The robots are coming: better get used to it

Every society needs an enemy: something which threatens the fabric of the nation. Whether it’s the barbarians at the gates of Rome, Reds under the bed, or the job-destroying stocking frames attacked by the Luddites, every age has its own perceived existential threat. Ours is robots.

This world will not just survive the rise of the robots, but benefit from them greatly. It’s true that they will disrupt the workforce, but the apocalyptic forecasts of mass unemployment are simply hyperbole, more fitted to a Brothers Grimm tale than a rational discourse of the near future.

What society needs are facts, not scaremongering. However, facts about the future (excluding death and taxes), especially with the pace of change and the uncertainty in the world are difficult to come by.

So let’s start with Forrester’s prediction that by 2019, a quarter of all job tasks will be offloaded to software or robots. It seems alarming and is certainly headline grabbing, until you read further and find, in the same report, that these technologies will create a further 14 million jobs in the same period.

No-one denies that a world powered by automation and AI will look very different from today, and no doubt some existing jobs will go the way of ostlers, farriers and blacksmiths. At the same time, technology will create entirely new careers, many of which people can only guess at today.

People should be accepting of this inevitable rise of the machine, because, for all the capabilities of AI, machine learning, RPA and robots, no technology comes close to the ingenuity of even the most average human mind.

The problem is not that robots will steal our jobs in the future: it is that humans have been wasting their faculties on tedious tasks that are much better performed by artificial intelligence or software, such as rekeying data or answering routine queries.

It will also help with the UK ‘productivity gap’, that the country has been suffering from for several years. The UK has been at the forefront of offshoring, lots of that efficiency gained from labour arbitrage can instead be delivered by robots and managed locally; driving more flexibility, control and efficiencies.

Far from being a jobs thief, new technology will augment the workforce, freeing them from repetitive, mundane tasks and using their higher abilities on more meaningful activity.

Take chatbots and AI assistants. Already these are replacing the time-consuming task of scheduling meetings, creating schedules – even taking notes in meetings. This means that the “cognitive load” (not to mention the time) can be spent on more productive, creative, and valuable activity.

Businesses must adapt to the great changes that have just begun to take shape and embrace the opportunities that technology represents. Because, if history teaches us anything, it is the futility of trying to stem the tide of change.

Source: robots are coming: better get used to it


Bring on the Bots

Artificial intelligence is moving from science fiction to practical reality fast.

AI — technology that teaches machines to learn so they can perform cognitive tasks and interact with people — is suddenly accessible to many companies. Costs associated with the advanced computing and data-storage hardware behind AI are plummeting. A growing number of vendors also offer AI tools such as robotic processing automation that can be configured without the help of a rocket scientist.

So this is clearly an area more banks will need to pay attention to going forward.

Already some AI pioneers have emerged in the financial industry just over the past year: Bank of New York Mellon‘s use of robotic process automation in trade settlement and other back-office operations; Nasdaq‘s search for signs of market tampering with an assist from AI; UBS’ initiative to answer basic customer-service questions through Amazon’s virtual assistant, Alexa; and USAA‘s development of its own virtual assistant.

Most large banks are considering using AI wherever mundane or repetitive tasks could be offloaded to a computer fairly easily.

What It Can Do

Here are some examples of where AI could make the biggest difference.

Customer conversations. Chatbots, natural language processing and speech processing could all be used to improve social interactions. In addition to USAA, Bank of America, Capital One Financial, Barclays and BBVA are experimenting with AI-powered virtual assistants.

“The vision that excites me is the one where we have seamless interactions, where I’m interacting with people, with the bank, with systems in the bank, and at the end of the day what the bank is giving me is exactly what I want,” said Marco Bressan, chief data scientist at BBVA. “We shouldn’t have a fixed idea of what the customer wants. There are some customers that the less they see their banks the better, as long as their money is well taken care of. Other customers want to see their bank every day. We have to serve both. And communicating with each of those from an AI perspective is very different. One has to do with full automation, and the other has to do with a smart interface.”

Automated investment advice. AI is used to help investment advisers and robo-advisers make better recommendations to customers. Australia’s ANZ Group has been using IBM’s Watson in its wealth management division for three years. Watson can read and understand unstructured data found in contracts and other documents, comb through millions of data points in seconds, and learn how to draw conclusions from the data. It can assess a new customer’s financial situation more quickly and comprehensively than a human being, and it never forgets anything.

BlackRock uses AI to improve investment decision-making. The startup Kensho combines big data and machine-learning techniques to analyze how real-world events affect markets.

Faster, better underwriting. BBVA uses artificial intelligence to improve its risk scoring of small and midsize businesses. “We realized we could update data in real time and integrate it with what the risk analysts were doing to have a much deeper understanding of their own portfolio,” Bressan said.

Some online lenders use AI to speed up their process. The software can look at hundreds or thousands of attributes, such as personal financial data and transaction data, to determine creditworthiness in a split second. The system learns as it goes — when a lender gets payment information on loans, that information gets fed back into the system, so its knowledge evolves.

However, some people question whether AI programs can be trusted to make sound, unbiased lending decisions.

Streamlined operations. BNY Mellon, Deutsche Bank and others are using bots in their back offices to automate repetitive tasks like data lookups.

Assisted account opening. Account origination can be a slow, cumbersome process. Some banks are experimenting with robotically automating some elements, such as data verifications.

Fraud detection. Card issuers and payment processors like PayPal use AI to compare current card transactions to the user’s past behavior as well as to general profiles of fraud behavior. Human analysts teach the model to discern the difference between legal and fraudulent transactions.

General efficiency. “The financial industry is an enormous percentage of the GDP,” said Robin Hanson, an associate professor at George Mason University. “A lot of it is due to various regulations and rules about who has to do what and how. It’s entrenched in regulatory practices, and it’s really hard to innovate in finance because you run into some of these obstacles.”

For example, Hanson wanted to sell some books at a convention. To do so, he had to apply for a tax ID, pay a fee and cover $25 in sales taxes. That required him to go to his bank to get a cashier’s check, for which he had to pay a $5 transaction fee and postage. “That’s an enormously expensive, awkward process,” he said. “If we had an efficient financial system, that would cost pennies.”

Unintended Consequences

As AI is used to improve the speed and efficiency of tasks now performed by humans, there are potential unintended consequences. For one, people in lower-paying jobs in operations, branches, compliance and customer service are likely to lose those jobs.

“Bank executives say they’re going to take those people and put them into high-tech, high-pay jobs to help us code, help us do this, help us do that. It’s just not going to happen,” said Christine Duhaime, a lawyer in Canada with a practice in anti-money-laundering, counterterrorist financing and foreign asset recovery and the founder of the Digital Finance Institute. However, “the bank may end up with the same number of employees,” as it sheds customer-facing jobs and hires trained software developers to code.

There are also privacy concerns around the use of AI in financial services. “From a consumer protection point of view, there are concerns people need to take into account when it comes to AI, machine learning and algorithmic decision-making,” said Steve Ehrlich, an associate at Spitzberg Partners, a boutique corporate advisory and investment firm in New York. “Say a company wants to look at your social media or your search engine history to determine your creditworthiness. They go into Facebook and find a picture of you that you didn’t upload. It’s a picture of you at a bachelor party or gambling at a casino. That data gets fed into the algorithm. For one, they should tell you they were going to be taking that information.”

There is also the chance that bots and AI engines could run amok and make poor lending decisions, or commit an operations error that a human with common sense could have averted.

What Banks Can Do

These caveats aside, banks’ wisest course is to prepare to be part of the revolution.

One thing they can do is create an internal center of excellence where a group of people become experts and help bring AI to other parts of the company. They could test technology and use cases and guide the business units in their adoption of bots and AI. Citigroup and BBVA are among the banks doing this. BNY Mellon has a robotics process automation team that partners with businesses and has come up with eight pilots, including settlement and data reconciliation.

Banks also can try to encourage people to embrace AI — even if their jobs are at risk. It helps to communicate that there could be some benefit to them. “People in operations and data analysts don’t want to be doing this work anyway — swivel-chair work, mindless copying and pasting and keying in data,” said Adam Devine, head of marketing at WorkFusion, a robotics process automation software provider that competes with Blue Prism and Automation Anywhere.

David Weiss, senior analyst at Aite Group, also sees the trend as an eventual positive for employees. “I personally argue for human augmentation — go after the peak human problems first,” he said. “There, you’re not going to cut jobs, you’re just going to make people more functional, and leverage their inorganic intelligence more.”

But there’s no question the workplace will change and people will have to adapt.

Source: on the Bots

Why bots are poised to disrupt the enterprise

The proliferation of robots completing manual tasks traditionally done by humans suggests we have entered the machine automation age. And while nothing captures the imagination like self-directing machines shuttling merchandise around warehouses, most automation today comes courtesy of software bots that perform clerical tasks such as data entry.

Here’s the good news: Far from a frontal assault on cubicle inhabitants, these software agents 7may eventually net more jobs than they consume, as they pave the way for companies to create new knowledge domain and customer-facing positons for employees, analysts say.

The approach, known as robotic process automation (RPA), automates tasks that office workers would normally conduct with the assistance of a computer, says Deloitte LLP Managing Director David Schatsky, who recently published research on the topic. RPA’s potential will grow as it is combined with cognitive technologies to make bots more intelligent, ideally increasing their value to businesses. Globally, the RPA market will grow to $5 billion by 2020 from just $183 million in 2013, predicts Transparency Market Research.

Bots mimic activities a human would perform, including anything from populating electronic forms to changing data in a customer account. Some bots log into an application, extract information from a web page, modify it and enter it into another application. At AT&T, bots pull sales leads from multiple systems, enabling staff to spend more time with customers.

Rise of the machines yield greater productivity

Bot benefits include the capability to cut staffing costs, reduce error rates associated with humans and improve customer engagement. For example, Schatsky says a bank redesigned its claims process and deployed 85 or bots running 13 processes, handling 1.5 million requests per year. The bank added capacity equivalent to more than 200 full-time employees at approximately 30 percent of the cost of recruiting more staff.

Deloitte analysis
Man vs. Bot (Click for larger image.)

A major appeal of bots is that they are typically low-cost and easy to implement, requiring no custom software or deep systems integration. Schatsky says such characteristics are crucial as organizations pursue growth without adding significant expenditures or friction among workers. “Companies are trying to get some breathing room so they can serve their business better by automating the low-value tasks,” Schatsky says.

There’s little question that many workers will lose their jobs as companies automate more business processes. Forrester Research last November estimated that RPA software will threaten the livelihood of 230 million or more knowledge workers, or approximately 9 percent of the global workforce. However, RPA will create new jobs as workers train up and pivot to new roles within their companies.

RPA, along with physical, intelligent machines and other automation capabilities, will replace 16 percent of U.S. jobs but create the equivalent of 9 percent, yielding a net loss of 7 percent of jobs by 2025, says Craig Le Clair, a Forrester analyst who tracks the impact of automation technologies on the corporate sector. For instance, Wolters Kluwer reallocated money saved using RPA to close its books to hire a financial analysts to analyze profits, revenue, planning and forecasting.

Le Clair also says increased RPA will give rise to “cognitive sommeliers,” or staff who understand domains and curate knowledge bases for an application area. Moreover, as the glut of information increases, particularly in financial services, customers will need more human advice than ever before, Le Clair says.

Most bots stick strictly to their business logic rules but that is changing. If the machines can become smarter, the popular thinking goes, businesses will be able to use them in more complex operations. Paired with chatbots, natural language processing, machine learning and other tools, RPA can extract and structure information from audio, text, or images, as well as identify patterns and pass that information to the next step of the process.

Bots are already making a difference in how businesess interact with customer. At Vanguard Group, sophisticated algorithms called “roboadvisors” pair with humans to offer clients tailored investment advice.Virgin Trains has deployed cognitive RPA to automatically refund customers for late running trains. As customer emails arrive, a natural language processing tool gauges meaning and sentiment and then recognizes key information in the text to service the customer, reducing daily processing time and manual labor involved in dealing with customer emails by 85 percent. “Cognitive RPA has the potential to go beyond basic automation to deliver business outcomes such as greater customer satisfaction, lower churn, and increased revenues,” Schatsky says.

Change management and integration challenges loom

However, Schatsky cautions, cognitive RPA has been slow-going due to the complex nature of blending the technologies with existing systems, as well as the lack of required skills to implement them. To bridge that talent gap, IBM and Blue Prism have inked a joint agreement to work together on cognitive RPA.

Organizations piloting the most basic bots must clear change management, governance and security hurdles, says Forrester’s Le Clair. Implementing too many interdependent bots can wreak havoc on existing systems. Bots can also create turmoil when paired with workers who must learn to work with their new virtual colleagues.

Moreover, because most RPA tools reside on desktops, implementations in environments that are highly virtualized — where information from thousands of PCs resides on centralized servers — can be clumsy. “They have integration problems with more sophisticated VDI [virtual desktop infrastructure] implementations,” Le Clair says.

Schatsky says that CIOs should introduce RPA quickly in increments but scale it up slowly. “Start small and start fast,” Schatsky says. “If you see early success, you need to take a step back and start thinking more strategically about how you scale up in terms of governance and your staffing model.”


Source: bots are poised to disrupt the enterprise

Image Credit: Thinkstock

Taking the robot out of the human

What do Americans fear more than flying, germs, or animals? Computers replacing people in the workforce. The 2016 Chapman University Survey on American Fears found 16 percent of respondents were afraid or very afraid of losing jobs to technology. And the generation that’s grown up attached to a smartphone is even more concerned. An international 2016 Infosys survey of 16-to 25-year-olds found that 40 percent thought their current jobs could be replaced by some form of automation within a decade.

So just how worried should we be about being replaced by a robot?

Not very, according to Martin Fiore, Americas Tax Talent Leader for EY, the global professional services firm. Fiore believes we should look forward to working alongside robots, particularly young people starting their careers. EY is the number two hiring firm for U.S. college graduates.

“Robots can free workers from mundane tasks, allowing them to provide purpose and value at a higher level,” says Fiore. EY uses Robotic Process Automation (RPA) in its tax practice, which consists of bots, or software applications that handle repetitive, high-volume automated tasks.

“Our people used to have to spend hours cutting and pasting, pulling together disparate pieces of information, “ says Fiore. “Now they can start with that information and ask ‘What does it mean for our client?’ It’s a huge change.”

Using this type of automation allows EY workers to focus on interpreting data as they work alongside a bot, according to Fiore. He says the bots haven’t cost any jobs at EY.

“We’ve taken the robot out of the human, “ says Fiore, by eliminating mundane and repetitive tasks. He says this is especially important for millennials, who want to make a difference early in their careers and apply what they’ve learned in college more quickly.

This sounds great for an information worker who no longer has to slog through data, but what about other industries? Momentum Machines has developed a robot that creates 400 made-to-order hamburgers in an hour without any help from humans. A 2015 Ball State University report found that almost 88 percent of job losses in manufacturing in recent years could be attributed to enhanced productivity because of automation. Can we expect more jobs to disappear as robots become cheaper and smarter?

It depends on who you ask. A 2016 Oxford University report found that 47 percent of U.S. jobs are at risk of being lost to automation over the next two decades.

But a 2016 McKinsey Global Institute report concluded that fewer than five percent of careers can be completely automated using existing technology. However, the report found about half of work activities could potentially be done by a machine. Data collection and processing and predictable physical work are the activities most likely to be automated.

Perhaps the most likely scenario is that many of us will end up working alongside robotic technology, like EY’s tax practitioners, rather than being kicked to the curb by them. For example, Fiore says a robot could lay bricks while a human being directs its work.

Nearly two-thirds of Americans are already using a digital assistant or some form of robotic technology, according to Loop Intelligence. A Roomba cleaning the kitchen floor has become routine for many of us, frightening only the cat.

But even as we become more reliant on Siri and Alexa in our personal lives, accepting more automation at work won’t be easy. Companies that invest in robotic technology will have to work hard to manage the people side of change. Workers worried about losing their jobs may have to learn new skills. For example, Momentum Machines, the maker of the burger bot, posted a job ad for a “restaurant generalist” who can troubleshoot software—quite a different skill from what’s normally expected of fast food workers.

“If you look at what’s ahead, you’re either going to be disrupted, or get in front of the disruption,” says Fiore. He says the best way to prepare workers for robotic technology is to help them understand how it will benefit them—improving the quality of their work, reducing mundane tasks, and giving them the time to provide purpose and value at a higher level.

Source: the robot out of the human

The optimist’s guide to the robot apocalypse

Machines, you may have heard, are coming for all the jobs.

Robots flip burgers and work warehouses. Artificial intelligence handles insurance claims and basic bookkeeping, manages investment portfolios, does legal research, and performs basic HR tasks. Human labor doesn’t stand a chance against them—after the “automation apocalypse,” only those with spectacular abilities and the owners of the robots will thrive.

Or at least, that’s one plausible and completely valid theory. But before you start campaigning for a universal basic income and set up a bunker, you might want to also familiarize yourself with the competing theory: In the long run, we’re going to be just fine.

We’ve been here before

Our modern fear that robots will steal all the jobs fits a classic script. Nearly 500 years ago, Queen Elizabeth I cited the same fear when she denied an English inventor named William Lee a patent for an automated knitting contraption. “I have too much regard for the poor women and unprotected young maidens who obtain their daily bread by knitting to forward an invention which, by depriving them of employment, would reduce them to starvation,” she told Lee, according to one account of the incident. The lack of patent didn’t ultimately stop factories from adopting the machine.

Two hundred years later, Lee’s invention, still being vilified as a jobs killer, was among the machines destroyed by protestors during the Luddite movement in Britain. More than 100 hundred years after that, though computers had replaced knitting machines as the latest threat to jobs, the fear of technology’s impact on employment was the same. A group of high-profile economists warned President Lyndon Johnson of a “cybernation revolution” that would result in massive unemployment. Johnson’s labor secretary had recently commented that new machines had “skills equivalent to a high school diploma” (though then, and now, machines have trouble doing simple things like recognizing objects in photos or packing a box), and the economists were worried that machines would soon take over service industry jobs. Their recommendation: a universal basic income, in which the government pays everyone a low salary to put a floor on poverty.

Today’s version of this scenario isn’t much different. This time, we’re warned of the “Rise of Robots” and the “End of Work.” Thought leaders such as Elon Musk have once again turned to a universal basic income as a possible response.

But widespread unemployment due to technology has never materialized before. Why, argue the optimists, should this time be any different?

Automating a job can result in more of those jobs

Though Queen Elizabeth I had feared for jobs when she denied Lee’s patent, weaving technology ended up creating more jobs for weavers. By the end of the 19th century, there were four times as many factory weavers as there had been in 1830, according James Bessen, the author of Learning by Doing: The Real Connection between Innovation, Wages, and Wealth.

Each human could make more than 20 times the amount of cloth that she could have 100 years earlier. So how could more textile workers be needed?

According to the optimist’s viewpoint, a factory that saves money on labor through automation will either:

  1. Lower prices, which makes its products more appealing and creates an increased demand that may lead to the need for more workers.
  2. Generate more profit or pay higher wages. That may lead to increased investment or increased consumption, which can also lead to more production, and thus, more employment.

Amazon offers a more modern example of this phenomena. The company has over the last three years increased the number of robots working in its warehouses from 1,400 to 45,000. Over the same period, the rate at which it hires workers hasn’t changed.

The optimist’s take on this trend is that robots help Amazon keep prices low, which means people buy more stuff, which means the company needs more people to man its warehouses even though it needs fewer human hours of labor per package. Bruce Welty, the founder of a fulfillment company that ships more than $1 billion of ecommerce orders each year and another company called Locus Robotics that sells warehouse robots, says he thinks the threat to jobs from the latter is overblown—especially as the rise of ecommerce creates more demand for warehouse workers. His fulfillment company has 200 job openings at its warehouse.

A handful of modern studies have noted that there’s often a positive relationship between new technology and increasing employment—in manufacturing firms, across all sectors, and specifically in firms that adopted computers.

How automation impacts wages is a separate question. Warehouse jobs, for instance, have a reputation as grueling and low-paying. Will automation make them better or worse? In the case of the loom workers, wages went up when parts of their jobs became automated. According to Bessen, by the end of the 19th century, weavers at the famous Lowell factory earned more than twice what they earned per hour in 1830. That’s because a labor market had built up around the new skill (working the machines) and employers competed for skilled labor.

That, of course, is not the only option, but it is an outcome embraced by the optimist crowd. Similarly positive results of automation: If companies can make more money with the same number of workers, they can theoretically pay those workers better. If the price of goods drops, those workers can buy more without a raise.

As automation kills some jobs, it creates others

As the Industrial Revolution ended, about half of American workers were still employed in agriculture jobs, and almost all of those jobs were about to be lost to machines.

If nothing else had changed, the decrease in agriculture jobs could have led to a largely unemployed society. But that’s not what happened. Instead, as agricultural employment dwindled to less than 2% of American workers, jobs in other sectors grew during the same period. They involved working in factories, yes, but also working with computers, flying airplanes, and driving cargo across the country—occupations that weren’t feasible in 1900.

Today’s optimists believe that the latest automation technologies will create new jobs as well.

What kind of jobs, they really can’t say (this is where the optimism comes in handy). About a third of new jobs created in the United States over the past 25 years didn’t exist (or just barely existed) at the beginning of that period, and predicting what jobs might be created in the next 25 years is just guessing. In a report on artificial intelligence and the economy, the Obama White House suggested that automation might create jobs in supervising AI, repairing and maintaining new systems, and in reshaping infrastructure for developments like self-driving cars. But, the report’s authors note, “Predicting future job growth is extremely difficult, as it depends on technologies that do not exist today.”

Automation doesn’t necessarily make humans obsolete

In 2013, researchers at Oxford sparked fear of the robot revolution when they estimated that almost half of US occupations were likely to be automated. But three years later, McKinsey arrived at a very different number. After analyzing 830 occupations, it concluded that just 5% of them could be completely automated.

The two studies obviously counted differently. The Oxford researchers assessed the probability that occupations would be fully automated within a decade or two. But automation is more likely to replace part of a job than an entire job. When Amazon installs warehouse robots, they currently don’t replace full workers, but rather, the part of the job that involves fetching products from different shelves. Similarly, when my colleague used artificial intelligence to transcribe an interview, we didn’t fire him; he just worked on the other parts of his job. McKinsey’s researchers’ model didn’t attempt to sort jobs into “replaceable” and “not replaceable,” but rather to place them on a spectrum of automation potential.

Almost every occupation that McKinsey looked at had some aspect that could be automated. Even 25% of tasks inside of a CEO job, the analysis found, could be automated. But very few jobs could be entirely automated.

McKinsey’s conclusion was not that machines will take all of these jobs, but rather, “more occupations will change than will be automated away.” Our CEO, for example, won’t spend time analyzing reports if artificial intelligence can draw conclusions more efficiently, so he can spend more time coaching his team.

This part of the optimist’s theory argues that if humans aren’t bogged down by routine tasks, they will find something better to do. The weavers will learn the new job of operating the machines. My coworker will write more articles because he’s not transcribing interviews. The warehouse workers will each pack more boxes because they’re not running between shelves collecting each item to be packed.

“Any time in history we’ve seen automation occur, people don’t all of the sudden stop being creative and wanting to do interesting new things,” says Aaron Levie, the CEO of enterprise software company Box and an automation optimist. “We just don’t do a lot of the redundant, obsolete work.” He points to potential examples like automatically scheduled calendar appointments or automated research services. “Why won’t we make up that time with doing the next set of activities that we would have been doing?” he says. “What I think it does is make the world move faster.”

What might that look like? Sodexo’s CEO of corporate services, Sylvia Metayer, offers one example. She says the outsourcing company’s building maintenance crew has started using drones to survey roofs for maintenance needs in three locations. Before the drones arrived, a human climbed onto the roof to check things out. Now, that human stays on the ground, which is safer. “The service hasn’t changed, the clients still need someone to help maintain the roof,” she says. “If we do it with drones, the people who would have been going up on the roof have more value, talking with clients about what needs to be done.”

Examples also exist in back office automation. “From what we’ve actually seen on the ground, in real business operations, we’ve seen almost zero job loss,” says Alastair Bathgate, CEO of Blue Prism, a software company that helps automate tasks within customer service, accounting, and other jobs. One of his clients, a bank, trained the automation software to react when a customer overdrew an account by checking to see if there were a balance in another account that could be transferred to cover it. This was a process that had never been done by humans, because it would be too tedious and expensive. Another bank used the software to allow customer service representatives to direct customers who had a credit card stolen to an automated system that would input their information and close the account. What do they do now? “It allows them to take another call,” Bathgate says. On-hold time, not head count, went down.

We may need automation

As the birthrate in many countries declines, the share of the working age population will shrink. To maintain today’s GDP, those workers will each need to be more productive than workers today, and they’ll need to improve at a faster rate than they have in the past. Even if productivity continued to improve at the same rate that it has throughout the last 50 years—within which the computer and the internet both became mainstream tools—it wouldn’t be enough of an improvement to sustain GDP. Automation technology could be the answer. According to a McKinsey analysis, it could raise global productivity by as much as 0.8% to 1.4% annually—but only if humans keep working, as well.

Being an automation optimist doesn’t mean ignoring jobs lost to automation

The Industrial Revolution eventually led to an unprecedented high standard of living for ordinary workers.

But this prosperity didn’t immediately materialize. There was a period in which life inside of factories was miserable for the laboring class. It included paltry wages, terrible working conditions, and child labor.

Today, during what the World Economic Forum has dubbed the “fourth industrial revolution,” even optimists expect short-term labor displacement, wage depression, and, for some workers, pain. To take just one sector, the Obama White House estimated that nearly 3.1 million people could lose their job to the autonomous car. New jobs in other sectors could be created as these jobs disappear, but the people who are losing driving jobs won’t necessarily have the skills to fill the new ones. This is a big deal.

What separates the optimists from the pessimists is that they tend to believe that the economy as a whole will recover from this short-term adjustment period.

Pessimists argue that not everyone will benefit from this industrial revolution in the same way that the standard of living for ordinary workers rose after the last industrial revolution. Over the last two decades, most gains in productivity have gone to the owners of businesses rather than people who work for them. Global inequality has for the last several decades soared.

But there’s a lot of stuff going on outside of technological developments, argue the automation optimists, like the decline of unions, weakening of labor laws, tax laws that benefit rich people, and education policies that haven’t adapted to a changing world—these are policy problems, and we should fix them rather than blaming technology.

There is, however, one point that cannot be easily brushed aside. Pessimists point to the pace of innovation as a reason that, this time, advances in technology will impact jobs more brutally than they have in the past. “In the past, when you had disruption, the economy adjusted and jobs were created elsewhere,” says Ethan Pollack, an economist at the Aspen Institute’s Future of Work Initiative who says he wavers between optimism and pessimism on automation. “What happens if [in the near future], each period of disruption comes so quickly, that it never recovers?”

So who is right?

“There will be fewer and fewer jobs that a robot cannot do better,” Tesla and SpaceX CEO Elon Musk recently mused at the World Government Summit in Dubai, before suggesting that a universal basic income would be necessary. But even as he talked of the threat to jobs, he also spoke of positive impacts of automation technology. “With automation, there will come abundance,” he said. “Almost everything will get very cheap.”

The optimism camp tends to have similarly mixed feelings about automation’s impact. “AI can seem dystopian,” tweeted Box CEO Levie, “because it’s easier to describe existing jobs disappearing than to imagine industries that never existed appearing.” He doesn’t deny that automated technology will make some labor obsolete—he just focuses on the long-term, big-picture opportunity for potential benefits.

Both sides generally agree that there should be measures in place to reduce the impact of labor displacement from automation, like education programs for re-skilling workers who will lose their jobs. One side just tends to have a more darker view of what happens after that.

So which side is right? If history is any guide, both.

In the 1930s, economist John Maynard Keynes famously coined the term “technological unemployment.” Less famous is the argument he was making at the time. His case wasn’t that impending technology doomed society to prolonged massive unemployment, but rather that a reaction to new technology should neither assume the end of the world or refuse to recognize that world had changed. From his essay, Economic Possibilities For Our Grandchildren:

The prevailing world depression, the enormous anomaly of unemployment in a world full of wants, the disastrous mistakes we have made, blind us to what is going on under the surface to the true interpretation, of the trend of things. For I predict that both of the two opposed errors of pessimism which now make so much noise in the world will be proved wrong in our own time-the pessimism of the revolutionaries who think that things are so bad that nothing can save us but violent change, and the pessimism of the reactionaries who consider the balance of our economic and social life so precarious that we must risk no experiments.

The Obama White House, in a report about how automation may impact jobs, recommended responding to automation by investing in education; creating training programs for workers, like drivers, who will be displaced by automation technology; and strengthening the social safety net. Bill Gates has suggested that we tax robots’ productivity similar to how we tax humans’ income in order to finance retraining programs and jobs for which humans are well-suited, like care-taking. Others have suggested wage subsidies and direct government employment programs. These proposed solutions are not so dissimilar to those provided to President Johnson in 1964, which included “a massive program to build up our educational system” and “a major revision of our tax structure.”

Even so, little progress has been made since then in making the US more resilient to job displacement caused by automation. The cost of college education has never been higher. As a society, the US has not shown a commitment in building effective, equal-opportunity re-skilling programs. Inequality continues to increase. And the Trump Administration has so far focused on preventing companies from hiring people into manufacturing jobs overseas rather than preparing the economy for the impact of automation. This is an insufficient approach.

As MIT’s Erik Brynjolfsson and Andrew McAfee put it more recently than Keynes in their 2014 book about automation’s economic impact, The Second Machine Age: “Our generation has inherited more opportunities to transform the world than any other. That’s a cause for optimism, but only if we’re mindful of our choices.”

Source: Quartz-The optimist’s guide to the robot apocalypse

Why branch bankers shouldn’t fear bots

Many bank employees likely fear robots will replace them, but to U.S. Bank’s Dominic Venturo, some bots are just there to be their wingman.

Much of the talk about artificial intelligence in banking has been about how technology can replace some functions currently performed by humans. But AI could help human bankers do their jobs more effectively by giving them quicker access to relevant information than ever before.

“AI won’t totally replace, but rather augment, a human’s ability to do their job in a lot of ways,” said Venturo, the Minneapolis-based bank’s chief innovation officer.

U.S. Bank is one of a number of financial institutions experimenting with how AI and machine learning can transform the financial industry. This year the bank announced the formation of an artificial intelligence enterprise solutions unit, which sits inside its payments, virtual solutions and innovation group.

The bank has begun experimenting with how artificial intelligence can help bankers serve customers that have a question on a product or service that is “infrequently asked about,” Venturo said. If a customer walks into a branch to ask a banker about such a product, the banker may not immediately know the answer. The banker may need to call a different expert in another location or spend time looking up additional information. That makes for a not-so-great experience for the customer. But if AI can contain an encyclopedic knowledge of U.S. Bank’s entire suite of products and services, the banker can quickly pull up information in seconds, he said.

“Let’s say there’s potentially hundreds of products a banker can get asked about; AI can give them the ability to get at the right answer for any of them in a rapid way,” Venturo added. “It enables your banker to become almost superhumanly smart about every product or service you might offer.”

This is important, he said, because although artificial intelligence can automate many repetitive tasks, and customers are more comfortable using digital financial services, they still want to talk to a human for many financial needs, Venturo said.

“The reality is there are many individuals who still prefer to talk to humans, and AI can augment that experience,” Venturo said.

Further, if the branch-based banker now doesn’t have to call a centralized contact center expert for information, that expert has more time to work on something more complicated.

“Now those folks can spend their time on other issues that require a higher level of service,” Venturo said.

AI can help improve not only in-person interactions between banks and customers, but human-initiated digital experiences, said Mitch Siegel, head of strategy for the financial services practice at KPMG. A wealth manager could use artificial intelligence to analyze customer’s financial data and send a personalized, automated report daily or weekly, for instance. If that client then had a further question or wanted to talk about something more complicated, such as changing investment strategies, they could then pick up the phone or talk to the wealth manager in person, Siegel said.

“There’s an opportunity for applying AI to better service customers, and give them a more personalized experience without getting rid of the human touch,” he said.

AI can also make suggestions to help banks build loyalty with customers by suggesting products based on their behavior. AI might be able to detect retail customers who typically have money left in their checking account when their next paycheck arrives. In that case, the bot can notify the bank, which can then push a digital message to the customers asking if they would like the bank to automatically sweep the remaining money into a savings account when the next check arrives.

“That’s something that could really deepen a customer relationship and a suggestion the customer might really appreciate,” Siegel said. “Insights into the ways you spend money, how you pay bills or savings habits are usually appreciated. Lower-value needs like these, customers are generally comfortable doing digitally, and when the customer has a financial need they want to speak to a human, with, like, a mortgage,” they’re then more likely to come to that bank first, he said.

AI can also free up bank employees to act in a more consultative, advisory role, said Adam Devine, head of marketing for WorkFusion, which provides robotic process automation and artificial intelligence solutions to several industries, including banks.

One example is contact centers where about a quarter of the calls are about the same topics — basic questions about transactions.

“So much of it is rules-based and repetitive,” Devine said.

If chatbots then could be trained to automatically handle these common calls, that could free up contact center employees to focus on providing more valuable services, Devine said.

“It allows the customer service agents to provide more of an advisory and recommendation service based on nuance and conversation,” he added. “It becomes less about transactions and provides more revenue opportunity for banks.”

In general, Devine said bankers he has met with as clients or potential clients have pointed to AI projects as top priorities.

“Two to three years ago we’d walk in [to a bank] and talk about machine learning and AI and they’d look at us like we had five heads,” he explained. “Now they’re showing us PowerPoint presentations about how it’s part of their core strategy.” For many banks, “if it’s not on their 2017 road map, it’s on their 2018 road map,” he added.

Source: branch bankers shouldn’t fear bots

How bots will shape the future of work

Picture this. You are in an elevator and your watch starts vibrating and one swipe tells you that it’s an important alert from your bank. You are facing some issues with your banking transaction and you are connected to a chatbot (an intelligent robot at the bank’s contact centre) and over a series of messages, the bot meticulously addresses your problem. This indicates the onset of a digital era which is set to transform the way people work and interact in daily business activities.

Intelligent automation, software robotics, cognitive computing, augmented reality and machine learning have the potential to increase productivity, improve efficiency, and reduce time-to-market and reshape the manner in which people and enterprises function.

Many industry experts believe that the use of artificial intelligence (AI) will become pervasive across industries in the next decade. Machines with natural language processing skills will help to automate routine and repetitive tasks.

One of the world’s oldest and largest news gathering organizations is using AI to develop more than 4,000 corporate earnings stories.

Leading IT services companies have developed AI platforms to streamline different aspects of their project delivery. For instance, a tier-1 Indian IT services player plans to use its AI platform to automate application maintenance projects. This will help the company save up to $50 million and free around 3,000 engineers from routine software maintenance activities. A leading utility company is using AI in the area of financial reporting and accounting statement preparation.

The future of the workforce is poised to change dramatically. In the new wave of automation led by software robots, AI is also expected to redefine jobs which were previously considered immune to technological displacement such as white-collar work. For instance, algorithms are bringing deeper insights in the financial services space (high-frequency trading) and automation is making its presence felt in the healthcare segment by altering the manner in which healthcare services are being delivered (mobile health apps, robotic surgery and diagnosis by algorithms).

The technological advances will redefine the notion of what a “job” is and change the “eight-hours-a-day-work” paradigm. The workplace will become a hyper-connected network of people and machines and no longer be confined to traditional working hours or places.

However, the proverbial glass is half full. Previous experience has shown that automation has redefined what were then considered as traditional jobs and created new jobs in the manufacturing ecosystem.

Rather, the digital disruption brought about by automation is likely to create new companies and opportunities in hitherto unheard of economic activities. However, it is observed that a majority of the workforce is not adequately prepared to deal with these technology changes.

Both employees and enterprises will have to adapt, reinvent and upskill themselves to stay relevant.

As technology drives and reshapes business needs, enterprises will be required to revamp their learning and development programmes to re-skill their employees and enable them to take on tasks beyond the purview of bots and algorithms. Technical training needs to be oriented towards meeting the dynamic needs of the next-generation workforce. Furthermore, the next-generation workforce will have to take ownership to build their own ‘brand’ to take on jobs which match their new skill-sets.

At the same time, to attract the new-age digitally-connected workforce, companies will need to provide an entrepreneurial environment where employees can experiment innovative ideas. The changing nature of work will free up individuals to pursue other interests and has the potential to spur a new wave of entrepreneurship.

An important stakeholder in the journey to the next-generation workplace is the government, which can act both as a monitor and an enabler. Governments around the world will have an important role to play in the new paradigm as the employer-employee relationship evolves drastically.

Next-generation enterprises, whose businesses are based mainly on AI/automation, argue that existing regulations were designed for another era and are not in line with the demands of the industry. There is a need to re-examine existing regulations and develop new regulatory regimes which are designed for the future—nimble, real time and responsive to the needs of the work force.

Source: Livemint-How bots will shape the future of work

Beyond robo-compliance: How bots will soon permeate banking

Banks are already experimenting with robotic process automation in areas like their compliance functions. But robotics technology may soon find its way to nearly all aspects of running the bank.

As banks become more comfortable with the relying on software robots to replicate the actions of a human interacting with machines to handle rote tasks, experts say they will be quick to deploy the technology companywide as a way to trim expenses and redirect employees to more crucial tasks.

“I think we’re going to see it move from a few narrow functions to across the enterprise,” said Alan McIntyre, the industry managing director for banking at Accenture. “It’s going to become an indispensable technology for banks, rather than an interesting experiment.”

This could include areas in finance departments that are heavily manual, such as accruals and managing and clearing payments. Human resources and administrative functions is also an area where robotics can be deployed. For example, robots could take over payroll and managing employee incentive programs.

And even if robots don’t fully run these departments, they can be used to assist human employees during periods when workloads get large, said Alastair Bathgate, CEO and co-founder of Blue Prism, a robotic process automation firm, which has partnered with Accenture to help financial services and other industries implement robotics.

“When used to help with large or temporary workloads, [robotics] can reduce costs,” since additional temporary employees wouldn’t need to be hired for that period, he said.

Austria’s Raiffeisen Bank International AG is among the first to work with Accenture and Blue Prism to automate various business functions. Additionally, it is in the process of creating an in-house robotics center dedicated to experimenting with how the technology can be used in different functions at the bank.

The bank started out with four pilots implementing robotic process automation in tasks that had “low-to-medium complexity; rule-based processes with a logical order of steps, repetitive process patterns with clearly defined process options,” said Markus Stanek, head of group efficiency management at the bank.

With the center, Raiffeisen will experiment with how to implement robotics in in a whole host of banking functions.

“RPA allows us to introduce automation where expensive and heavy IT solutions do not pay off,” Stanek said. “RPA as a tool and as we understand it, is to be deployed like a surgical intervention, automating specific process steps…given the speed of implementation it should allow us to start thinking and implementing automation in a couple of weeks rather than months.”

Of course, the technology also has potential uses for consumer facing functions, not just back-office automation and staff efficiency. The most notable use thus far has been so-called robo-advisers, which use simple, rules-based models to choose investment vehicles for an investor after that person inputs basic information about their risk tolerance and investing goals. But beyond robo-advisers and even more complicated wealth management services, the technology can be used to enhance and improve customer relationship management for banks, said Mark Schwanhausser, director of omnichannel financial services at Javelin Strategy & Research.

Think of a human financial adviser, said Schwanhausser, after a major event that affects the stock market (such as Brexit). The adviser may have 30 clients to call who have questions about how this affects their portfolio, a major task for one person. But using robotics, the adviser could send a message tailored to each individual client telling them how the event affects their portfolio, along with a “click to call” button if they do want to talk to the adviser more in depth.

Similar ideas can be used to enhance personal budgeting and financial management tools for customers, Schwanhausser said. For example, when logging onto mobile banking, a customer can view personalized information on how they are doing achieving their financial goals with customized insights into spending and saving habits.

“Maybe [robotics] could even take your financial information and boil it into a useful infographic,” he said. “It can provide very personalized service that can be delivered without interacting with a human.”

But, like Accenture’s McIntyre, Schwanhausser believes this doesn’t mean the human element will be removed from banking, but rather deployed in smarter ways.

“It is a move to automation, but it’s a move to automation that complements the human element,” he said. “You may not want to talk to someone every time you have any financial question; [robotics] can provide you with a lot of daily information you wouldn’t have thought to ask for to begin with. If it just represents an interaction that never would have happened anyway, then it’s not a threat to any employee.”

Regardless of how it plays out, Schwanhausser said the move to using robotics in financial services has already passed the point of no return.

“What you are seeing now is the beginning stages of what is going to increasingly become the norm,” he said.

Source: robo-compliance: How bots will soon permeate banking

The Robot Work Revolution, How Most Jobs Will Change

The robot worker has arrived and many more are coming — impacting the stock boy and the chief executive officer in fashion.

The good news is that jobs aren’t expected to go away as much as they’re going to change, with human workers relying more on automation, according to a new report on the future of work from the McKinsey Global Institute.

Artificial intelligence and machine learning are all jumping ahead and have opened the door for continuing change.

“Automation now has the potential to change the daily work activities of everyone, from miners and landscape gardeners to commercial bankers, fashion designers, welders — and ceo’s,” McKinsey said.

“Almost half the activities people are paid almost $16 trillion in wages to do in the global economy have the potential to be automated by adapting currently demonstrated technology,” the report said.

While less than 5 percent of all occupations could be entirely given over to robots, the research found that a third of tasks that make up 60 percent of jobs could be handled by machines.

That could help companies do more, and better.

“At a time of lackluster productivity growth, this would give a needed boost to economic growth and prosperity and help offset the impact of a declining share of the working-age population in many countries,” McKinsey said.

That’s the utopian vision, more “Star Trek” than “Terminator,” but it would be a tricky feat for companies and policy makers to make the transition in the generations ahead.

McKinsey said the tasks that are most susceptible to automation are “physical activities in highly structured and predictable environments, as well as the collection and processing of data.”

All of that should be ringing bells for retailers.

Such tasks make up 51 percent of the U.S. work life, accounting for almost $2.7 trillion in wages, and are centered in manufacturing, accommodation and food service, and retail trade.

Many tasks in the retail trade could be automated, according to the report, which pointed to work in a predictable physical environment and the collection and processing of data.

That doesn’t necessarily mean that Apple’s Siri, Amazon’s Alexa or the Google Assistant will be bucking for employee of the month at Macy’s Inc. anytime soon. Other key attributes in retail don’t lend themselves to robots, including management and interfacing with people.

All told, half of today’s work activities could be automated by 2055, the report said. That’s a shift in the labor force that would rival the move away from an agricultural-based economy and one that was based on manufacturing — a sector President Trump is talking about trying to bring back.

Agricultural and manufacturing jobs that were lost in those massive changes were replaced by other jobs that didn’t exist earlier. (That doesn’t mean that the march of progress includes everyone, with some workers leaving the factory finding themselves working at fast-food joints or nowhere at all).

“We cannot definitively say whether historical precedent will be upheld this time,” McKinsey said. “But our analysis shows that humans will still be needed in the workforce: the total productivity gains we estimate will come about only if people work alongside machines.”

As long as machines want them to.

Source: -The Robot Work Revolution, How Most Jobs Will Change

Hilton hotel chain powers robot concierge with IBM Watson

The Hilton Worldwide hotel chain is trialling a robotic concierge service – powered by IBM’s Watson cognitive computing technology – to assist front desk staff in its hotels.

Named after its founder Conrad Hilton, “Connie” – who is being tested out at a hotel McLean, Virginia, near Washington DC – uses domain knowledge from Watson and WayBlazer, a cognitive travel recommendation engine, to provide guests with information on tourist attractions, local restaurants and hotel amenities.

“We’re focused on re-imagining the entire travel experience to make it smarter, easier and more enjoyable for guests,” said Jonathan Wilson, vice-president of product innovation and brand services at Hilton Worldwide.

“By tapping into innovative partners like IBM Watson, we’re wowing our guests in the most unpredictable ways.”

Connie will work alongside Hilton staff to assist with guest requests and personalise guests’ stay. The robot uses a number of Watson application programming interfaces (APIs) – including dialogue, speech-to-text, text-to-speech and natural language classification – to greet arrivals and answer their questions by tapping into WayBlazer’s database of travel domain knowledge.

Hilton hopes Connie will be able to learn, adapt and improve its recommendations over time as more guests interact with it. Staff, meanwhile, will be able to access a log of what guests ask it, and the answers they receive, to help them improve the service they provide.

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Robots promote brand loyalty

Rob High, vice-president and CTO of IBM Watson, said the test represented an important shift in human-machine interaction.

“Watson helps Connie understand and respond naturally to the needs and interests of Hilton’s guests – which is an experience that’s particularly powerful in a hospitality setting, where it can lead to deeper guest engagement,” he said.

WayBlazer CEO Felix Laboy added: “We believe providing personalised and relevant insights and recommendations – specifically through a new form factor such as a robot – can transform brand engagement and loyalty at the Hilton.”

Hilton has been testing out a number of other digital innovations in recent years to enhance its guest experience, including digital check-in services and keys, and partnerships with taxi service Uber.

Source: hotel chain powers robot concierge with IBM Watson