Tag Archives: AI

Forget A.I. ‘Remote Intelligence’ Will Be Much More Disruptive

 

Getty Images, A remote surgeon on an InTouch robot at the European Institute of TeleSurgery. Strasbourg, France. Jan. 12, 2009.

Globalization can usefully be thought of as a form of arbitrage driven by the simple fact that some things are cheaper in one country than another. In today’s world, we have large international differences in wages and salaries. So far, it is quite difficult to arbitrage wage differences.

And widespread political resistance to mass migration means that low-wage workers are mostly stuck at home. But what if workers in poor nations could sell their labor in rich nations without leaving home? What if the services provided by labor could cross borders without the laborers?

Telerobotics is the technology that overcomes the current need for physical presence in many jobs. These are robots that are controlled not by artificial intelligence but by remote intelligence ― a faraway human operating the robot.

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Weaponized AI, digital espionage and other technology risks for 2017

A recent wave of high-profile cyber-attacks — with objectives ranging from disrupting critical infrastructure to influencing the US presidential election — has heightened attention around the need for stronger security and governance measures in the public domain. Technological advances have also facilitated a significant uplift in industrial espionage, which could grow further in an era of state-sponsored use of cyber technology. Meanwhile, the future weaponization of AI and robotics by rogue states or terrorists and the scope for hacking global satellite systems are also firmly on the radar of security specialists.

A padlock is displayed at the Alert Logic booth during the 2016 Black Hat cyber-security conference in Las Vegas, Nevada, U.S. August 3, 2016.

Image: REUTERS/David Becker

As businesses embrace innovation, they also take on new risks. Not only are companies buying and employing technology that creates new exposure, their IT systems are becoming increasingly connected to those of other companies in their value chain, such as suppliers, customers and utilities. Additionally, more IoT devices are being deployed to improve productivity or increase safety. This expanding interconnectedness, often facilitated by devices with limited security, creates additional points of vulnerability to cyber-attack and makes assessing the risk permutations that much more difficult.

Other innovations in the technology landscape, such as the migration of data and software to the Cloud and the use of AI and robotics in commercial applications, are also shifting the nature of cyber risk. At the same time, companies implementing innovations may be assuming, through legacy contracts, new liabilities where legal precedent is embryonic at best, along with vulnerabilities they will find challenging to mitigate or transfer into insurance markets.

Digital restrictions

Cross-border data flows are being slowed by a rise in government intervention. Some measures are aimed at consumer protection. For example, the European Union’s General Data Protection Regulation (GPDR) is driven primarily by privacy concerns on personal data. Other initiatives are aimed at state protection, driven by heightened security concerns. These measures enforce a range of protectionist policies, including prohibitive technical standards, censorship, surveillance and data localization. China, for instance, has joined Russia in tightening the requirements placed on foreign companies to store information within national borders. Increasing regulation is complicating the space for business to work in and aggravating “splinternet” tendencies.

These trends may present significant challenges for businesses. Compliance with new regulation could be costly, and failure to comply could result in significant sanctions. Restricted access to digital supply chains and markets will create complexities for firms with global operating models. In an era of heightened nationalism, this direction could threaten open global competition.

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The Three Breakthroughs That Have Finally Unleashed AI on the World

A few months ago I made the trek to the sylvan campus of the IBM research labs in Yorktown Heights, New York, to catch an early glimpse of the fast-arriving, long-overdue future of artificial intelligence. This was the home of Watson, the electronic genius that conquered Jeopardy! in 2011. The original Watson is still here—it’s about the size of a bedroom, with 10 upright, refrigerator-shaped machines forming the four walls. The tiny interior cavity gives technicians access to the jumble of wires and cables on the machines’ backs. It is surprisingly warm inside, as if the cluster were alive.

Today’s Watson is very different. It no longer exists solely within a wall of cabinets but is spread across a cloud of open-standard servers that run several hundred “instances” of the AI at once. Like all things cloudy, Watson is served to simultaneous customers anywhere in the world, who can access it using their phones, their desktops, or their own data servers. This kind of AI can be scaled up or down on demand. Because AI improves as people use it, Watson is always getting smarter; anything it learns in one instance can be immediately transferred to the others. And instead of one single program, it’s an aggregation of diverse software engines—its logic-deduction engine and its language-parsing engine might operate on different code, on different chips, in different locations—all cleverly integrated into a unified stream of intelligence.

Consumers can tap into that always-on intelligence directly, but also through third-party apps that harness the power of this AI cloud. Like many parents of a bright mind, IBM would like Watson to pursue a medical career, so it should come as no surprise that one of the apps under development is a medical-diagnosis tool. Most of the previous attempts to make a diagnostic AI have been pathetic failures, but Watson really works. When, in plain English, I give it the symptoms of a disease I once contracted in India, it gives me a list of hunches, ranked from most to least probable. The most likely cause, it declares, is Giardia—the correct answer. This expertise isn’t yet available to patients directly; IBM provides access to Watson’s intelligence to partners, helping them develop user-friendly interfaces for subscribing doctors and hospitals. “I believe something like Watson will soon be the world’s best diagnostician—whether machine or human,” says Alan Greene, chief medical officer of Scanadu, a startup that is building a diagnostic device inspired by the Star Trek medical tricorder and powered by a cloud AI. “At the rate AI technology is improving, a kid born today will rarely need to see a doctor to get a diagnosis by the time they are an adult.”

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