Rishi Sunak’s coronavirus rescue package is crucial for a collapsing economy. Social partnership is back writes Will Hutton in The Guardian
Food queues at Covent Garden market in London during the Second World War. Photograph: Trinity Mirror/Mirrorpix/Alamy Stock Photo
Last week, the British economic and financial system came very close to breakdown. An extraordinary number of companies were, and are, in acute financial distress, threatening mass lay-offs and the cessation of swathes of economic activity. There was an almost complete collapse in investor confidence, with attempts to sell every financial asset – even high-quality government bonds – in a desperate quest to hold cash. Such was the loss of generalised faith in the integrity of the system that the governor of the Bank of England, Andrew Bailey, came close to shutting the financial markets.
The scale of the incredible drama – much more acute than the financial crisis of September 2008 and still unfolding – only commanded half our attention. Most eyes understandably were focused on the march of the coronavirus and the missteps and miscommunications of a prime minister unsuited for the leadership demands of high office.
The confusion and growing public panic at the uncertain response was amplified manyfold in the financial markets, matched by fear and uncertainty in the real economy that produces the goods and services we want and need. The Treasury and the Bank of England stared into an abyss. Thankfully their officials, derided by the cabal of second-rate ideologue advisers at Number 10, were up to the task.
Here Boris Johnson – and the country – got lucky. The Conservative party, broken by the triumph of anti-EU ideology and the wilful disregard for fact that is the hallmark of the Brexiter mindset, now offers the weakest talent pool in its long history. But the chancellor, Rishi Sunak, is an unexpected outlier. Officials report that he is proving highly intelligent, economically literate, agile and with acutely sensitive political antennae. Thus the unprecedented interventions last week – with much more to come in the weeks ahead.
Even as I write, the Treasury and the Bank are in urgent talks to organise bailout packages for a number of top companies (including, but not only, airlines), sometimes taking government share stakes along the lines of the bailout of RBS in 2008.
But it was only last Monday that the government genuinely thought that if it stood behind business with a massive programme of soft loans, with grants for hard-hit sectors, it might escape without having to go much further. It did not need to sully its hands with un-Tory propositions – underwriting worker incomes together with improved benefits for those thrown out of work.
However, the crisis of confidence in the financial markets and intense lobbying by the CBI and the TUC soon changed minds, none faster than the initially sceptical Sunak. After all, business cannot prosper without buyers for its products: the good health and predictable incomes of the working population are vital. The last vestiges of Thatcherite individualism are being torched. Social partnership is back with a vengeance
Meanwhile, the top echelons of the Bank of England witnessed the consequences of the outbreak as mounting panic in global trading hit British markets badly, all magnified by Johnson’s bumbles. The sterling crisis expected with a no-deal Brexit was brought forward: a currency dependent on the “kindness of strangers”, given the scale of Britain’s monumental international balance of payments deficit, was in near freefall. There had to be a twin response: a fiscal one that “would blow the bloody wall down” and a shock-and-awe monetary intervention to try to steady shattered bond markets.
The Bank moved first, committing to a £200bn programme of printing money to buy bonds (quantitative easing) and cutting interest rates to a symbolic 0.1%. For the moment, the markets have steadied. Then came Sunak’s measures, the centrepiece of which was the commitment to pay 80% of the wages (up to £2,500 a month) of workers threatened by lay-off. He also ratcheted up support for renters and those on universal credit.
Two million people working in the now shut hospitality sector will be immediately eligible, along with up to five million more as the economy contracts by at least one fifth in the months ahead, with the expected package for the self-employed adding yet more. At its peak, the cost per month will exceed £25bn and the scheme will plainly need extending. The budget deficit in 2020-21 will comfortably exceed £200bn, to be financed, if necessary, by the Bank of England printing money. There are no other options. One privy to the policy told me that even at the last they were unsure whether Sunak “had the balls”. He did. It is what had to be done – and is being reproduced across Europe and North America.
It is wartime finance for wartime economic conditions. Over and above the multiple bailout packages currently being negotiated will come state direction and manufacture of vaccines, key medical products, respirators, and the takeover of private hospitals. Key workers – in the NHS, police, transport and food supply chain – will have to be marshalled in their millions and their wellbeing and health protected. Rationing of key foodstuffs will need to be imposed. The only way to head off a full-scale collapse of sterling and protracted economic depression will be to defer Brexit for at least a year or, as one source told me, five years. Government communications will have to be infinitely more sure-footed. The government itself has to be 100% trusted.
The open question is whether Johnson’s government, with its “frighteningly weak” core at Number 10, as one insider reported to me, can do what is necessary. If not there will, as in wartime, have to be a national government (headed by Sunak with Keir Starmer as his deputy). Johnson is too divisive a figure, too thin-skinned, too unserious in his messaging and with too divisive a history, to lead.
Sunak and Starmer offer competence and humanity above ideology. Whether through the deferral of Brexit or smart and well-thought-through state direction of the economy, they will do what is needed to get us through. In the meantime, take social distancing seriously. Be one of those who put society and social obligations first. And stay safe.
The Covid-19 outbreak is forcing politicians and central bankers to set aside ideology and orthodoxy to prevent a global collapse writes Larry Elliot in The Guardian
‘For the time being, politicians are adopting a bipartisan approach to coping with the crisis, and that’s entirely understandable.’ Donald Trump and Steven Mnuchin at a White House press conference on Tuesday. Photograph: Drew Angerer/Getty Images
It is as if the lights have been switched off. The global economy has been plunged into darkness as countries hunker down in response to the Covid-19 pandemic.
Most recessions develop gradually over time. When the last one started in 2008 it took the Bank of England six months to spot it. This time it is different. Then it was a financial virus, this time it is the real thing. Commentators often say the economy is hitting the wall or is falling off a cliff on the weakest of evidence. Today the cliches are horrifyingly true.
On some estimates the UK economy is on course to shrink by 15% in the second quarter of 2020. That is not a recession, it is a collapse surpassing anything in modern times, including the Great Depression.
When the banks were bailed out in 2008, it was because policymakers feared precisely what is now happening: a complete shutdown of the global economy. The rescue package worked, but only just. The early indications from China are that the impact of Covid-19 is markedly greater than that of the financial crisis, itself the most severe downturn of the postwar era.
This was a crisis that could and should have been predicted but, as in the years leading up to 2008, policymakers have been complacent and financial markets in denial about the risks.
Late in the day though it is, lessons need to be learned from 2008. The response not only has to be big and bold, it also has to be coordinated. Yet the international community went into this crisis with a row between two of the biggest oil producers – Russia and Saudi Arabia – driving down the cost of crude, and China and the US embroiled in a trade war. The pandemic has highlighted the need to work together for both public health and economic stability reasons.
Sadly, the world has rarely looked less prepared to act in concert and that matters, because this time it is not the banks that need bailing out, it is the people. Some are able to work from home: millions are not. Covid-19 is already a health crisis; it is set to be an economic crisis too.
A month ago, when financial markets belatedly woke up to the threat posed by Covid-19, the assumption was that there would be a painful but relatively short shock. But even if countries have emerged from quarantine by the summer – a very big if – the speed of economic recovery is going to depend on the collateral damage caused in the meantime: how many businesses go bust; whether laid-off workers have reached the limit of their credit cards to pay the regular monthly bills; the time it takes for confidence to return.
Politicians are starting to use the language, and deploying the policies, of wartime. The UK government wants manufacturers to switch production lines to making ventilators in the same way that factories switched from consumer goods to making planes and tanks.
They are also adopting the language and policies of the left: the need for social solidarity, the importance of intervening to help struggling firms, the urgency of bailouts for hard-hit industries. In a battle for economic survival the constraints of peacetime have to be ditched. When the chancellor, Rishi Sunak, said this was not a time for ideology or orthodoxy, what he really meant was that this was not time for free-market ideology or orthodoxy. Just as in 1940, the size of the budget deficit is seen as irrelevant. All sorts of hitherto taboo policies become possible.
Central banks have provided the first line of defence. They have cut interest rates and begun pumping money into the financial system through the process known as quantitative easing (QE). It is a sign of how the once unconventional quickly becomes part of the mainstream that QE is now seen as being a regular part of a central bank’s armoury.
This time too the once unthinkable will eventually become not just feasible but desirable. Milton Friedman said that governments could always prevent a slump if they were prepared to load helicopters with money and rain it down on the populace. Provided the public thought the cash didn’t have to be paid back, they would increase their spending and lift the economy out of recession.
Governments have always harboured grave doubts about helicopter money. It involves finance ministries ordering central banks to finance tax cuts, cash handouts or public spending increases through the printing of money and so brings into question central bank independence. An even stronger objection is that it leads to hyperinflation and ends – as in the Germany of 1923 – with people trundling wheelbarrows of worthless cash to the shops.
But for now what should be scaring policymakers is the risk that the world economy is heading for the Germany of 1932, when unemployment hit six million and a failure to abandon orthodox policies led to the rise of fascism.
When Jeremy Corbyn was running to be leader of the Labour party in 2015 he flirted with the idea of People’s QE, by which he meant using the money created by the Bank of England to support a green transformation of the economy. It was seen as wildly irresponsible at the time and was quickly ditched.
This week, Jim O’Neill, a former Goldman Sachs chief economist and minister under David Cameron, said there should be cash handouts so people can feed themselves and pay their household bills during the crisis. And what did he call it? People’s QE. Hong Kong has decided to give all residents a cash handout; Donald Trump wants to do the same in the US.
For the time being, politicians are adopting a bipartisan approach to coping with the crisis, and that’s entirely understandable. But at the end of the second world war the public asked themselves a simple question: if a more interventionist approach was right in wartime, why not try it in peacetime? When the Covid-19 crisis is over, as it eventually will be, they might well ask the same question.
With 850 million children worldwide shut out of schools, tech evangelists claim now is the time for AI education. But as the technology’s power grows, so too do the dangers that come with it. By Alex Beard in The Guardian
For a child prodigy, learning didn’t always come easily to Derek Haoyang Li. When he was three, his father – a famous educator and author – became so frustrated with his progress in Chinese that he vowed never to teach him again. “He kicked me from here to here,” Li told me, moving his arms wide.
Yet when Li began school, aged five, things began to click. Five years later, he was selected as one of only 10 students in his home province of Henan to learn to code. At 16, Li beat 15 million kids to first prize in the Chinese Mathematical Olympiad. Among the offers that came in from the country’s elite institutions, he decided on an experimental fast-track degree at Jiao Tong University in Shanghai. It would enable him to study maths, while also covering computer science, physics and psychology.
In his first year at university, Li was extremely shy. He came up with a personal algorithm for making friends in the canteen, weighing data on group size and conversation topic to optimise the chances of a positive encounter. The method helped him to make friends, so he developed others: how to master English, how to interpret dreams, how to find a girlfriend. While other students spent the long nights studying, Li started to think about how he could apply his algorithmic approach to business. When he graduated at the turn of the millennium, he decided that he would make his fortune in the field he knew best: education.
In person, Li, who is now 42, displays none of the awkwardness of his university days. A successful entrepreneur who helped create a billion-dollar tutoring company, Only Education, he is charismatic, and given to making bombastic statements. “Education is one of the industries that Chinese people can do much better than western people,” he told me when we met last year. The reason, he explained, is that “Chinese people are more sophisticated”, because they are raised in a society in which people rarely say what they mean.
Li is the founder of Squirrel AI, an education company that offers tutoring delivered in part by humans, but mostly by smart machines, which he says will transform education as we know it. All over the world, entrepreneurs are making similarly extravagant claims about the power of online learning – and more and more money is flowing their way. In Silicon Valley, companies like Knewton and Alt School have attempted to personalise learning via tablet computers. In India, Byju’s, a learning app valued at $6 billion, has secured backing from Facebook and the Chinese internet behemoth Tencent, and now sponsors the country’s cricket team. In Europe, the British company Century Tech has signed a deal to roll out an intelligent teaching and learning platform in 700 Belgian schools, and dozens more across the UK. Their promises are being put to the test by the coronavirus pandemic – with 849 million children worldwide, as of March 2020, shut out of school, we’re in the midst of an unprecedented experiment in the effectiveness of online learning.
But it’s in China, where President Xi Jinping has called for the nation to lead the world in AI innovation by 2030, that the fastest progress is being made. In 2018 alone, Li told me, 60 new AI companies entered China’s private education market. Squirrel AI is part of this new generation of education start-ups. The company has already enrolled 2 million student users, opened 2,600 learning centres in 700 cities across China, and raised $150m from investors. The company’s chief AI officer is Tom Mitchell, the former dean of computer science at Carnegie Mellon University, and its payroll also includes a roster of top Chinese talent, including dozens of “super-teachers” – an official designation given to the most expert teachers in the country. In January, during the worst of the outbreak, it partnered with the Shanghai education bureau to provide free products to students throughout the city.
Though the most ambitious features have yet to be built into Squirrel AI’s system, the company already claims to have achieved impressive results. At its HQ in Shanghai, I saw footage of downcast human teachers who had been defeated by computers in televised contests to see who could teach a class of students more maths in a single week. Experiments on the effectiveness of different types of teaching videos with test audiences have revealed that students learn more proficiently from a video presented by a good-looking young presenter than from an older expert teacher.
When we met, Li rhapsodised about a future in which technology will enable children to learn 10 or even 100 times more than they do today. Wild claims like these, typical of the hyperactive education technology sector, tend to prompt two different reactions. The first is: bullshit – teaching and learning is too complex, too human a craft to be taken over by robots. The second reaction is the one I had when I first met Li in London a year ago: oh no, the robot teachers are coming for education as we know it. There is some truth to both reactions, but the real story of AI education, it turns out, is a whole lot more complicated.
At a Squirrel AI learning centre high in an office building in Hangzhou, a city 70 miles west of Shanghai, a cursor jerked tentatively over the words “Modern technology has opened our eyes to many things”. Slouched at a hexagonal table in one of the centre’s dozen or so small classrooms, Huang Zerong, 14, was halfway through a 90-minute English tutoring session. As he worked through activities on his MacBook, a young woman with the kindly manner of an older sister sat next to him, observing his progress. Below, the trees of Xixi National Wetland Park barely stirred in the afternoon heat.
A question popped up on Huang’s screen, on which a virtual dashboard showed his current English level, unit score and learning focus – along with the sleek squirrel icon of Squirrel AI.
“India is famous for ________ industry.”
Huang read through the three possible answers, choosing to ignore “treasure” and “typical” and type “t-e-c-h-n-o-l-o-g-y” into the box.
“T____ is changing fast,” came the next prompt.
Huang looked towards the young woman, then he punched out “e-c-h-n-o-l-o-g-y” from memory. She clapped her hands together. “Good!” she said, as another prompt flashed up.
Huang had begun his English course, which would last for one term, a few months earlier with a diagnostic test. He had logged into the Squirrel AI platform on his laptop and answered a series of questions designed to evaluate his mastery of more than 10,000 “knowledge points” (such as the distinction between “belong to” and “belong in”). Based on his answers, Squirrel AI’s software had generated a precise “learning map” for him, which would determine which texts he would read, which videos he would see, which tests he would take.
As he worked his way through the course – with the occasional support of the human tutor by his side, or one of the hundreds accessible via video link from Squirrel AI’s headquarters in Shanghai – its contents were automatically updated, as the system perceived that Huang had mastered new knowledge.
Huang said he was less distracted at the learning centre than he was in school, and felt at home with the technology. “It’s fun,” he told me after class, eyes fixed on his lap. “It’s much easier to concentrate on the system because it’s a device.” His scores in English also seemed to be improving, which is why his mother had just paid the centre a further 91,000 RMB (about £11,000) for another year of sessions: two semesters and two holiday courses in each of four subjects, adding up to around 400 hours in total.
“Anyone can learn,” Li explained to me a few days later over dinner in Beijing. You just needed the right environment and the right method, he said.
Derek Haoyang Li, the founder of Squirrel AI, at a web summit in Lisbon. Photograph: Cody Glenn/Sportsfile via Getty Images
The idea for Squirrel AI had come to him five years earlier. A decade at his tutoring company, Only Education, had left him frustrated. He had found that if you really wanted to improve a student’s progress, by far the best way was to find them a good teacher. But good teachers were rare, and turnover was high, with the best much in demand. Having to find and train 8,000 new teachers each year was limiting the amount students learned – and the growth of his business.
The answer, Li decided, was adaptive learning, where an intelligent computer-based system adjusts itself automatically to the best method for an individual learner. The idea of adaptive learning was not new, but Li was confident that developments in AI research meant that huge advances were now within reach. Rather than seeking to recreate the general intelligence of a human mind, researchers were getting impressive results by putting AI to work on specialised tasks. AI doctors are now equal to or better than humans at analysing X-rays for certain pathologies, while AI lawyers are carrying out legal research that would once have been done by clerks.
Following such breakthroughs, Li resolved to augment the efforts of his human teachers with a tireless, perfectly replicable virtual teacher. “Imagine a tutor who knows everything,” he told me, “and who knows everything about you.”
In Hangzhou, Huang was struggling with the word “hurry”. On his screen, a video appeared of a neatly groomed young teacher presenting a three-minute masterclass about how to use the word “hurry” and related phrases (“in a hurry” etc). Huang watched along.
Moments like these, where a short teaching input results in a small learning output, are known as “nuggets”. Li’s dream, which is the dream of adaptive education in general, is that AI will one day provide the perfect learning experience by ensuring that each of us get just the right chunk of content, delivered in the right way, at the right moment for our individual needs.
One way in which Squirrel AI improves its results is by constantly hoovering up data about its users. During Huang’s lesson, the system continuously tracked and recorded every one of his key strokes, cursor movements, right or wrong answers, texts read and videos watched. This data was time-stamped, to show where Huang had skipped over or lingered on a particular task. Each “nugget” (the video to watch or text to read) was then recommended to him based on an analysis of his data, accrued over hundreds of hours of work on Squirrel’s platform, and the data of 2 million other students. “Computer tutors can collect more teaching experience than a human would ever be able to collect, even in a hundred years of teaching,” Tom Mitchell, Squirrel AI’s chief AI officer, told me over the phone a few weeks later.
The speed and accuracy of Squirrel AI’s platform will depend, above all, on the number of student users it manages to sign up. More students equals more data. As each student works their way through a set of knowledge points, they leave a rich trail of information behind them. This data is then used to train the algorithms of the “thinking” part of the Squirrel AI system.
This is one reason why Squirrel AI has integrated its online business with bricks-and-mortar learning centres. Most children in China do not have access to laptops and high-speed internet. The learning centres mean the company can reach kids they otherwise would not be able to. One of the reasons Mitchell says he is glad to be working with Squirrel AI is the sheer volume of data that the company is gathering. “We’re going to have millions of natural examples,” he told me with excitement.
The dream of a perfect education delivered by machine is not new. For at least a century, generations of visionaries have predicted that the latest inventions will transform learning. “Motion pictures,” wrote the American inventor Thomas Edison in 1922, “are destined to revolutionise our schools.” The immersive power of movies would supposedly turbo-charge the learning process. Others made similar predictions for radio, television, computers and the internet. But despite small successes – the Open University, TV universities in China in the 1980s, or Khan Academy today, which reaches millions of students with its YouTube lessons – teachers have continued to teach, and learners to learn, in much the same way as before.
There are two reasons why today’s techno-evangelists are confident that AI can succeed where other technologies failed. First, they view AI not as a simple innovation but as a “general purpose technology” – that is, an epochal invention, like the printing press, which will fundamentally change the way we learn. Second, they believe its powers will shed new light on the working of the human brain – how repetitive practice grows expertise, for instance, or how interleaving (leaving gaps between learning different bits of material) can help us achieve mastery. As a result, we will be able to design adaptive algorithms to optimise the learning process.
UCL Institute of Education professor and machine learning expert Rose Luckin believes that one day we might see an AI-enabled “Fitbit for the mind” that would allow us to perceive in real-time what an individual knows, and how fast they are learning. The device would use sensors to gather data that forms a precise and ever-evolving map of a person’s abilities, which could be cross-referenced with insights into their motivational and nutritional state, say. This information would then be relayed to our minds, in real time, via a computer-brain interface. Facebook is already carrying out research in this field. Other firms are trialling eye tracking and helmets that monitor kids’ brainwaves.Get the Guardian’s award-winning long reads sent direct to you every Saturday morning
The supposed AI education revolution is not here yet, and it is likely that the majority of projects will collapse under the weight of their own hype. IBM’s adaptive tutor Knewton was pulled from US schools under pressure from parents concerned about their kids’ privacy, while Silicon Valley’s Alt School, launched to much fanfare in 2015 by a former Google executive, has burned through $174m of funding without landing on a workable business model. But global school closures owing to coronavirus may yet relax public attitudes to online learning – many online education companies are offering their products for free to all children out of school.
Daisy Christodoulou, a London-based education expert, suggests that too much time is spent speculating on what AI might one day do, rather than focusing on what it already can. It’s estimated that there are 900 million young people around the world today who aren’t currently on track to learn what they need to thrive. To help those kids, AI education doesn’t have to be perfect – it just needs to slightly improve on what they currently have.
In their book The Future of the Professions, Richard and Daniel Susskind argue that we tend to conceive of occupations as embodied in a person – a butcher or baker, doctor or teacher. As a result, we think of them as ‘too human’ to be taken over by machines. But to an algorithm, or someone designing one, a profession appears as something else: a long list of individual tasks, many of which may be mechanised. In education, that might be marking or motivating, lecturing or lesson planning. The Susskinds believe that where a machine can do any one of these tasks better and more cheaply than the average human, automation of that bit of the job is inevitable.
The point, in short, is that AI doesn’t have to match the general intelligence of humans to be useful – or indeed powerful. This is both the promise of AI, and the danger it poses. “People’s behaviour is already being manipulated,” Luckin cautioned. Devices that might one day enhance our minds are already proving useful in shaping them.
In May 2018, a group of students at Hangzhou’s Middle School No 11 returned to their classroom to find three cameras newly installed above the blackboard; they would now be under full-time surveillance in their lessons. “Previously when I had classes that I didn’t like very much, I would be lazy and maybe take naps,” a student told the local news, “but I don’t dare be distracted after the cameras were installed.” The head teacher explained that the system could read seven states of emotion on students’ faces: neutral, disgust, surprise, anger, fear, happiness and sadness. If the kids slacked, the teacher was alerted. “It’s like a pair of mystery eyes are constantly watching me,” the student told reporters.
The previous year, China’s state council had launched a plan for the role AI could play in the future of the country. Underpinning it were a set of beliefs: that AI can “harmonise” Chinese society; that for it to do so, the government should store data on every citizen; that companies, not the state, were best positioned to innovate; that no company should refuse access to the government to its data. In education, the paper called for new adaptive online learning systems powered by big data, and “all-encompassing ubiquitous intelligent environments” – or smart schools.
At AIAED, a conference in Beijing hosted by Squirrel AI, which I attended in May 2019, classroom surveillance was one of the most discussed topics – but the speakers tended to be more concerned about the technical question of how to optimise the effectiveness of facial and bodily monitoring technologies in the classroom, rather than the darker implications of collecting unprecedented amounts of data about children. These ethical questions are becoming increasingly important, with schools from India to the US currently trialling facial monitoring. In the UK, AI is being used today for things like monitoring student wellbeing, automating assessment and even in inspecting schools. Ben Williamson of the Centre for Research in Digital Education explains that this risks encoding biases or errors into the system and raises obvious privacy issues. “Now the school and university might be said to be studying their students too,” he told me.
While cameras in the classroom might outrage many parents in the UK or US, Lenora Chu, author of an influential book about the Chinese education system, argues that in China anything that improves a child’s learning tends to be viewed positively by parents. Squirrel AI even offers them the chance to watch footage of their child’s tutoring sessions. “There’s not that idea here that technology is bad,” said Chu, who moved from the US to Shanghai 10 years ago.
Rose Luckin suggested to me that a platform like Squirrel AI’s could one day mean an end to China’s notoriously punishing gaokao college entrance exam, which takes place for two days every June and largely determines a student’s education and employment prospects. If technology tracked a student throughout their school days, logging every keystroke, knowledge point and facial twitch, then the perfect record of their abilities on file could make such testing obsolete. Yet a system like this could also furnish the Chinese state – or a US tech company – with an eternal ledger of every step in a child’s development. It is not hard to imagine the grim uses to which this information could be put – for instance, if your behaviour in school was used to judge, or predict, your trustworthiness as an adult.
Students leaving a gaokao college entrance exam in Hangzhou, China. Photograph: Imaginechina/Rex/Shutterstock
On the one hand, said Chu, the CCP wants to use AI to better prepare young people for the future economy, and to close the achievement gap between rural and urban schools. To this end, companies like Squirrel AI receive government support, such as access to prime office space in top business districts. At the same time, the CCP, as the state council put it, sees AI as “opportunity of the millennium” for “social construction”. That is, social control. The ability of AI to “grasp group cognition and psychological changes in a timely manner” through the surveillance of people’s movements, spending and other behaviours means it can play “an irreplaceable role in effectively maintaining social stability”.
The surveillance state is already penetrating deep into people’s lives. In 2019, there was a significant spike in China in the registration of patents for facial recognition and surveillance technology. All new mobile phones in China must now be registered via a facial scan. At the hotels I stayed in, Chinese citizens handed over their ID cards and checked in using face scanners. On the high-speed train to Beijing, the announcer repeatedly warned travellers to abide by the rules in order to maintain their personal credit. The notorious social credit system, which has been under trial in a handful of Chinese cities ahead of an expected nationwide roll out this year, awards or detracts points from an individual’s trustworthiness score, which affects their ability to travel and borrow money, among other things.
The result, explained Chu, is that all these interventions exert a subtle control over what people think and say. “You sense how the wind is blowing,” she told me. For the 12 million Muslim Uighurs in Xinjiang, however, that control is anything but subtle. Police checkpoints, complete with facial scanners, are ubiquitous. All mobile phones must have Jingwang (“clean net”) app installed, allowing the government to monitor your movements and browsing. Iris and fingerprint scans are required to access health services. As many as 1.5 million Uighurs, including children, have been interned at some point in a re-education camp in the interests of “harmony”.
As we shape the use of AI in education, it’s likely that AI will shape us too. Jiang Xueqin, an education researcher from Chengdu, is sceptical that it will be as revolutionary as proponents claim. “Parents are paying for a drug,” he told me over the phone. He thought tutoring companies such as New Oriental, TAL and Squirrel AI were simply preying on parents’ anxieties about their kids’ performance in exams, and only succeeding because test preparation was the easiest element of education to automate – a closed system with limited variables that allowed for optimisation. Jiang wasn’t impressed with the progress made, or the way that it engaged every child in a desperate race to conform to the measures of success imposed by the system.
One student I met at the learning centre in Hangzhou, Zhang Hen, seemed to have a deep desire to learn about the world – she told me how she loved Qu Yuan, a Tang dynasty romantic poet, and how she was a fan of Harry Potter – but that wasn’t the reason she was here. Her goal was much simpler: she had come to the centre to boost her test scores. That may seem disappointing to idealists who want education to offer so much more, but Zhang was realistic about the demands of the Chinese education system. She had tough exams that she needed to pass. A scripted system that helped her efficiently master the content of the high school entrance exam was exactly what she wanted.
On stage at AIAED, Tom Mitchell had presented a more ambitious vision for adaptive learning that went far beyond helping students cram for mindless tests. Much of what he was most excited by was possible only in theory, but his enthusiasm was palpable. As appealing as his optimism was, though, I felt unconvinced. It was clear that adaptive technologies might improve certain types of learning, but it was equally obvious that they might narrow the aims of education and provide new tools to restrict our freedom.
Li insists that one day his system will help all young people to flourish creatively. Though he allows that for now an expert human teacher still holds an edge over a robot, he is confident that AI will soon be good enough to evaluate and reply to students’ oral responses. In less than five years, Li imagines training Squirrel AI’s platform with a list of every conceivable question and every possible response, weighting an algorithm to favour those labelled “creative”. “That thing is very easy to do,” he said, “like tagging cats.”
For Li, learning has always been like that – like tagging cats. But there’s a growing consensus that our brains don’t work like computers. Whereas a machine must crunch through millions of images to be able to identify a cat as the collection of “features” that are present only in those images labelled “cat” (two triangular ears, four legs, two eyes, fur, etc), a human child can grasp the concept of “cat” from just a few real life examples, thanks to our innate ability to understand things symbolically. Where machines can’t compute meaning, our minds thrive on it. The adaptive advantage of our brains is that they learn continually through all of our senses by interacting with the environment, our culture and, above all, other people.
Li told me that even if AI fulfilled all of its promise, human teachers would still play a crucial role helping kids learn social skills. At Squirrel AI’s HQ, which occupies three floors of a gleaming tower next door to Microsoft and Mobike in Shanghai, I met some of the company’s young teachers. Each sat at a work console in a vast office space, headphones on, eyes focused on a laptop screen, their desks decorated with plastic pot plants and waving cats. As they monitored the dashboards of up to six students simultaneously, the face of a young learner would appear on the screen, asking for help, either via a chat box or through a video link. The teachers reminded me of workers in the gig economy, the Uber drivers of education. When I logged on to try out a Squirrel English lesson for myself, the experience was good, but my tutor seemed to be teaching to a script.
Squirrel AI’s head of communications, Joleen Liang, showed me photos from a recent trip she had taken to the remote mountains of Henan, to deliver laptops to disadvantaged students. Without access to the adaptive technology, their education would be a little worse. It was a reminder that Squirrel AI’s platform, like those of its competitors worldwide, doesn’t have to be better than the best human teachers – to improve people’s lives, it just needs to be good enough, at the right price, to supplement what we’ve got. The problem is that it is hard to see technology companies stopping there. For better and worse, their ambitions are bigger. “We could make a lot of geniuses,” Li told me.
The politics of denial, first honed in the tobacco industry, has serious consequences for a floundering Johnson government writes George Monbiot in The Guardian
Protesters outside Downing Street. Photograph: Dan Kitwood/Getty Images
The worst possible people are in charge at the worst possible time. In the UK, the US and Australia, the politics of the governing parties have been built on the dismissal and denial of risk. Just as these politics have delayed the necessary responses to climate breakdown, ecological collapse, air and water pollution, obesity and consumer debt, so they appear to have delayed the effective containment of Covid-19.
I believe it is no coincidence that these three governments have responded later than comparable nations have, and with measures that seemed woefully unmatched to the scale of the crisis. The UK’s remarkable slowness to mobilise, followed by its potentially catastrophic strategy – fiercely criticised by independent experts and now abandoned – to create herd immunity, and its continued failure to test and track effectively or to provide protective equipment for health workers, could help to cause large numbers of unnecessary deaths. But to have responded promptly and sufficiently would have meant jettisoning an entire structure of political thought developed in these countries over the past half century.
Politics is best understood as public relations for particular interests. The interests come first; politics is the means by which they are justified and promoted. On the left, the dominant interest groups can be very large – everyone who uses public services, for instance. On the right they tend to be much smaller. In the US, the UK and Australia, they are very small indeed: mostly multimillionaires and a very particular group of companies: those whose profits depend on the cavalier treatment of people and planet.
Over the past 20 years, I have researched the remarkably powerful but mostly hidden role of tobacco and oil companies in shaping public policy in these three nations. I’ve seen how the tobacco companies covertly funded an infrastructure of persuasion to deny the impacts of smoking. This infrastructure was then used, often by the same professional lobbyists, to pour doubt on climate science and attack researchers and environmental campaigners.
I showed how these companies funded rightwing thinktanks and university professors to launch attacks on public health policy in general and create a new narrative of risk, tested on focus groups and honed in the media. They reframed responsible government as the “nanny state”, the “health police” and “elf ’n’ safety zealots”. They dismissed scientific findings and predictions as “unfounded fears”, “risk aversion” and “scaremongering”. Public protections were recast as “red tape”, “interference” and “state control”. Government itself was presented as a mortal threat to our freedom.
Their purpose was to render governments less willing and able to respond to public health and environmental crises. The groups these corporations helped to fund – thinktanks and policy units, lobbyists and political action committees – were then used by other interests: private health companies hoping to break up the NHS, pesticide manufacturers seeking to strike down regulatory controls, junk food manufacturers resisting advertising restrictions, billionaires seeking to avoid tax. Between them, these groups refined the justifying ideology for fragmenting and privatising public services, shrinking the state and crippling its ability to govern.
Now, in these three nations, this infrastructure is the government. No 10 Downing Street has been filled with people from groups strongly associated with attacks on regulation and state intervention – such as Munira Mirza, who co-founded the Manifesto Club; Chloe Westley from the TaxPayers’ Alliance; and of course Dominic Cummings, who was hired by Matthew Elliott, the founder of the TaxPayers’ Alliance, to run Vote Leave.
When Boris Johnson formed his first government, the Institute of Economic Affairs (IEA), which has been funded by the tobacco industry, boasted that 14 of its frontbenchers, including the home secretary, the foreign secretary and the chancellor, were “alumni of IEA initiatives”. The foreign secretary, Dominic Raab, has published one book and launched another through the IEA, which he has thanked for helping him “in waging the war of ideas”. The health secretary, Matt Hancock, in a previous role, sought to turn an IEA document into government policy. He has accepted significant donations from the organisation’s chairman, Neil Record. The home secretary, Priti Patel, was formerly a tobacco lobbyist. One in five new Conservative MPs have worked in lobbying or public relations for corporate interests.
Modern politics is impossible to understand without grasping the pollution paradox. The greater the risk to public health and wellbeing a company presents, the more money it must spend on politics – to ensure it isn’t regulated out of existence. Political spending comes to be dominated by the dirtiest companies, ensuring that they wield the greatest influence, crowding out their cleaner rivals. While nobody has a commercial interest in the spread of coronavirus, the nature and tenor of the governments these interests have built impedes state attempts to respond quickly and appropriately.
Brexit (remember that?) could be interpreted as an effort to bridge the great split within the Conservatives, caused by the rising power of dirty money. The party became divided between an older, conservative base, with a strong aversion to novelty and change, and its polar opposite: the risk-taking radical right. Leaving the European Union permits a reconciliation of these very different interests, simultaneously threatening food standards and environmental protections, as well as price controls on medicines and other crucial regulations, while raising barriers to immigration and integration with other nations. It invokes ancient myths of empire, destiny and exceptionalism while potentially exposing us to the harshest of international trade conditions. It is likely further to weaken the state’s capacity to respond to the many crises we face.
The theory on which this form of government is founded can seem plausible and logically consistent. Then reality hits, and we find ourselves in the worst place from which to respond to crisis, with governments that have an ingrained disregard for public safety and a reflexive resort to denial. When disasters arrive, its exponents find themselves wandering nonplussed through the wastelands, unable to reconcile what they see with what they believe. Witness Scott Morrison’s response to the Australian fires and Boris Johnson’s belated engagement with the British floods. It is what we see today, as the Trump, Johnson and Morrison governments flounder in the face of this pandemic. They are called upon to govern, but they know only that government is the enemy.
Alicia Clegg in The FT
Caroline Barlow felt little emotion when she settled with the BBC last May and withdrew her employment tribunal claims over unequal pay and constructive dismissal. Just a crushing tiredness that left her shaky and sick and so disoriented that for a while she stopped driving.
She now views her reaction as a kind of grieving, for her job and faith in an institution that she had revered. She entered the BBC’s pay review process suspecting that she was paid less than male heads of product doing jobs similar to her own, and received a 25 per cent rise, though with little explanation of how the figure was arrived at. So she used data protection law to view internal documents that indicated that even after the increase she would still be paid less. The assessors argued, without providing evidence, that she had skills she still needed to develop and the men had bigger roles.
“Publicly the BBC was saying it had introduced a transparent process. Yet, it was made very clear to me that I’d only get salary information on my peers at a final tribunal hearing by court order,” she says.
Like the journalist Carrie Gracie, who also challenged unequal pay at the BBC, Ms Barlow talks of her sense of entering a no-man’s-land of stonewalling and doublespeak, where evidence that she presented was watered down or selectively reported. She says that a strategic project described as “transforming” in a business case, for which she obtained executive committee sign-off, was trivialised as “a hygiene project” after she questioned her pay. She felt blocked by the slow progress of her grievance — she only received the outcome on her final day of employment − undermined in numerous small ways and made to feel unimportant. She became ill and was diagnosed with depression.
Lawrence Davies, director of Equal Justice Solicitors, who acted for Ms Barlow, says such experiences are common. Most employers try to quash internal complaints to avoid exposing themselves legally, should the employee sue. Yet while employers uphold only 1 per cent of grievances, he says, 65-70 per cent of complainants who persevere to an employment tribunal ultimately win, though the strain can be immense.
Kathy Ahern, a retired mental health nurse and academic, studied the psychological toll of challenging an employer after discovering that nurses who reported misconduct had strong beliefs about what it means to be a nurse. When they faced reprisals for putting patients before other loyalties they suffered overwhelming mental distress, not just because of what was done, but because the institutional reality gave the lie to everything that nursing codes of conduct teach. Another study, published in the journal Psychological Reports in 2019, found levels of anxiety and depression among whistleblowers are similar to those of cancer patients.
Ms Ahern likens retaliatory employers to domestic abusers who psychologically manipulate or “gaslight” a partner to destroy their self-confidence and credibility. Tell-tale patterns, which she documents in a review paper published in the Journal of Perinatal & Neonatal Nursing in 2018, run the gamut from maliciously finding fault, to sustained campaigns of petty slights and obstructions, to seeding rumours that the victim is unhinged.
Tom Mueller, author of Crisis of Conscience: Whistleblowing in an Age of Fraud, believes that while employers sometimes label whistleblowers as “crazy” simply to tarnish them, this may actually be how they see them. To “more negotiable” colleagues who know when to bend with the wind, they may come across as “unreasonable sticklers”, and end up friendless and questioning their own sanity.
Margaret Oliver, a former detective with Greater Manchester Police, says that senior officers dismissed her as “unreasonable” and “too emotionally involved” when she voiced concerns about the conduct of two investigations into child sexual exploitation, Operation Augusta (2004-2005) and Operation Span (2010-2012).
After returning from sick-leave, brought on by stress, she spotted an article in the staff newspaper in which GMP’s then chief constable urged officers to challenge police policies that their gut told them was wrong. She “took the scary step” of contacting him directly. But instead of meeting her, as she had suggested, she says he replied with a “bland email” promising that her concerns would be reviewed and passing her back down the command chain.
Having got nowhere, she resigned in 2012 and went public with her allegations, prompting the Mayor of Greater Manchester to commission an independent review. In January this year phase one, covering the period to 2005, concluded that Operation Augusta, had, as she always alleged, been closed down prematurely and children at risk of sexual exploitation had been failed. Ms Oliver recently launched the Maggie Oliver Foundation to support abuse survivors, and also whistleblowers who, like her, have nowhere to turn. “I asked myself: ‘Is there something obvious to others that I’m not seeing? Or is what I’m seeing wrong and making me ill?’ I felt isolated,” she says.
Isolation dogged whistleblower Aaron Westrick throughout a 14-year US legal battle concerning alleged corruption in the body armour industry that concluded, in 2018, with all the defendants ultimately making settlement payments.
As research director at Second Chance Body Armor (since liquidated), Mr Westrick urged his employer to recall a line of defective bulletproof vests containing Zylon, a material manufactured by Japanese company Toyobo. Instead he says that he was frozen out, told by an HR officer accompanied by his employer’s attorney that he was “crazy,” sacked and maligned. “If there’s one word that describes being a whistleblower, it’s loneliness,” he says. “Even your friends don’t really get it.”
Georgina Halford-Hall, chief executive of WhistleblowersUK, says the stress of fighting a bad employer is all-consuming. But, however difficult, it is important to continue doing the everyday things you enjoy. Drawing on personal experience, she recommends finding an independent mental health professional to offload on. “Don’t make every conversation with your partner and friends about your concerns, because that only isolates you further, making it likelier that you’ll end up behaving irrationally.”
From a practical standpoint, the best way for society to support victims of retaliation is to pay their legal fees, says Peter van der Velden, senior researcher at CentERdata, a Dutch research institute, and lead investigator of the study published in Psychological Reports. “What we know from research is that financial problems are a main stressor, few people have money for a lawyer after losing their job.” Something organisations should consider doing, that might strengthen their culture, is to look for opportunities to hire former whistleblowers rather than giving them a wide berth, says Marianna Fotaki, professor of business ethics at the University of Warwick Business School.
Ms Barlow says she still has “bad days”, though increasingly less so. Finding people who have had similar experiences, she says, is helping her rebuild her shattered sense of self. “It keeps your feet grounded in reality, not the manipulated version of reality that your employer wants you to believe.”
The Choreography of Retaliation
When organisations retaliate against employees, they tend to do so through a gradual piling on of pressure that pushes the individual to the point where they mistrust their own judgment, says Kathy Ahern. They become anxious, hypersensitive to threats and easy to cast as “overreacting, or simply disgruntled”. Some warning signs of what she terms a “gaslighting” pattern of retaliation include:
▪Reassuring employees that their complaints are being investigated, while repeatedly stalling.
▪Using euphemisms that diminish the person’s experience, such as “grey area” or “personality clash” for victimisation.
▪Finding fault with a highly-regarded employee who makes a complaint.
▪Praising someone for reporting misconduct, while doing nothing to prevent reprisals.
▪ Encouraging an employee who has suffered retaliation to take sick leave or undergo a psychological evaluation, under the guise of offering support.
Will Hutton in The Guardian
Britain’s national debt over the past decade has always been a non-problem. For most of the last 300 years, it has been very much higher as a share of national output. Our public debt has been well-managed by the Bank of England, so that the average duration of government bonds is 15 years: there is close to zero chance of a crisis of refinancing or of confidence in public debt. At current rates of interest the overall cost of debt service is among the lowest in our history.
Britain has thus plenty of room to spend and borrow, and there was no need for the draconian Cameron-Osborne austerity squeeze in which cumulative cuts in public spending in many areas of government exceeded 40%. Deficit reduction could have been more measured and the pain mitigated. It was baloney from top to bottom – a cruel hoax that was one of the reasons for the Brexit vote, imposing wanton and needless suffering. I and other Keynesian economists have made these arguments in vain for more than a decade – indeed for most of my working life. So Wednesday’s budget was an extraordinary moment.
Chancellor Rishi Sunak repudiated the entire discourse and accepted core Keynesian propositions. He delivered the biggest fiscal boost for nearly 30 years, coordinating it with an interest-rate reduction by the Bank of England – exactly the Keynesian stimulus a flagging economy needed. Public investment was on target to become the highest since 1955, he declared – actually understating the coming public investment boom because in 1955 the comparable figures included investment by the nationalised industries, now nonexistent. The coming wave of investment in roads, rail, housing, schools, further education and ports is unparalleled. It was not just that the investment is needed: he accepted it was part of the government’s role in raising parlously low levels of productivity. Right again.
Yet a rubicon has been crossed. Keynesianism has been restored to its proper place in British public life
Alongside it current public spending is going to rise again, with an additional £12bn package to alleviate the impact of Covid-19. The government would do everything it could to alleviate the spread and impact of the virus. The larger point was that fiscal policy – excusing his party’s volte-face by trying to position it as part of the new international consensus – has got to shoulder its responsibility for driving the economy forward. Amen to that.
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On the Today programme the following morning my jaw dropped as Sunak informed his audience that reasons for confidence in his package included Britain’s public debt averaging 15 years in duration and debt service costs being extraordinarily low. To make the same argument during the Blair, Cameron and May years was to ensure you wore the mark of Cain – an outlandish Keynesian perspective that branded you as ignorant of the basic laws of economics and public finance. But if a Tory chancellor backed by his press makes the same argument, suddenly it becomes the new economic common sense. To be on the liberal left, as Neil Kinnock once remarked, is to be made to feel an alien outsider – even if reason and a majority of the electorate are with you.
Of course cruel truths remain. The colossal errors of the past decade, Brexit and austerity especially, cannot be expunged at a stroke. Britain’s long-run growth rate is barely above 1% as the Office for Budget Responsibility recorded. The impact of Brexit, it declared, would be to lower output over the next 15 years by 5.2% below what it would have been. The much-vaunted US trade deal, if it ever happens, will raise output by a mere 0.16%. Over the next decade exports and imports will be 15% lower. Britain, tragically, is closing – and becoming more intolerant and anti-foreigner in the process.
Nor can the social carnage of the past decade be quickly corrected. Sunak did little or nothing to address child poverty, the desperate plight of the court and criminal justice system or a host of other casualties. This was government from the centre for the centre: local government remained a neglected Cinderella. The increase in current public spending will redress only about a quarter of the cumulative loss in health and education spending since 2010.
Yet a Rubicon has been crossed. Keynesianism has been restored to its proper place in British public life. The Conservatives have once again shown their breathtaking and shameless capacity for reinvention. If Labour wants to trump them, it will need to take Keynesianism even further – into the wholesale Keynesian recasting of the way the financial system intersects with the real economy.
In the meantime it’s a big moment. Perhaps in this respect – and this only – Labour did win an argument at the last election. At the very least a new and beneficial consensus has been born.