Future Bites 2 – Populism paves the way for something worse

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

The third one will be more optimistic. Honest.

populism

In the five years of President Trump, corporate taxes were slashed and federal spending on infrastructure projects was boosted. Companies and individuals were exhorted (and sometimes extorted) to buy American, and imports were cut by tariff and non-tariff barriers. The impact was profound. Initially, US GDP rose sharply as its firms repatriated hundreds of $billions of profits from their foreign subsidiaries, and jobs were created to carry out the infrastructure projects.

But the government spending was inefficient, and there were persistent reports of large-scale corruption, some of it involving members of the Trump family. Cross-border trade and investment slumped as more and more countries retaliated against US protectionism.

More importantly, job growth was constrained and then outweighed by the beginnings of cognitive automation, and the unmistakeable signs of widespread and lasting technological unemployment.

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By the end of Trump’s term, inflation was rising fast, along with the national debt. Unemployment was at 15%, and regional military conflicts were becoming both chronic and acute as America had withdrawn from its role as the global peace-keeper. Americans were increasingly scared, and they looked for a scapegoat. President Trump declined the Republican Party’s fretful offer to be its candidate again in 2020, and railed against (and frequently sued) anyone who criticised his track record, blaming Muslims, Mexicans, and the covert activities of “internal traitors”, who he declined to identify.

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Polls showed the Republicans heading for electoral disaster, and a tight contest between a reluctant Michelle Obama and a rising new party which called for law and order, a clamp-down on dissent and protest, internment for certain racial minorities, and a major increase in military expenditure. Hundreds of thousands of newly unemployed people participated in mass rallies, wearing armbands and giving identical salutes to the party’s garish flag.

* 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.

Betting on technological unemployment

lemire-adisq-2016

Daniel Lemire is a Canadian professor of computer science.  He believes that cognitive automotive will not cause lasting unemployment.  I believe the opposite, as I have written in various places, including this blog post and my book, The Economic Singularity.

Neither Daniel nor I has a crystal ball, and we both recognise that we could be wrong.  But we have both thought long and hard about the prospect, and we are both fairly confident in our predictions.  So after chatting about the issue online for a while, we have agreed a bet.

There are currently around 1.7m long-haul truck drivers in the US.  If that number falls to 250,000 between now and the end of the year 2030, then Daniel will pay $100 to a charity of my choice.  If not, then I will make the charitable donation.

This is my second long bet (see here for the first).  I did not expect that becoming a futurist would also make me a gambler!

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A dozen AI-related forecasts for 2017

Robodamus 3

  1. Machines will equal or surpass human performance in more cognitive and motor skills. For instance, speech recognition in noisy environments, and aspects of NLP – Natural Language Processing. Google subsidiary DeepMind will be involved in several of the breakthroughs.

  1. Unsupervised learning in neural networks will be the source of some of the most impressive results.

  1. In silico models of the brains of some very small animals will be demonstrated. Some prominent AI researchers will predict the arrival of strong AI – Artificial General Intelligence, or AGI – in just a few decades.

    amazon-echo-and-google-home

  1. Speech will become an increasingly common way for humans to interact with computers. Amazon’s early lead with Alexa will be fiercely challenged by Google, Microsoft, Facebook and Apple.

  1. Some impressive case studies of AI systems saving significant costs and raising revenues will cause CEOs to “get” AI, and start demanding that their businesses use it. Companies will start to appoint CAIOs – Chief AI Officers.

  1. Self-driving vehicles (Autos) will continue to demonstrate that they are ready for prime time. They will operate successfully in a wide range of weather conditions. Countries will start to jockey for the privilege of being the first jurisdiction to permit fully autonomous vehicles throughout their territory. There will be some accidents, and controversy over their causes.

  1. Some multi-national organisations will replace their translators with AIs.

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  1. Some economists will cling to the Reverse Luddite Fallacy, continuing to deny that cognitive automation could cause lasting unemployment because that is not what has happened in the past. Others will demand that governments implement drastic changes in the education system so that people can be re-trained when they lose their jobs. But more and more people will come to accept that many if not most people are going to be unemployed and unemployable within a generation or so, and that we may have to de-couple incomes from jobs.

  1. As a result, the debate about Universal Basic Income – UBI – will become more realistic, as people realise that subsistence incomes will not suffice. Think tanks will be established to study the problem and suggest solutions.

  1. AI systems will greatly reduce the incidence of fake news.

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  1. There will be further security scares about the Internet of Things, and some proposed consumer applications will be scaled back. But careful attention to security issues will enable successful IoT implementations in high-value infrastructural contexts like railways and large chemical processing plants. The term “fourth industrial revolution” will continue to be applied – unhelpfully – to the IoT.

  1. 2016 was supposed to be the year when VR finally came of age. It wasn’t, partly because the killer app is games, and hardcore gamers like to spend hours on a session, and the best VR gear is too heavy for that. Going out on a limb, that problem won’t be solved in 2017.

AI in 2016: a dozen highlights

alphago

March: AlphaGo combines deep reinforcement learning with deep neural networks to beat the best human player of the board game Go.  [Article]

April: Nvidia unveils a “supercomputer for AI and deep learning”. With a price tag of $129k, it delivers 170 teraflops, and is 12 times more powerful than the company’s 2015 offering. Nvidia’s share price continues its skyward trajectory.  [Article]

April: Researchers from Microsoft and several Dutch institutions create a new Rembrandt. Not a copy of an existing picture, but a new image in the exact style of the master, 3-D printed to replicate his brush-strokes.  [Article]

September: DeepMind unveils WaveNet, a convoluted neural net which produces the most realistic computer-generated speech achieved to date.  [Article]

September: Google unveils an image captioning system that achieves 93.9% accuracy on the ImageNet classification task, and makes it available as an open source model in its Tensor Flow software library.  [Article]

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September: Google, Facebook, Amazon, IBM and Microsoft join forces to create the Partnership on Artificial Intelligence to Benefit People and Society, an organisation intended to facilitate collaboration and ensure transparency and safety.  [Article]

September: Uber launches trials of self-driving taxis in Pittsburgh, open to the public.  [Article]  It was beaten to the punch by NuTonomy, a much smaller company in Singapore.  [Article]  A month later, a self-driving truck operated by Otto, a group of ex-Googlers acquired by Uber, delivers 50,000 beers from a brewery to a customer 120 miles away.  [Article]

September: The Economic Singularity is published, with encouraging reviews. 🙂  [Link]

October: The White House reports that China now publishes more academic papers on AI than the US. European leaders don’t appear concerned that even collectively, they are very far behind.  [Article]

November: Two months after it started using machine learning, Google announces that its Translate system has invented an intermediary language, interlingua, to enable it to translate between languages it had not been taught to translate.  [Article]

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December: The inaugural AI-Europe conference in London attracts 50+ top speakers and 1,000+ attendees.  [Link]


Next up (tomorrow), some forecasts for developments in AI during 2017.

Reviewing last year’s AI-related forecasts

This time last year I made some forecasts about how AI would change, and how it would change us. It’s time to look back and see how those forecasts for 2016 panned out.

Not a bad result: seven unambiguous yes, four mixed, and one outright no. Here are the forecasts (and you can see the original article here.)

forecasts

AlphaGo is the big one: it caught most people by surprise, and is still seen as one of the major landmarks in AI development, along with Deep Blue beating Kasparov in 1997 and Watson beating Jennings in 2011. Admittedly AlphaGo had already beaten excellent human Go players in 2015, but most observers agreed with Lee SeDol’s confident estimate that he would win in March.

My least successful forecast was that Google would re-launch Glass. It didn’t. Instead, 2016 was the year when smart watches reached peak hype and then faded again. I remain confident that AI-powered head-up displays for consumers will be back, whether or not it will be called Glass.

There was a significant development regarding Google’s robot companies, but it was a negative one: Boston Dynamics was quietly put up for sale.

Intel admitted that it was moving from a tick-tock rhythm of chip development to a slower tic-tac-toe one, but Nvidia stormed into the breach, positioning itself as the Intel for AI, declaring rapid advances and scoring a vertigo-inducing stock market performance.

The Internet of Things did hit the headlines in October, but for the wrong reasons, when a multitude of connected devices were commandeered for a botnet attack. The IoT is increasingly being mis-labelled as the Fourth Industrial Revolution – see here.  Grrr.

Next up (tomorrow), a review of 2016’s AI highlights.

Future Bites 1

The first in what may or may not become a series of un-forecasts*, little glimpses of what may lie ahead in the century of two singularities.

otto-self-driving-truck

It’s 2025 and self-driving trucks, buses, taxis and delivery vans are the norm.  Almost all of America’s five million professional drivers are out of work.  They used to earn white-collar salaries for their blue-collar work, which means it is now virtually impossible for them to earn similar incomes.  A small minority have re-trained and become coders, or virtual reality architects or something, but most are on welfare, and / or earning much smaller incomes in the gig economy.  And they are angry.

The federal government, fearful of social unrest (or at least disastrous electoral results), steps in to replace 80% of their income, guaranteed for two years.  This calms the drivers’ anger, but other people on welfare are protesting, demanding to know why their benefit levels are so much lower.

Meanwhile, many thousands of the country’s 1.3m lawyers are being laid off.  And their salaries were much higher.  The government knows it cannot fund 80% replacement of those incomes, but the lawyers are a vociferous bunch.

And there are doctors, journalists, warehouse managers, grocery store workers…

* This un-forecast is not a prediction.  Predicitons are almost always wrong, so we can be sure 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.

Discussing AI with George Osborne

One of the many worrying aspects of the Brexit referendum in the UK and the Trumpularity in the US is that most politicians are not yet talking about the challenges posed by the coming impact of powerful artificial intelligence.  This needs to change.

A conversation I had recently with George Osborne (until recently the UK’s Chancellor of the Exchequer) gives grounds for hope.

The video below (16 minutes) contains excerpts from a recent panel discussion called “Ask Me Anything About the Future”.  Hosted by Bloomberg, it was organised by Force Over Mass, an early-stage investment fund manager.  It was very ably chaired by David Wood, who runs the London Futurists meetup group.

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The video of the whole event (1hr 39 mins) is here.