PwC asks: Will robots steal our jobs?

PwC logo

PwC has released a report (here) called “Will robots steal our jobs?” It’s not the first report on the subject and it certainly won’t be the last. But coming from the world’s second-largest professional services firm, it deserves attention. (Disclosure: PwC is an occasional client of mine.)

As you’d expect, the report offers a thorough and intelligent analysis. It also arrives at some fairly radical conclusions. I have some major disagreements with it, but it is a welcome contribution.

The key points

Significant job losses…

By the mid-2030s, PwC expects automation to cause the loss of around 38% of US jobs. This is lower than an influential report in 2013 by two Oxford economists, Osborne and Frey, who put the figure at 47%, but higher than other recent reports by mainstream economists. The UK will experience a lower level of job loss, at 30%.

Job-Cutsoffset by new jobs …

The report argues that most of this loss will be offset by (a) the creation of totally new jobs in digital technologies, and (b) the creation of more of the jobs that people already have in services industries, which PwC thinks are harder to automate. These latter jobs will be created because productivity growth creates wealth and extra spending, and therefore job creation.

but leaving a distribution problem

The radical part of the report is its conclusions about income distribution. It argues that the gains in the new economy won’t be equally shared, and that government policy will have to moderate this effect. It addresses the political left’s current favourite solution, universal basic income (UBI), but concludes that it is too expensive, it is wasteful because it pays people who don’t need it, and it reduces incentives to work.

We want change
The report does trot out the tired old pabulum that improving our education and training services can mitigate the problem, but it does so with little conviction. It concludes that “the wider question of how to deal with possible widening income gaps arising from increased automation seems unlikely to go away.” Amen to that.

Questioning the assuptions

So what to make of the report?  Its annex shows that much of the authors’ time was spent re-visiting the algorithms used by Frey and Osborne, and the calculations derived from their assumptions. The original Frey and Osborne work was famously a curious mix of precise calculation and finger-in-the-air guesswork. In particular, they made very subjective guesses about which tasks (and therefore which jobs) are susceptible to automation.

What can an AI do?

That susceptibility to automation depends heavily on the capabilities of the AI systems that will be available in the next two decades, and that gets surprisingly little attention in the PwC report. Given that the computing power available to the developers of AI systems will go through six doublings between now and 2035, those systems will be very different from the ones we are so impressed with today. (At this point some people will be protesting that Moore’s Law is dead or dying. This may be true in a narrow sense, but in its broader, underlying meaning that computer power double every eighteen months or so, it has plenty of life in it yet.)

Where’s the exponential?

The failure to take seriously the impact of the exponential improvement in AI is a problem with a great deal of thinking about its impact.

Exponential
Today’s AI systems can already recognise images (including faces) better than you can. They are overtaking you in speech recognition, and they are catching up with you in natural language processing. By 2035 they will be enormously better than you at all these skills – and these are the very skills which you use at work every day. Of course we don’t know for sure yet, but it is entirely possible that by 2035, the great majority of jobs which people do today will be done cheaper, faster and better by AIs. This includes middle-class white collar jobs in the professions as well as repetitive jobs in warehouses and factories. AI is collar-blind. (I address this in more detail in chapter 3 of my book, The Economic Singularity.)

Legions of new jobs?

These exponentially improved AIs (and their peripherals, the robots) won’t just take our existing jobs: there won’t be much to stop them taking any new jobs we might devise as well. And there is no guarantee that we will devise legions of new jobs. The PwC report observes that “6% of all UK jobs in 2013 were of a kind that didn’t exist in 1990”. That represents significant innovation, but remember, this is the period in which the web was invented and adopted, which changed most aspects of life and work pretty dramatically. Earlier research by Gerald Huff found that 80% of all jobs done by Americans in 2014 existed in 1914.

UBI quibbles

I’m mostly in agreement with the PwC report when it comments on UBI, although the empirical evidence from the trials which have been conducted so far is that it doesn’t turn recipients into lazy couch potatoes. In general the challenge for the automated world is likely to be income, not meaning.

The PwC report omits to mention what is surely the biggest problem with universal basic income, which is that it is basic. We don’t want to spend our futures scraping by on subsistence incomes: we want to live in comfort while the robots do our jobs for us. I believe this is possible, and that it is what we should be aiming for.

Revolutionising education… yet again

Finally, it is wishful thinking to believe that we can give cognitive automation a swerve by revolutionising education. The institutions of education are notoriously hard to fix, and the timescale for fixing them with government policy is far too long. They will be revolutionised in time, thanks to AI, but that will happen in spite of top-down policy, not because of it.

Verdict:

As you’d expect, a thorough and intelligent analysis, with usefully radical conclusions. I disagree with some of the key conclusions, but this is certainly not a bland re-assertion of the Reverse Luddite Fallacy.  Hooray.

heads-in-the-sand

 

Do you need a Chief Artificial Intelligence Officer (CAIO)?

Guest post by Matt Buskell of Rainbird

Do you remember 1996? DVDs were launched in Japan, Travelocity became the first online booking agent, eBay and Ask Jeeves opened their online doors, and the Spice Girls had their first UK number one. It was an inflection point in technology.

ask-jeeves
I spent a lot of time back then trying to convince executives that the internet was going to change the world and they needed to innovate. Not all of them got it. One large UK retailer said this about their internet strategy: “We’ve got it covered. We’ve hired a company to build us a website and they are going to make our product catalogue into a PDF that can be downloaded”.  That retailer no longer exists.

Twenty years later we are at another inflection point – this time thanks to artificial intelligence (AI). In my opinion, AI has the potential to be even more impactful than the internet. Organisations need to take it very seriously. Those which don’t are likely to go the same way as that retailer from 1996.

Organisations need to understand AI, embrace it, and focus on it. For most organisations it is new, so they will need to acquire new skills and carve out new budgets. I think this means they will need a Chief AI Officer, or CAIO.

Rainbird image
Some will argue that the CIO should lead the organisation’s forays into AI. But most CIOs today are busy reducing IT costs and delivering services in an increasingly complex technical landscape. In short, they are too busy keeping the lights on. Strategy directors and finance directors are unlikely to have the requisite expertise. The impact of AI on organisations will be so profound that it deserves its own department, reporting direct to the CEO.

In the short term, what would this CAIO be doing? The first task in many organisations will be to collate all the data the organisation has, and understand its potential value in helping to raise revenue or reduce costs. This will involve a detailed assessment of what would be required to get it “clean” enough for use by AI algorithms.

Many organisations could then significantly improve customer engagement – externally and internally – by the use of AI bots. Bots using advanced natural language processing technologies will need extensive training on the terminology used within the industry and the specific company.

New business modelsPerhaps the biggest impact the CAIO and her colleagues will have in many organisations is the development of new business models. In most cases, any new ideas will have to be quickly prototyped, and comprehensive business cases will have to be produced before they are rolled out. For example an accounting firm could put revenue recognition rules and guidelines into an expert system and publish it to their customers. This service could be sold per click, per positive outcome, or per user, all of which are very different to the traditional model of billing per hour. The CAIO would need to model different business scenarios based on the new pricing or billing options, and show that adopting the new model would create incremental revenue and not just cannibalise existing revenue streams. He might of course also point out that if the organisation does not adopt the new model, existing competitors or startups might do so instead.

The CAIO’s team will need to include a range of different skill sets, and will probably involve an eclectic mix of personalities. Revenue-focused commercial people will have to work closely with more academic AI experts and pragmatic process improvement experts. The office party should be interesting – perhaps they will play the Spice Girls.

Rainbird

Rainbird is an award winning cognitive reasoning platform. It enables businesses to rapidly automate decision-making tasks and build tools that augment human workers in more complex operations.

Future Bites 5 – Drones

The fifth in a series of un-forecasts*, little glimpses of what may lie ahead in the century of two singularities.

Julia felt the blast more than she heard it. The deep rumble almost seemed to come from inside her. She had once experienced an earthquake, several years ago, and her first thought was that this was another one. But that had been in Indonesia, where earthquakes were fairly common; an earthquake in East London was unheard of.

Terror attack

Instinctively she flicked her phone into life, and it brought her up to speed. The newsfeeds had nothing yet, but Twitter was already alight with information. The blast had been a massive explosion at an electricity sub-station about fifteen miles from where she stood. Eyewitnesses thought that a lot of people had been killed, and many more injured. Then the videos started spilling into her feed, and they were astonishing, horrific. The videos were surprisingly clear considering the stress the people taking them must be going through, but Julia didn’t stop to consider the amazing performance of smartphone cameras these days. What she was looking at was shocking. The blast area was huge and it was clear the damage was enormous.

She went back to her favourite newsfeed, which was catching up with Twitter.  It told her that two organisations had claimed responsibility. One was a jihadist Islamic organisation, but its star had faded years ago, and its routine attempts to claim the “credit” for any piece of mayhem were generally dismissed. The other was a more likely culprit: JUST – the Jobless Union for Socialist Technology. Starting out as a think tank, a decidedly non-violent talking shop for people interested in how society could adjust to technological unemployment, JUST had gradually been taken over by militants as more and more people found themselves on subsistence welfare incomes, completely unable to find a job.

Julia realised that this attack was a watershed event, maybe even on the scale of 9/11. Sirens screamed as every available rescue services vehicle raced to the site. Then she looked up, and she noticed something odd. The air was full of drones, and they were all heading to the site as well. Most of them were Amazon delivery drones, but she had never seen so many in the air before.

Drones swarm

She looked back to her phone, where the explanation awaited her. The government had commandeered, temporarily, the entire fleet of Amazon drones, and every other drone whose owner they could track down. At the time it was just one detail of an extraordinary and terrible time, but in the months to come Julia would recognise it as one of the most important things to happen that day. It was the day when the government put eyes in the sky. Amazon would get control of their drones back the next day, but from now on the feeds from the cameras on board would always be available to something like thirty different government agencies on demand. From now on there would always be an eye in the sky, watching.

* This un-forecast is not a prediction.  Predictions are almost always wrong, so we can be pretty confident that the future will not turn out exactly like this.  It is intended to make the abstract notion of technological unemployment more real, and to contribute to scenario planning.  Failing to plan is planning to fail: if you have a plan, you may not achieve it, but if you have no plan, you most certainly won’t.  In a complex environment, scenario development is a valuable part of the planning process. Thinking through how we would respond to a sufficient number of carefully thought-out scenarios could well help us to react more quickly when we see the beginnings of what we believe to be a dangerous trend.

Future Bites 4 – Simultaneous Singularities

The fourth in a series of un-forecasts* – little glimpses of what may lie ahead in the century of two singularities.  This is another optimistic one (aren’t I jolly!).   The first two paragraphs might seem a tad familiar.

It is 2032. Most professional drivers have lost their jobs, and although many have found new ones, they rarely pay anything like as much as the drivers used to earn. A host of other job categories are becoming the preserve of machines, including call centre operatives and radiographers. A few people still cling onto the notion that new types of jobs will be created to replace the old ones taken by machines, but most accept that the game is up. The phrase “Economic Singularity” is in widespread use.

Pollsters report what everyone already knows: there is a rising tide of anger. Crime is soaring, and street protests have turned violent. Populist politicians are blaming all sorts of minorities, and while nobody really believes them, many suspend their disbelief in order to give themselves some kind of hope.

Meanwhile, close observers of the field of AGI research have noticed a rapid acceleration of progress, and are therefore not surprised when Google’s Deep Mind announces that it has essentially cracked the problem. Working closely with the Future of Humanity Institute in Oxford, the Future of Life Institute in Boston and others, Deep Mind also claims that it has worked out how to ensure the planet’s first human-level artificial intelligence has an extremely favourable attitude towards the species which created it.

supercomputer

The world holds its breath as, in a televised event which attracts record-breaking audiences around the world, one of the founders of Deep Mind ceremonially throws the switch which will bring the first true AGI online. After a few moments conferring with colleagues, he announces that the process was successful, and that a large array of backup servers will now be connected to the network of machines which is hosting the first AGI. Nervously, journalists whisper about the arrival of the technological singularity.

Two days later, in another televised event with even more record-breaking audience figures, Deep Mind introduces the new entity to an expectant world. Somehow the entity manages to avoid sounding immodest as it describes itself as the world’s first superintelligence, with an IQ of 1,000 and rising. It announces that it has a cunning plan. It will dedicate most of its cognitive resources (which are being expanded rapidly) to solving the problem of offering all humans the opportunity to upload their minds into highly secure computer substrates. It expects this can be achieved within a couple of years. Anyone who chooses not to pursue this option will be provided with the necessities of life without charge until they die.

brain-computer

It describes this plan as the merging of the two singularities.

* This un-forecast is not a prediction.  Predictions are almost always wrong, so we can be pretty confident that the future will not turn out exactly like this.  It is intended to make the abstract notion of technological unemployment more real, and to contribute to scenario planning.  Failing to plan is planning to fail: if you have a plan, you may not achieve it, but if you have no plan, you most certainly won’t.  In a complex environment, scenario development is a valuable part of the planning process. Thinking through how we would respond to a sufficient number of carefully thought-out scenarios could well help us to react more quickly when we see the beginnings of what we believe to be a dangerous trend.

Bill Gates says we should tax the robot which will steal your job

gates-and-robots

Bill Gates has floated the idea of taxing robots which replace human workers. He said it in an interview (here) with Quartz, a media outlet owned by The Atlantic, and staffed by journalists from The Economist, the New York Times and other publications that Dirty Donald would label as fake news. They made a nice short video (here) to promote the piece, with Gates giggling at the end about the idea of paying more taxes.

It’s a neat idea, and has got a lot of people online very excited. It could help to pay for Universal Basic Income, which is also very exciting to a lot of people online. And it could slow down the pace of cognitive automation, although that isn’t an aspect he is majoring on.

Unfortunately I’m pretty sure it won’t work, and I suspect that Gates understands this. (After all, he is a good deal smarter than me.)

Imagine two firms offering the same service. One has been going for a few years, and recently replaced a thousand humans with machines. The other is a startup, and went straight to machines. The former would be hit by a tax that the latter would escape. Not only is that very unfair, it would simply mean the former would close, and the tax take would disappear anyway.

robot-call-centre

Machines will rarely replace humans on a one-for-one basis. Humans will disappear from call centres, and be replaced by an AI system running on the cloud somewhere, not by a physical robot like in the picture above. Does the government tax one entity – namely the AI – or several, to account for all the unemployed humans?

If you spend a few minutes at this I bet you can come up with a whole lot more reasons why you can’t stabilise the government’s revenues by treating AIs as straight replacements for humans.

But I do think Gates is onto something very important. A couple of years ago he was one of the famous people who warned that strong AI and superintelligence are coming, and that we had to prepare for it. He was one of the “three wise men” who woke the world up to the possibility that we are heading towards a Technological Singularity. The others, of course, were Stephen Hawking and Elon Musk.

three-wise-men-2

Maybe he is now going to do the same with regard to the Economic Singularity – the idea that within a generation most humans are going to be unemployable, and we will need to design and adopt a new economic system. Most economists are still in denial, arguing that automation has not caused lasting unemployment in that past, so it will not do so in the future. They say that fears about cognitive automation leading to technological automation are simply the Luddite Fallacy. But of course, past performance is no guarantee of future outcome, and the economists may well be victims of the Reverse Luddite Fallacy.

We need a “three wise men” (or how about a “three wise women”?) moment for the Economic Singularity. Bring it on, Mr Gates.

It is very likely that part of the solution to technological automation – for part of our future at least – will be heavy taxes on those corporations and individuals who own the means of production. Whether we are looking to fund a Universal Basic Income or something more generous, tax is likely to play an important part in the story.

It’s just not likely to be a tax on individual robots.

ATMs and Asilomar

The ATM automation meme

autor

In an engaging TED talk recorded in September 2016i, economist David Autor points out that in the 45 years since the introduction of Automated Teller Machines (ATMs), the number of human bank tellers doubled from a quarter of a million to half a million. He argues that this demonstrates that automation does not cause unemployment – rather, it increases employment.

He says ATMs achieved this counter-intuitive feat by making it cheaper for banks to open new branches. The number of tellers per branch dropped by a third, but the number of branches increased by 40%. The ATMs replaced a big part of the previous function of the tellers (handing out cash) but the tellers were liberated to do more value-adding tasks, like selling insurance and credit cards.

atm

This story about ATMs has become something of a meme, popular with people who want to believe that technological unemployment is not going to be a thing.

There are three problems with this account. One is that the numbers don’t seem to add up: if you increase the number of branches by 40% and reduce the number of tellers per branch by a third, you don’t get double the number of tellersii. But I don’t want to dwell on this problem: David Autor is a world-renowned economist and I’m not. I may have got my sums wrong! 🙂

It was deregulation, not ATMs

The second problem is that it is not true. The increase in bank tellers was not due to the productivity gains afforded by the ATMs. According to an analysis by finance author Erik Sherman, the increase was mostly due instead to a piece of financial deregulation, the Riegle-Neal Interstate Banking and Branching Efficiency Act of 1994, which removed many of the restrictions on opening bank branches across state lines. Most of the growth in the branch network occurred after this Act was passed in 1994, not before it.iii

President Bill Clinton Signs Riegle-Neal Act of 1994

This explains why teller numbers did not rise in the same way in other countries during the period. In the UK, for instance, retail bank employment just about held steady at around 350,000 between 1997 and 2013iv, despite significant growth in the country’s population, its wealth, and its demand for sophisticated financial services.

The third problem with Autor’s ATM story is that it is unnecessary. No-one is arguing that previous rounds of automation caused lasting unemployment. In 1800, US farms employed 80% of all American workers. In 1900 it was down to 40%, and by 2000 it was below 2%. This was due to automation – or to be more precise, to mechanisation. No doubt the shift was painful for many of the farm workers involved, but in the medium and long term they ended up doing better-paid, safer and more interesting work in towns and cities. And they – or their children – got an education to make sure they could do the new jobs.

It really could be different this time

The present worry about technological automation is that a new wave is coming, and it could be different this time. Previous rounds of automation have involved machines substituting for human and animal muscle power. Horses were put out of a job permanently because they had nothing to offer beyond muscle power – their population in the US went from 25m in 1900 to 2 million today.

horse-dead-2

We humans, by contrast, did have something else to offer: our cognitive skills. This is what the machines, powered by AI, are coming for this time. This time we will see a wave of cognitive automation.

We have had cognitive automation in the past: the role of secretaries has largely been automated by desktop computers. But it hasn’t really got started yet: after all, AI wasn’t very effective until machine learning was successfully applied to it, starting around 2012. Now machines can recognise images better than you can (including faces, which is one of humanity’s special talents), they are overtaking you in speech recognition, and they are catching up fast in natural language processing. And unlike you, they are improving at an exponential rate.

No-one knows for sure what the impact of this will be. But to declare at this early stage that widespread and lasting unemployment will not happen – just because it hasn’t happened in the past – is complacent and dangerous.

Automaticering - productie van het woord "AUTOMATION"

If we are smart, the outcome of cognitive automation could be wonderful. A world in which machines do all the boring stuff (jobs) could be a world in which humans get on with the important things in life, like socialising, learning, playing, exploring.

But there are challenges. In particular, we need to figure out how to give an income to everyone who no longer has a job. And not just a UBI-style subsistence income, but a decent income that allows us all to escape financial anxiety and achieve fulfilment.

Complacency

It is increasingly a matter for concern that even the (relatively few) people who have thought about this are complacent. At the recent Asilomar conference organised by the excellent Future of Life Institutev, the illustrious members of a discussion panel entitled “Implications of AI for the Economy and Society” were confident that there will always be plenty of jobs. MIT economist Andrew McAfee added that even if joblessness is coming, it is far too early to worry about it today.

asilomar-panel

Professor Stuart Russell was in the audience. A few years ago he played a key role in the process of waking the world up to the potential problems raised by artificial general intelligence and superintelligence. Now it seems he is doing the same thing regarding technological unemployment. Towards the end of the discussion he tried to puncture the complacency with a pertinent question; he was politely but firmly rebuffed by Google’s Eric Schmidt.

Autos and awareness

In the next decade, self-driving vehicles (autos for short) will render many professional drivers unemployed. This is not just because they save lives. (Human drivers kill 1.2m people around the world every year – a holocaust that we should not allow to continue now that we have the means to stop it.) It is also because they save cost. Human drivers usually constitute around a quarter of the cost of running a vehicle, and fleet owners will remove that cost as soon as they can.

Professional drivers earn white-collar salaries for blue-collar jobs, and there are no obvious replacements for these jobs. The unemployed drivers will be very unhappy, and we have just seen what happens to the politics of a country when a substantial slice of the electorate is very unhappy. What is more, factory workers, lawyers and nurses will all look at those drivers and think, ”that is me, in ten years or so.”

the_economic_singula_cover_for_kindle

We are heading for an economic singularityvi, and unless our political and business leaders have some answers for how we are going to get through it, the consequences could be very ugly. It is time to wake up.

——-

ii Start with 100 branches, each with 6 tellers, so you have 600 tellers in all. Increase the branch network to 140 and reduce the tellers per branch by a third to 4 and you get 560 tellers. Certainly not a doubling!

iii  http://bit.ly/2kUNAfY

iv  http://bit.ly/2jGrTuS

v https://futureoflife.org/bai-2017/ Since I wrote this article, the FLI seems to have removed the video.
vi As discussed in my book of the same name: http://amzn.to/29LWjaE

Future Bites 3 – Abundance accelerated

The third in a series of un-forecasts* – little glimpses of what may lie ahead in the century of two singularities.

As promised, this one is more optimistic.

angry-trucker

Most professional drivers have lost their jobs, and although many have found new ones, they rarely pay anything like as much as the drivers used to earn. A host of other job categories are becoming the preserve of machines, including call centre operatives and radiographers. A few people still cling onto the notion that new types of jobs will be created to replace the old ones taken by machines, but most accept that the game is up. The phrase “Economic Singularity” is in widespread use.

Pollsters report what everyone already knows: there is a rising tide of anger. Crime is soaring, and street protests have turned violent. Populist politicians are blaming all sorts of minorities, and while nobody really believes them, many suspend their disbelief in order to give themselves some kind of hope.

The government knows that it must act quickly. In desperation it enacts legislation which was ridiculed just a few months previously.

it offers a separate, higher level of unemployment benefit to people who willingly give up their jobs to others. In addition to elevated unemployment payments, these so-called “job sacrificers” are allowed to live in their existing homes, with bills and maintenance paid for by the government.

video-night-and-day

In addition, they receive free access to a new entertainment service which allows them to stream a wide range of music, films, and video games. This new service is funded by a consortium of American and Chinese tech giants who now occupy all of the top ten positions in global rankings of companies by enterprise value thanks to their enormously popular AI-powered services. (Netflix was acquired by one of them for a gigantic premium to stop it protesting.)

Governments around the world are in negotiations with the tech giants and other business leaders about making some of the basic needs of life free to jobless people, including food, clothing, housing and transport. They argue that innovation will continue to improve the quality and performance of each product and service thanks to the remaining demand for luxury versions from those who are still employed, many of whom are earning enormous sums of money.

It has not escaped the attention of policy makers that a gulf is opening up between the jobless and those in work. Nobody has yet suggested a generally acceptable solution.

* This un-forecast is not a prediction.  Predictions are almost always wrong, so we can be pretty confident that the future will not turn out exactly like this.  It is intended to make the abstract notion of technological unemployment more real, and to contribute to scenario planning.  Failing to plan is planning to fail: if you have a plan, you may not achieve it, but if you have no plan, you most certainly won’t.  In a complex environment, scenario development is a valuable part of the planning process. Thinking through how we would respond to a sufficient number of carefully thought-out scenarios could well help us to react more quickly when we see the beginnings of what we believe to be a dangerous trend.