Tag Archives: blue collar

The Robocalypse for Knowledge Jobs

Long-time Costa Rican National Champion Bernal Gonzalez told a very young me in 1994 that the world’s best chess-playing computer wasn’t quite strong enough to be among the top 100 players in the world.

Technology can advance exponentially, and just three years later world champion Garry Kasparov was defeated by IBM’s chess playing supercomputer Deep Blue. But chess is a game of logic where all potential moves are sharply defined and a powerful enough computer can simulate many moves ahead.

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Things got much more interesting in 2011, when IBM’s Jeopardy-playing computer Watson defeated Ken Jennings, who held the record of winning 74 Jeopardy matches in a row, and Brad Rutter, who has won the most money on the show. Winning at Jeopardy required Watson to understand clues in natural spoken language, learn from its own mistakes, buzz in and answer in natural language faster than the best Jeopardy-playing humans. According to IBM, ”more than 100 different techniques are used to analyze natural language, identify sources, find and generate hypotheses, find and score evidence and merge and rank hypotheses.” Now that’s impressive — and much more worrisome for those employed as knowledge workers.

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What do game-playing computers have to do with white collar, knowledge jobs? Well, Big Blue didn’t spend $1 billion developing Watson just to win a million bucks playing Jeopardy. It was a proof of concept and a marketing move. A computer that can understand and respond in natural language can be adapted to do things we currently use white collar, educated workers to do, starting with automating call centers and, sooner rather than later, moving on up to more complex, higher-level roles, just like we have seen with automation of blue collar jobs.

In the four years since its Jeopardy success, Watson has continued advancing and is now being used for legal research and to help hospitals provide better care. And Watson is just getting started. Up until very recently, the cost of using this type of technology was in the millions of dollars, making it unlikely that any but the largest companies could make the business case to replace knowledge jobs with AIs (artificial intelligence). In late 2013, IBM put Watson “on the cloud,” meaning that you can now rent Watson time without having to buy the very expensive servers.

Watson is cool but requires up-front programming of apps for very specific activities and, while incredibly smart, lacks any sort of emotional intelligence, making it uncomfortable for regular people to deal with it. In other words, even if you spent the millions of dollars to automate your call center with Watson, it wouldn’t be able to connect with your customer, because it has no sense of emotions. It would be like having Data answering your phones.

Then came Amelia…

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Amelia is an AI platform that aims to automate business processes that up until now had required educated human labor. She’s different from Watson in many ways that make her much better-suited to actually replace you at the office. According to IPsoft, Amelia aims at working alongside humans to “shoulder the burden of tedious, often laborious tasks.”

She doesn’t require expensive up-front programming to learn how to do a task and is hosted on the cloud, so there is no need to buy million-dollar servers. To train her, you literally feed her your entire set of employee training manuals, and she reads and digests them in a matter of a few seconds. Literally, just upload the text files, and she can grasp the implications and apply logic to make connections between the concepts. Once she has that, she can start working customer emails and phone calls and even recognize what she doesn’t know and search the Internet and the company’s intranet to find an answer. If she can’t find an answer, then she’ll transfer the customer to a human employee for help. You can even let her listen to any conversations she doesn’t handle herself, and she literally learns how to do the job from the existing staff, like a new employee would, except exponentially faster and with perfect memory. She also is fluent in 20 languages.

Like Watson, Amelia learns from every interaction and builds a mind-map that eventually is able to handle just about anything your staff handled before. Her most significant advantage is that Amelia has an emotional component to go with her super brains. She draws on research in the field of affective computing, “the study of the interaction between humans and computing systems capable of detecting and responding to the user’s emotional state.” Amelia can read your facial expressions, gestures, speech and even the rhythm of your keystrokes to understand your emotional state, and she can respond accordingly in a way that will make you feel better. Her EQ is modeled in a three-dimensional space of pleasure, arousal and dominance through a modeling system called PAD. If you’re starting to think this is mind-blowing, you are correct!

The magic is in the context. Instead of deciphering words like insurance jargon when a policyholder calls in to add a vehicle or change an address, IPsoft explains that Amelia will engage with the actual question asked. For example, Amelia would understand the same requests that are phrased different but essentially mean the same thing: “My address changed” and “I need to change my address.” Or, “I want to increase my BI limits” and “I need to increase my bodily injury limits”.

Amelia was unveiled in late 2014, after a secretive 16-year-long development process, and is now being tested in the real world at companies like Shell Oil, Accenture, NNT Group and Baker Hughes on a variety of tasks from overseeing a help desk to advising remote workers in the field.

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Chetan Dube, long-time CEO of IPSoft, Amelia’s creator, was interviewed by Entrepreneur magazine:

“A large part of your brain is shackled by the boredom and drudgery of everyday existence. […] But imagine if technology could come along and take care of all the mundane chores for you, and allow you to indulge in the forms of creative expression that only the human brain can indulge in. What a beautiful world we would be able to create around us.”

His vision sounds noble, but the reality is that most of the employees whose jobs get automated away by Watson, Amelia and their successors, won’t be able to make the move to higher-level, less mundane and less routine tasks. If you think about it, a big percentage of white collar workers have largely repetitive service type jobs. And even those of us in higher-level roles will eventually get automated out of the system; it’s a matter of time, and less time than you think.

I’m not saying that the technology can or should be stopped; that’s simply not realistic. I am saying that, as a society, there are some important conversations we need to start having about what we want things to look like in 10 to 20 years. If we don’t have those discussions, we are going to end up in a world with very high unemployment, where the very few people who hold large capital and those with the STEM skills to design and run the AIs will do very well, while the other 80-90% of us could potentially be unemployable. This is truly scary stuff, McKinsey predicts that by 2025 technology will take over tasks currently performed by hundreds of millions of knowledge workers. This is no longer science fiction.

As humans, our brains evolved to work linearly, and we have a hard time understanding and predicting change that happens exponentially. For example, merely 30 years ago, it was unimaginable that most people would walk around with a device in their pockets that could perform more sophisticated computing than computers at MIT in the 1950s. The huge improvement in power is a result of exponential growth of the kind explained by Moore’s law, which is the prediction that the number of transistors that fit on a chip will double every two years while the chip’s cost stays constant. There is every reason to believe that AI will see similar exponential growth. Just five years ago, the world’s top AI experts at MIT were confident that cars could never drive themselves, and now Google has proven them wrong. Things can advance unimaginably fast when growth becomes exponential.

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Some of the most brilliant minds of our times are sounding the alarm bells. Elon Musk said, “I think we should be very careful about AI. If I had to guess, our biggest existential threat is probably that we are summoning the demon.” Stephen Hawking warned, “The development of full-artificial intelligence could spell the end of the human race.”

4 Technologies That Are Changing Risk

This summarizes a session from RIMS that was headlined by Google Risk Manager Kelly Crowder as well as Google Global Safety Manager Erike Young. I served as the event host and moderator, teeing up the subject matter. We focused on four major areas of technology that are driving transformative change in the way we do things and, thus, changing risk. Disruptive technology, as the panel pointed out, forces risk managers and insurers to imagine and forecast how various advancements affect: safety; risk assessment; regulatory and legal parameters; and insurance implications.

Albert Einstein set the course for the future when he said: “The true sign of intelligence is not knowledge but imagination.” Ideas can reach beyond probable or practical restraints.

Google takes that notion to heart at Google X, a semi-secret lab located in Silicon Valley that aims via research and development to advance scientific knowledge and fuel discoveries that can change the world. “What if” abstract concepts, also known to Google as “moonshots,” are tireless experiments that often fail but that occasionally produce disruptive technology. The mantra is “fail fast, fail often, fail forward.” Learn and change. Sergey Brin, one of Google’s co-founders, and scientist Astro Teller (Captain of Moonshots) seek to improve existing technologies by a factor of 10. Google began with the self-driving car in 2010. Google X now includes a life sciences division involved in bionics.

As with the radical transportation shift to horseless carriages 130 years ago, the technologies are changing risk in profound ways, but the positive and negative impact of new technology can be hard to predict.

Starting with Botsourcing and Robotics, the panel highlighted the trend of companies to utilize robots and artificial intelligence for a wide array of service industries, manufacturers, medical providers and first responders, which seek safer, more efficient and cost-effective ways of serving clients or conducting business. While more dangerous occupational risks and blue-collar jobs are expected to be safer and more efficient, it remains uncertain whether the demand for labor will continue to grow as technology marches forward. Within 10 years, more than 40% of the workforce is expected to be affected by or replaced with robotics.

One positive sign noted in the presentation is that many American companies using robotics and 3D printing technologies, are transferring production facilities from overseas back to the U.S. and creating homeland jobs in the process. New job skills will become necessary to sustain broad-based prosperity. With respect to the highly advanced robots expected to integrate into society, the panel if their cognition will ever replace emotionally oriented skills. Will the warmth of human interaction remain a value in the future?

Another area of advancement is Surveillance and Wearable Biometrics. The Internet of Things represents the embedding of physical objects with sensors and connectivity. Devices like smart thermostats, as Google pointed out, are able to learn from our behavior patterns to anticipate our needs at home or work on a 24- hour basis. Our security and monitoring systems are tied to public safety, medical providers and our smartphones. Data collection is growing at an enormous pace, effectively tracking our every move. This, as pointed out, has created concern for privacy and for the increasing vulnerability to cyber threats.

Fixed and mobile surveillance cameras have facial identification technology. Unmanned aerial vehicles (UAV’s), also known as drones, can be preprogrammed to operate autonomously, although the panel pointed out that current FAA restrictions require an operator following visual line-of sight rules below 400 feet of altitude. It’s expected that, within the next few years, there will be autonomous drone surveillance and product delivery systems.

Utilities can use drones to monitor power transmission lines at 1/10th the cost of a helicopter and with safety and efficiency impossible with helicopters. Public safety departments can use UAVs to assess damages as well as risks. Four U.S. insurers are currently using human-operated drones to assess property damage claims arising from natural disasters. The panel showed photos of UAVs that look like insects that are the size of a fingertip.

Wearable biometrics are much more sophisticated than Apple watches and Fitbits. Google explained the company’s quest to improve health monitoring systems. With 9.3% of the U.S. population alone (29 million) suffering from diabetes, Google sells a revolutionary contact lens, developed with Novartis, that monitors glucose levels and corrects vision similar to an autofocus camera. Other panel photos show tattoo-like patches thinner than a human hair that stick to the skin. Using microfluidic construction, these nearly invisible patches monitor EKG and EEG bodily functions and transmit the data 24/7 wirelessly. Similar monitors, known as smarty pants, can be sewn into underclothes and bras.

Exoskeleton Technologies are being developed by more than a dozen major manufacturers, as the panel demonstrated, and their products are expanding human capacity and endurance far beyond most expectations. These are wearable machines that combine human intelligence and machine power to achieve nearly any conceivable task without falling. Used by the military, public safety, hazmat teams and industries and for medical rehabilitation, exoskeletons let humans perform feats that would have been physically impossible a few years ago. Neuro interfaces with bio-logical signals allow paraplegics to relearn lost functions. Some patients can actually experience running a four-minute mile or play certain sports. Lifting is painless and commonplace with weights of 40 to 60 pounds, with new technology allowing a person to run without falling down with 200 pounds of weight on their back. A la “Iron Man,” exoskeleton suits are being designed into wearable fabrics with micro energy packs.

This area of technology has the greatest potential of protecting workers from soft tissue strains and back injuries. In addition, it serves a dual purpose of advancing an injured worker’s rehabilitation and recovery process without the inherent risk of getting reinjured. As pointed out, experts expect industrial injuries to be reduced as much as 70% as exoskeleton technology is woven into the workplace as personal protective equipment (PPE). Perhaps a bigger question, with an aging workforce and population, is the unknown cost and whether employers, insurers or individuals will bear the expense.

The fourth and final technology covered by the panel was Autonomous Transportation Systems and Devices. Google pioneered self-driving vehicles and leads in the development of its associated technology, but autonomous vehicles are now being produced and tested by a growing number of manufacturers. In March 2015, Delphi sent a driverless Audi SUV on a 3,400-mile trip through 15 states from San Francisco to New York City in eight days without an accident. Auto manufacturers are approaching self-driving features on an incremental basis with self-braking, self-parking and other autonomous safety-related features. Google has inspired a jump to a fully autonomous vehicle with no steering wheel or brake. These self-driving vehicles perform 7,000 safety processes per second at high speeds with far safer results than any human driver.

The impact of self-driving vehicles, including trucks, is expected to be commonplace within 20 years or sooner. A recent national survey of drivers indicated 44% are looking forward to autonomous vehicles. Respondents cited safety as their first priority. Their second reason was their expectation that they would not be paying for car insurance, which averages $820 per licensed vehicle per year in the U.S. Statisticians expected a drastic reduction of injuries as well as reduced violations like DUI, speeding and running red lights. With 35,000 motor vehicle deaths each year in the U.S., increased safety coupled with increased freeway efficiencies of ultimately more than 10 fold are issues that will make this a disruptive technology that will seem long overdue.

As the Google risk management team pointed out, insurers don’t know how to react or respond to the inevitable switch to autonomous vehicles. Even on a road test basis, auto insurance underwriters are scratching their heads trying to assess the risk implications.

As the panel pointed out to the inquisitive audience during the Q&A session, it may be relatively simple to determine the impact of new technology from a measurable, scientific basis. But the big challenge for risk managers is imagining the implications these various technological advancements will have on our organizations, workforce and insurers. Auto insurers have at least $500 billion in annual premiums at stake in the U.S. alone. What will happen to that revenue when we shed our need to get behind the wheel every day?

Google also pointed out that each of the technological areas cover a wide range of regulatory implications. While they attempt to notify every conceivable regulatory entity as they develop and test new products, it’s clear that there often aren’t clear legal or regulatory guidelines in place. How will regulators be able to promulgate new rules, regulations and laws as these science fiction-like inventions come to reality?

As Dr. Seuss said so profoundly, “Think and Wonder. Wonder and Think.”

ITL and its 400-plus thought leaders are providing the kind of wisdom and insight we will need to help bring all the parties together to solve these challenges. We welcome you to the conversation.

RIMS 2015