe, Latin America, or across the rest of Asia or elsewhere around the world. If the US and Chinese governments each allege that the other country’s homegrown technology can’t be trusted, there’s a risk that the rest of the world will conclude that both are right and turn toward other sources.

What’s the basis for this view? Mostly it comes down to the power of data. The argument is that the firm that gains the most users will gain the most data, and because data is rocket fuel for AI, its AI product will become stronger as a result. With a stronger AI product, the firm will attract even more users and hence more data. The cycle will continue with returns to scale, so that eventually this firm will crowd out everyone else in the market. According to Kai-Fu, “AI naturally gravitates toward monopolies … once a company has jumped out to an early lead, this kind of ongoing repeating cycle can turn that lead into an insurmountable barrier to entry for other firms.”

According to Kai-Fu, AI will benefit from a similar network effect on steroids, with AI leading to increased concentration of power in nearly every sector of the economy. The company in any sector that most effectively deploys AI will gain the most data about its customers and create the strongest feedback loop. In one scenario, the outcome could be even worse. Data could be locked up and processed by a few giant tech companies, while every other economic sector relies on these companies for their AI services. Over time, this would likely lead to an enormous transfer of economic wealth from other industrial sectors to these AI leaders. And if, as Kai-Fu projects, these companies are located mostly on the east coast of China and the west coast of the United States, then these two areas will benefit at every other region’s expense.

The Hutch has become like almost every institution and company in virtually every field on earth: Its future depends on data. As Hutch president Gary Gilliland has concluded, data is “going to transform cancer prevention, diagnosis and treatment.”7 He notes that researchers are turning data into a “fantastic new microscope” that shows “how our immune system responds to diseases like cancer.”8 As a result, the future of biomedical science is no longer in biology alone, but in its convergence with computer science and data science.

open source had revolutionized the creation and use of software. Increasingly software developers were publishing their code under a variety of open-source models that allowed others to incorporate, use, and contribute improvements to it. This enabled broad collaboration among developers that helped accelerate software innovation.

Studying these documents is a formidable challenge. Many are torn into fragments and scattered in libraries and museums around the world. The sheer volume and location of the material makes physically piecing them together next to impossible. With AI, Rustow’s team was able to comb through the digital fragments and match pieces stored thousands of miles apart, painting a previously incomplete picture of how Jews and Muslims coexisted in the middle ages.

In Africa, poaching is an ongoing issue that threatens to snuff out endangered species, including some of the world’s most iconic and recognized animals. Microsoft’s AI for Earth team is working with researchers at Carnegie Mellon University to help park rangers in the Uganda Wildlife Authority stay one step ahead of poachers. Using an algorithm to sift through fourteen years of historical national park patrol data, the Protection Assistant for Wildlife Security application, or PAWS, uses computational game theory to learn and predict poaching behavior, enabling authorities to proactively identify poaching hotspots and modify their patrols.

AI is unlike singular inventions from the past such as the automobile, the telephone, or even the personal computer. It behaves more like electricity in that it powers tools and devices that run almost every aspect of society and our lives. Like electricity, AI will run in the background and in many ways, we will forget it’s even there, until the day the power goes out.

We see these dynamics come into play in the political issues of our time. People argue about immigration, trade, and tax rates for wealthy individuals and corporations, but we seldom see politicians consider or the tech sector acknowledge the role that technology is playing in creating these challenges. It’s as if we’re all so absorbed in the resulting symptoms that we lack the time and energy to focus on some of the important underlying causes. Especially as the impact of technology continues to accelerate, it risks fostering a myopic understanding.

In many ways, a second challenge for governments is far more pronounced. Information technology and the companies that create it have gone global. The internet was designed to be a global network, and many of its benefits come from its connected nature. Perhaps more than any other technology in history, its influence and its geographical reach exceed any single government. This sets it apart from prior inventions such as the telephone, television, and electricity, which are based on networks or grids that typically correspond to national or state lines.

How can governments regulate a technology that is bigger than themselves? This is perhaps the single greatest conundrum confronting technology’s regulatory future. But once you ask the question, one part of the answer becomes clear: Governments will need to work together.

This means that more people live in democratic societies than at any time in history. But recently the world’s democracies have become less healthy. Perhaps more than that of any group of societies, their long-term well-being requires new collaboration to manage technology and its impact.