Monthly Archives: June 2017

This kind of A.I. is spreading to thousands of domains (not just loans), and as it does, it will eliminate many jobs. Bank tellers, customer service representatives, telemarketers, stock and bond traders, even paralegals and radiologists will gradually be replaced by such software. Over time this technology will come to control semiautonomous and autonomous hardware like self-driving cars and robots, displacing factory workers, construction workers, drivers, delivery workers and many others.

Unlike the Industrial Revolution and the computer revolution, the A.I. revolution is not taking certain jobs (artisans, personal assistants who use paper and typewriters) and replacing them with other jobs (assembly-line workers, personal assistants conversant with computers). Instead, it is poised to bring about a wide-scale decimation of jobs mostly lower-paying jobs, but some higher-paying ones, too.

This transformation will result in enormous profits for the companies that develop A.I., as well as for the companies that adopt it. Imagine how much money a company like Uber would make if it used only robot drivers. Imagine the profits if Apple could manufacture its products without human labor. Imagine the gains to a loan company that could issue 30 million loans a year with virtually no human involvement. (As it happens, my venture capital firm has invested in just such a loan company.)

We are thus facing two developments that do not sit easily together: enormous wealth concentrated in relatively few hands and enormous numbers of people out of work. What is to be done?

Part of the answer will involve educating or retraining people in tasks A.I. tools arent good at. Artificial intelligence is poorly suited for jobs involving creativity, planning and cross-domain thinking for example, the work of a trial lawyer. But these skills are typically required by high-paying jobs that may be hard to retrain displaced workers to do. More promising are lower-paying jobs involving the people skills that A.I. lacks: social workers, bartenders, concierges professions requiring nuanced human interaction. But here, too, there is a problem: How many bartenders does a society really need?

The solution to the problem of mass unemployment, I suspect, will involve service jobs of love. These are jobs that A.I. cannot do, that society needs and that give people a sense of purpose. Examples include accompanying an older person to visit a doctor, mentoring at an orphanage and serving as a sponsor at Alcoholics Anonymous or, potentially soon, Virtual Reality Anonymous (for those addicted to their parallel lives in computer-generated simulations). The volunteer service jobs of today, in other words, may turn into the real jobs of the future.

Other volunteer jobs may be higher-paying and professional, such as compassionate medical service providers who serve as the human interface for A.I. programs that diagnose cancer. In all cases, people will be able to choose to work fewer hours than they do now.

Who will pay for these jobs? Here is where the enormous wealth concentrated in relatively few hands comes in. It strikes me as unavoidable that large chunks of the money created by A.I. will have to be transferred to those whose jobs have been displaced. This seems feasible only through Keynesian policies of increased government spending, presumably raised through taxation on wealthy companies.

As for what form that social welfare would take, I would argue for a conditional universal basic income: welfare offered to those who have a financial need, on the condition they either show an effort to receive training that would make them employable or commit to a certain number of hours of service of love voluntarism.

To fund this, tax rates will have to be high. The government will not only have to subsidize most peoples lives and work; it will also have to compensate for the loss of individual tax revenue previously collected from employed individuals.

This leads to the final and perhaps most consequential challenge of A.I. The Keynesian approach I have sketched out may be feasible in the United States and China, which will have enough successful A.I. businesses to fund welfare initiatives via taxes. But what about other countries?

They face two insurmountable problems. First, most of the money being made from artificial intelligence will go to the United States and China. A.I. is an industry in which strength begets strength: The more data you have, the better your product; the better your product, the more data you can collect; the more data you can collect, the more talent you can attract; the more talent you can attract, the better your product. Its a virtuous circle, and the United States and China have already amassed the talent, market share and data to set it in motion.

For example, the Chinese speech-recognition company iFlytek and several Chinese face-recognition companies such as Megvii and SenseTime have become industry leaders, as measured by market capitalization. The United States is spearheading the development of autonomous vehicles, led by companies like Google, Tesla and Uber. As for the consumer internet market, seven American or Chinese companies Google, Facebook, Microsoft, Amazon, Baidu, Alibaba and Tencent are making extensive use of A.I. and expanding operations to other countries, essentially owning those A.I. markets. It seems American businesses will dominate in developed markets and some developing markets, while Chinese companies will win in most developing markets.

The other challenge for many countries that are not China or the United States is that their populations are increasing, especially in the developing world. While a large, growing population can be an economic asset (as in China and India in recent decades), in the age of A.I. it will be an economic liability because it will comprise mostly displaced workers, not productive ones.

So if most countries will not be able to tax ultra-profitable A.I. companies to subsidize their workers, what options will they have? I foresee only one: Unless they wish to plunge their people into poverty, they will be forced to negotiate with whichever country supplies most of their A.I. software China or the United States to essentially become that countrys economic dependent, taking in welfare subsidies in exchange for letting the parent nations A.I. companies continue to profit from the dependent countrys users. Such economic arrangements would reshape todays geopolitical alliances.

One way or another, we are going to have to start thinking about how to minimize the looming A.I.-fueled gap between the haves and the have-nots, both within and between nations. Or to put the matter more optimistically: A.I. is presenting us with an opportunity to rethink economic inequality on a global scale. These challenges are too far-ranging in their effects for any nation to isolate itself from the rest of the world.

Kai-Fu Lee is the chairman and chief executive of Sinovation Ventures, a venture capital firm, and the president of its Artificial Intelligence Institute.

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A version of this op-ed appears in print on June 25, 2017, on Page SR4 of the New York edition with the headline: The Real Threat of Artificial Intelligence.

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The Real Threat of Artificial Intelligence - New York Times

Peter Wallqvist: "It's a good trend that governments are brave enough to pull the trigger on things like this"

Phil Fisk. Set Design: Vicky Lees

The Serious Fraud Office (SFO) had a problem. Its investigation into corruption at Rolls-Royce was inching towards a conclusion, but four years of digging had produced 30 million documents. These needed to be sorted into "privileged" and "non-privileged", a legal requirement that involves paying junior barristers to do months of repetitive paperwork. "We needed a way that was faster," says Ben Denison, chief technology officer at the SFO. So, in January 2016, he started working with RAVN.

Pronounced "Raven", the London startup builds robots that sift and sort data, not only neatly presented material, but also unstructured documents. "Where someone has scanned 300 pages, it's not uncommon to put one page in upside down," says co-founder Peter Wallqvist. "We need to deal with that real world of messy datasets."

The two teams started to feed material from the Rolls-Royce case into the AI. By July they had a viable system, and with the agreement of lawyers on both sides, they set the robot to work. The barristers were wading through 3,000 documents a day. RAVN processed 600,000 daily, at a cost of 50,000 - with fewer errors than the lawyers. "It cut out 80 per cent of the work," says Denison. "It also saved us a lot of money." For Rolls-Royce, it had the opposite effect. In January 2017, the engineering company admitted to "vast, endemic" bribery and paid a 671 million fine. "It's hard to imagine a better outcome," says Wallqvist.

RAVN's co-founders - Jan Van Hoecke, Simon Pecovnik, Sjoerd Smeets and Wallqvist - met at Autonomy, the UK's first unicorn, where they worked on early versions of AI-powered database management. In 2010, the four left to launch RAVN. The self-funded firm now has 51 employees, revenues of 3 million and around 70 clients, mainly city law firms. BT, which signed a "very significant" deal, credits RAVN with annual savings of 100 million, due to automated checks that ensure contracts' accuracy.

Plus, of course, there's the SFO, which is using RAVN in increasingly clever ways. That means allowing it to make subjective judgements, including pointing investigators to data it thinks is relevant to a case. "This is potentially very valuable," says Denison.

Wallqvist believes the system can go even further and make not just assessments, but predictions. For example, by suggesting likely outcomes of mergers and acquisitions. "We've gone to the level of figuring out and structuring data," says Wallqvist. "Now we have the ability to surface that record of the past to predict the future." Today, Watson. Tomorrow, Holmes.

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Artificial intelligence is entering the justice system - Wired.co.uk

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Why it matters to you

AI promises to transform the world. Companies like this one will pave the way.

Hes been called one of the foremost thinkers on the topic of artificial intelligence, so its no surprise that Andrew Ng the cofounder of Coursera, the lead developer ofStanford Universitys main Massive Open Online Course (MOOC) platform, and the founder of the Google Brain project is starting another AI company of his own now that hes left Baidu. The resume of this impressive entrepreneur reads like a laundry list of some of the most impressive achievements in AI technology, and it seems safe to assume that Ngs newest venture, known only as deeplearning.ai, wont disappoint.

While Ng has founded and led many of his own projects in the past, he was most recently attached to another behemoth of a company Chinese web giant Baidu. There, Ng was chief scientist and headed the companys (what else) Artificial Intelligence Group, turning the Beijing-based giant into one of only a handful of companies in the world with expertise in each of the major AI categories: speech,natural language processing, computer vision, machine learning, and knowledge graph. Ngs team was also responsible for bringing two new business groups into the company autonomous driving and the DuerOS Conversational Computing platform.

Three months ago, Ng announced his departure from the company, noting in aMedium post, Baidus AI is incredibly strong, and the team is stacked up and down with talent; I am confident AI at Baidu will continue to flourish. After Baidu, I am excited to continue working toward the AI transformation of our society and the use of AI to make life better for everyone.

At the time, he told Forbes that his future plans were still in flux: I am looking into quite a few ideas in parallel, and exploring new AI businesses that I can build. One thing that excites me is finding ways to support the global AI community so that people everywhere can access the knowledge and tools that they need to make AI transformations.

And that may just be what deeplearning.ai is all about. In his Twitter announcement, Ng said only that he hoped the company would help many of you, and promised more announcements soon. Until then, well wait with bated breath.

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Artificial intelligence genius Andrew Ng has another AI project in the works - Digital Trends

Intelligent machines are taking over thousands of jobs, and being qualified is no longer enough to keep your job. Earlier this year, consulting firm McKinsey and Co. released a study that said 51% of all jobs could be automated in the next 20 years. Even specialized professions like medicine, law and banking are feeling the heat of Artificial Intelligence (AI). A few months ago, investment bank JP Morgan made the news by introducing intelligent machines to review financial deals that once kept employees busy for thousands of hours. Diagnostics and other decision-making skills previously thought of as the exclusive preserve of human beings, will soon be better handled by machines.

But Garry Kasparov has a different take on the issue. On 11 May 1997, Russian chess grandmaster Kasparov became the first world champion to be defeated by a machine. Yet in his new book Deep Thinking: Where Artificial Intelligence Ends And Human Creativity Begins, he is optimistic about the future of people with skills even as he concedes the inevitability of intelligent machines becoming more prominent. The sensation of being challenged, surpassed and possibly replaced by automaton, or an invisible algorithm, is becoming a standard part of our society, he writes. So while smarter computers are one key to success, doing a smarter job of humans and machines working together is far more important.

Is it possible to beat this threat of being displaced? Theres ample research and books on the subject, and here are some of the things they suggest you could do to robot-proof your career.

Build empathy

Employers want people who are empathetic and collaborative, who can guide relationships and work in teams. Because empathy is something that even intelligent machines are incapable of. Recognizing the importance of this skill is Geoff Colvin in his book Humans Are Underrated : What High Achievers Know That Brilliant Machines Never Will. The critical 21st century skill is empathy: we empathize to survive, he says, pointing to the healthcare profession. So while machines may be superior with diagnostics, a patient still needs to have a conversation with an expert. An empathetic doctor can help the patient deal with his condition better and recover faster. This, in turn, leads to lower healthcare costs and fewer lawsuits, says Colvin.

Empathy is a skill that can be developed through learning how to study the thoughts and feelings of others, and then responding appropriately. This involves inviting people to speak about their worries and concerns, hearing them out and then reassuring them, says Colvin.

Be a good communicator

A skill like communication is less easy to automate, says Anu Madgavkar, partner with McKinsey Global Institute, the research arm of McKinsey and Co., Mumbai. Intelligent machines cannot communicate the way human beings do. So people with better communication skills will be harder to replace with AI. The bigger message for professionals is that they should learn to communicate in a more compelling way, learn to work in teams, to excel at social interactions, says Madgavkar.

Become a lifelong learner

Previously in history, even in the 20th century, life was divided into two main parts: in the first part, you mostly learned, acquired knowledge and skills, and built yourself a personal and a professional identity. In the second part, you mostly made use of those skills and those identities. The pace of change in the 21st century will be such that most of what you learn as a teenager will be completely irrelevant by the time youre 40, says Yuval Noah Harari, author of Homo Deus: A Brief History Of Tomorrow, in a February interview with Time magazine, where he emphasized the necessity of life-long learning.

The good news is that anytime, anywhere learning is a reality now. For instance, if you want to do a project on design thinking, you can go immediately to the massive open online courses at online platforms like edX and Coursera and do a course on it, says Vijay Thadani, co-founder, NIIT.

Get those number skills

Digital literacy should be taken as seriously as language literacy, says Infosys chief executive Vishal Sikka, in an Infosys commissioned study on how to amplify human potential. The most important academic subjects that decision-makers see as focus areas for future generations are computer sciences, business and management and mathematics, says the study, which looked at the skills professionals need to acquire to integrate AI in a positive way into organizations and society.

Be constructive

Many perceive AI as a threat. Prominent among them are entrepreneur Elon Musk (our biggest existential threat) and scientist Stephen Hawking (the development of full AI could spell the end of the human race). From elevator operators to bank tellers and airplane pilots, history is full of examples of how technology has made jobs redundant.

But technology has also made life safer, easier and better. Its better to accept AI as a part of development, and look at the avenues it opens up rather than see the situation as man versus machine, says Kasparov.

Start to look at tasks hard to mechanizeanything that involves human creative energy, from photography and theatre, to baking, art, running, cooking classes, teachinganything thats not linear, says Mumbai-based Gurprriet Siingh, senior client partner at consulting firm Korn Ferry Hay Group. He says skills like empathy, creativity, flexibility and the ability to communicate can never be automated, and so education today should emphasize development of those skills.

Many of the most promising jobs today didnt even exist 20 years ago, says Kasparov, pointing to the demand for talent in new professions like app designers, 3D print engineers, drone pilots, social media managers and genetic counsellors. This is a trend that will accelerate as technology continues to create different professions .

Learn to work with machines

The future of increased productivity and business success isnt men or machines. Its both, argue Thomas H. Davenport and Julia Kirby in their book Only Humans Need Apply. Augment your skills, learn to work with machines, they say. The doctor who relies on diagnostic software, the lawyer who relies on research machines, the logistics manager who works with drones or the customer service manager who works with a chatbot, all of these professionals will be able to work better by complementing their human skills of empathy, of communication and creativity with machine intelligence. As the McKinsey report states, Humans will still be needed in the workforce; the total productivity gains we estimate will only come if people work alongside machines.

At wealth management firm ORO Wealth, for instance, the role of human portfolio advisers who work with intelligent machines is important. Even though the investment recommendations are machine-based, we need humans beings to work alongside. Because only a human adviser can empathize, can sense hesitation or lack of enthusiasm for a particular investment on the clients part. In which case they will go back to the machine-based algorithm, which will recommend alternative products, says Mumbai-based Vijay Kuppa, co-founder of ORO Wealth.

The skill and flexibility to work with a machine will help the workforce to become more productive. As Kasparov puts it, Smart machines will free us all...taking over the more menial aspects of cognition and elevating our mental lives towards creativity, curiosity, beauty and joy. These are what truly make us human, not any particular activity or skill like swinging a hammeror even playing chess.

First Published: Sun, Jun 25 2017. 03 47 PM IST

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Artificial Intelligence-proof your career - Livemint