Category Archives: Artificial Intelligence

House of Lords Select Committee on Artificial Intelligence – Submission by Prof Toby Walsh.

Written Submission to
House of Lords Select Committee on Artificial Intelligence
Prof. Toby Walsh FAA, FAAAI, FEurAI.
1. Pace of technological change.
Recent advances in AI are being driven by four rapid changes: the doubling of processing power every two years (aka Moore’s Law), the doubling of data storage also every two years (aka Kryder’s Law), significant improvements is AI algorithms especially in the area of Machine Learning, and a doubling of funding into the field also roughly every two years. This has enabled significant progress to be made on a number of aspects of AI, especially in areas like image processing, speech recognition and machine translation. Nevertheless many barriers remain to building machines that match the breadth of human cognitive capabilities. A recent survey I conducted of hundreds of members of the public and as well as experts in the field ( reveals that experts are significantly more cautious about the challenges remaining.
2. Impact on society.
Education is likely the best tool to prepare the public for the changes that AI will bring to almost every aspects of our lives. An informed society is one that will best be able to make good choices so we all share the benefits. Life-long education will be the key to keeping ahead of the machines as many jobs start to be displaced by automation. Regarding the skills of the future, STEM is not the answer. The population does need to be computationally literate so the new technologies are not magic. But the most valued skills will be those that make us most human: skills like emotional and social intelligence, adaptability, and creativity.
3. Public perception.
The public’s perception is driven more by Hollywood than reality. This has focused attention on very distant threats (like the fear that the machines are about to take over) distracting concern about very real and immediate problems (like the fact that we’re already giving responsibility to stupid algorithms with potentially drastic consequences on society).
4. Industry.
The large technology companies look set to benefit most from the AI revolution. These tend to be winner-take-all markets, with immense network effects. We only need and want one search engine, one social network, one messaging app, one car-sharing service, etc. These companies can use their immense wealth and access to data to buy out or squash any startup looking to innovate. Like any industry that has become rather too powerful, big tech will need to be regulated more strongly by government so it remains competitive and acting in the public good. The technology industry can no longer be left to regulate itself. It creates markets which are immensely distorted. It is not possible to compete against companies like Uber because they don’t care if they lose money. Uber also often doesn’t care if it breaks the law. As to fears that regulation will stifle innovation, we only need look at the telecommunications industry in the US to see that regulation can result in much greater innovation as it permits competition. Competition is rapidly disappearing out of the technology industry as power becomes concentrated in the hands of a few natural monopolies who pay little tax and act in their own, supra-national interests. For example, wouldn’t it likely be a better, more open and competitive market place if we all owned our own social media and not Facebook?
5. Ethics.
There will be immense ethical consequences to handing over many of the decisions in our lives to machines, especially when these machines start to have the autonomy to act in our world (on the battlefield, on the roads, etc.). This promises to be a golden age for philosophy as we will be need to make very precise the ethical choices we make as a society, precisely enough that we can write computer code to execute these decisions. We do not know today how, for example, to build autonomous weapons that can behave ethically and follow international humanitarian law. The UK therefore should be supporting the 19 nations that have called for a pre-emptive ban on lethal autonomous weapons at the CCW in the UN. More generally, we will need to follow the lead being taken at EU on updating legislation to ensure we do not sacrifice rights like the right to avoid discrimination on the grounds of race, age, or sex to machines that cannot explain their decision making. Finally, just as we have strict controls in place to ensure money cannot be used to influence elections, we need strict controls in place to limit the already visible and corrosive effect of algorithms on political debate. Elections should be won by the best ideas and not the best algorithms.
6. Conclusions:
The UK is one of the birthplaces of AI. Alan Turing helped invent the computer and dreamt of how, by now, we would be talking of machines that think. The UK therefore has the opportunity and responsibility to take a lead in ensuring that AI improves all our lives. There are a number of actions needed today. The UK Government needs to reverse its position in the ongoing discussions around fully autonomous weapons, and support the introduction of regulation to control the use and proliferation of such weapons. Like any technology, AI and Robotics are morally neutral. It can be used for good or for bad. However, the market and existing rules cannot alone decide how AI and Robotics are used. Government has a vital responsibility to ensure the public good. This will require greater regulation of the natural monopolies developing in the technology sector to ensure competition, to ensure privacy and to ensure that all of society benefits from the technological changes underway.


Toby Walsh is Scientia Professor of AI at the University of New South Wales. He is a graduate of the University of Cambridge, and received his Masters and PhD from the Dept. of AI at the University of Edinburgh. He has been elected a Fellow of the Australian Academy of Science, the Association for the Advancement of Artificial Intelligence and the European Association for Artificial Intelligence. He is currently Guest Professor at TU Berlin. His latest book, “Android Dreams: The Past, Present, and Future of Artificial Intelligence” is published in the UK on 7 th September 2017. 5 September 2017

Will robots bring about the end of work? – Toby Walsh.

Hal Varian, chief economist at Google, has a simple way to predict the future. The future is simply what rich people have today. The rich have chauffeurs. In the future, we will have driverless cars that chauffeur us all around. The rich have private bankers. In the future, we will all have robo-bankers.

One thing that we imagine that the rich have today are lives of leisure. So will our future be one in which we too have lives of leisure, and the machines are taking the sweat? We will be able to spend our time on more important things than simply feeding and housing ourselves?

Let’s turn to another chief economist. Andy Haldane is chief economist at the Bank of England. In November 2015, he predicted that 15 million jobs in the UK, roughly half of all jobs, were under threat from automation. You’d hope he knew what he was talking about.

And he’s not the only one making dire predictions. Politicians. Bankers. Industrialists. They’re all saying a similar thing.

“We need urgently to face the challenge of automation, robotics that could make so much of contemporary work redundant”, Jeremy Corbyn at the Labour Party Conference in September 2017.

“World Bank data has predicted that the proportion of jobs threatened by automation in India is 69 percent, 77 percent in China and as high as 85 percent in Ethiopia”, according to World Bank president Jim Yong Kim in 2016.

It really does sound like we might be facing the end of work as we know it.

Many of these fears can be traced back to a 2013 study from the University of Oxford.This made a much quoted prediction that 47% of jobs in the US were under threat of automation in the next two decades. Other more recent and detailed studies have made similar dramatic predictions.

Now, there’s a lot to criticize in the Oxford study. From a technical perspective, some of report’s predictions are clearly wrong. The report gives a 94% probability that bicycle repair person will be automated in the next two decades. And, as someone trying to build that future, I can reassure any bicycle repair person that there is zero chance that we will automate even small parts of your job anytime soon. The truth of the matter is no one has any real idea of the number of jobs at risk.

Even if we have as many as 47% of jobs automated, this won’t translate into 47% unemployment. One reason is that we might just work a shorter week. That was the case in the Industrial Revolution. Before the Industrial Revolution, many worked 60 hours per week. After the Industrial Revolution, work reduced to around 40 hours per week. The same could happen with the unfolding AI Revolution.

Another reason that 47% automation won’t translate into 47% unemployment is that all technologies create new jobs as well as destroy them. That’s been the case in the past, and we have no reason to suppose that it won’t be the case in the future. There is, however, no fundamental law of economics that requires the same number of jobs to be created as destroyed. In the past, more jobs were created than destroyed but it doesn’t have to be so in the future.

In the Industrial Revolution, machines took over many of the physical tasks we used to do. But we humans were still left with all the cognitive tasks. This time, as machines start to take on many of the cognitive tasks too, there’s the worrying question: what is left for us humans?

Some of my colleagues suggest there will be plenty of new jobs like robot repair person. I am entirely unconvinced by such claims. The thousands of people who used to paint and weld in most of our car factories got replaced by only a couple of robot repair people.

No, the new jobs will have to be doing jobs where either humans excel or where we choose not to have machines. But here’s the contradiction. In fifty to hundred years time, machines will be super-human. So it’s hard to imagine of any job where humans will remain better than the machines. This means the only jobs left will be those where we prefer humans to do them.

The AI Revolution then will be about rediscovering the things that make us human. Technically, machines will have become amazing artists. They will be able to write music to rival Bach, and paintings to match Picasso. But we’ll still prefer works produced by human artists.

These works will speak to the human experience. We will appreciate a human artist who speaks about love because we have this in common. No machine will truly experience love like we do.

As well as the artistic, there will be a re-appreciation of the artisan. Indeed, we see the beginnings of this already in hipster culture. We will appreciate more and more those things made by the human hand. Mass-produced goods made by machine will become cheap. But items made by hand will be rare and increasingly valuable.

Finally as social animals, we will also increasingly appreciate and value social interactions with other humans. So the most important human traits will be our social and emotional intelligence, as well as our artistic and artisan skills. The irony is that our technological future will not be about technology but all about our humanity.


Toby Walsh is Professor of Artificial Intelligence at the University of New South Wales, in Sydney, Australia.

His new book, “Android Dreams: the past, present and future of Artificial Intelligence” was published in the UK by Hurst Publishers in September 2017.

The Guardian

Japanese company replaces office workers with artificial intelligence – Justin McCurry. 

A future in which human workers are replaced by machines is about to become a reality at an insurance firm in Japan, where more than 30 employees are being laid off and replaced with an artificial intelligence system that can calculate payouts to policyholders.

Fukoku Mutual Life Insurance believes it will increase productivity by 30% and see a return on its investment in less than two years. 

The system is based on IBM’s Watson Explorer, which, according to the tech firm, possesses “cognitive technology that can think like a human”, enabling it to “analyse and interpret all of your data, including unstructured text, images, audio and video”.

The technology will be able to read tens of thousands of medical certificates and factor in the length of hospital stays, medical histories and any surgical procedures before calculating payouts. 

The Guardian