Automation, artificial intelligence and employment
The combination of big data, automation and artificial intelligence looked like something new in 2012, from self-driving cars to e-discovery software to “robojournalism” to financial advisers to medical diagnostics. Wherever it’s possible, “software is eating the world.” In 2013, the federal government will need an innovation agenda to win the race against the machines.
What all of these old solutions have in common is that they are premised on the continued growth of traditional jobs. If we want to make progress we first have to abandon that notion and have to think about a world in which there are fewer and fewer traditional jobs. Here then are three proposed solutions aimed at such a world:
The problem is that the current focus across tech on efficiency is succeeding in destroying jobs for many and creating capital for few: “Disruptive innovations create jobs, whereas efficiency innovations destroy them.”
One of the paradoxes of our age is that we are simultaneously living through a time of positive economic innovation and also a time of the painful erosion of the way of life of many middle-class families.
@PeterDiamandis
The village of Panthbadodiya lies 30km south of Indore, in Madhya Pradesh. Known as the “Heart of India”, this central state has the country’s highest levels of malnutrition and largest tribal population. The ethnic majority here are the Bhil: under the classification system inherited from the British administration they are an “aboriginal tribe”; under the Indian government’s policy of positive discrimination towards disadvantaged communities and castes a “scheduled tribe”.
A group of Bhil women were gathered on mats before their mud and straw homes, built some distance from the other village houses. Mamatabai Punjraj told me the government had given her a bigha (about a quarter of a hectare) of land to farm. But a few months later she fell from a tree while collecting firewood and broke her left leg and hand. “To pay the 25,000 rupees ($460) we owed the hospital, we took out a mortgage on the land, for 50,000 rupees. With the 25,000 we had left, we bought half a bigha of land to farm: we grow maize in the rainy season and beans in winter. But last year the rains did not come on time and we lost our crop. We don’t know how we are going to repay the 25,000 rupees we borrowed from the landowner.”
As in many villages, the landlord, who inherited his land and is of a high caste, is the only employer and lender. Punjraj has no job; her husband works as a day labourer in a city. Her eldest son, Vinod, is a naukar, working all hours for the landlord for never more than 15,000 rupees a year ($275); her second son, Laxman, is a gwala — a child who works for a landlord in return for a reduction of his parents’ debt; her daughter goes to school, thanks to government aid; her youngest son will be a gwala when he is old enough. This serfdom has contributed to the failure of the Indian government’s attempts to raise the great majority of the population out of poverty. More than 77% are thought to live on less than 20 rupees ($0.37) a day, despite India’s rapid economic growth (1).
Unconditional income project
A new pilot study at Panthbadodiya could significantly change living conditions for the poor, and India’s approach to fighting poverty. The village is taking part in the Madhya Pradesh Unconditional Cash Transfer Initiative, a project run by the Self Employed Women’s Association (Sewa; a trade union that has defended the rights of women with low incomes in India for 40 years), with subsidies from Unicef (United Nations Children’s Fund) India. The research director, Sarath Dewala, explained: “The experiment involves giving individuals a small sum of money, at regular intervals, as a supplement to all other forms of income, and observing what happens to their families if this sum is given unconditionally.”
Dewala’s team studied the effects of a minimum monthly income on 4,000 people in eight villages over 18 months. There were no conditions regarding wages, employment, caste, gender or age, and the recipients could use the money as they saw fit. Besides social security benefits, adults received 200 rupees ($3.65) a month, and mothers were given 100 rupees for each child. Four of the villages had had help from Sewa for some years, with the organisation of support groups, savings cooperatives (2), bank loans, training in financial management and support during visits to local officials. Twelve non-participant villages served as controls for comparative study. The initiative, modelled on an urban Sewa project in a district of Delhi, was India’s first applied research on unconditional income. The hypothesis was that direct financial payments would change behaviour and improve family living conditions, especially children’s nutrition and health.
Studies at the beginning, mid-point and end of the project confirmed that, in villages receiving payments, people spent more on eggs, meat and fish, and on healthcare. Children’s school marks improved in 68% of families, and the time they spent at school nearly tripled. Saving also tripled, and twice as many people were able to start a new business.
‘I don’t have to borrow’
“With this money, we can buy more food,” said Mamatabai Punjraj. “I also spend some on medicine, and it means I don’t have to borrow. I have joined the women’s savings group. I’m going to save all the money I get and spend it on my son’s wedding.” Mamatabai’s brother-in-law Bahadua was a gwala until he was 13, earning 4,000 rupees a year, then he became a naukar on 13,000 rupees. He had to borrow his day-to-day living expenses from the landlord. Now, at 22, the unconditional income means he can refuse to work under such conditions.
The idea of giving money to the poor without asking for anything in return startled some. “They told us the men would use the money to get drunk, and the women to buy jewellery and saris,” said Dewala. “But it’s a middle-class prejudice that the poor don’t know how to use money sensibly. The study showed that a regular income allows people to act responsibly. They know their priorities. When something is rare, people measure its value. (Anyway, in tribal villages, people distil their own liquor.) The main advantage is regularity. It makes it possible to organise, save and borrow. The principle is that a small amount of money generates a great deal of energy in a village.”
In the village of Malibadodiya, a few tens of kilometres from Panthbadodyia, Sewa has been helping women for a decade. At a meeting of the women’s savings group, the members mixed freely, though they were from different castes and backgrounds. In a cheerful atmosphere, they discussed collective projects such as the building of a roof for the temple, and public toilets. Dewala joked: “Own up, how many of you have used the money to buy jewellery?” In response, one showed the sewing machine she had saved for over a year to buy, another proudly announced she had nearly finished paying for her family’s television set, and another held up a 300-rupee blanket for the winter, of far better quality than the one it replaced. Everyone laughed as Mangu, related the adventures of a group of women who had gone to a nearby town on a tractor, to demonstrate against the high cost of living, defying warnings from their menfolk and threats from the police.
“Women are no longer afraid. They are becoming independent, managing money, making plans. In several villages, they have forced the landlord to raise their wages,” said Rashmani. She worked in a bidi cigarette factory for 20 years before becoming a Sewa activist, and now works with more 300 villages. Some union representatives lead district communities with as many as 75,000 members. “We want to show that, if a union manages the money, it will be better shared out, and that if you take care of people, you can succeed.” Dewala added: “The key point we want to make is that the presence of a civil society body makes all the difference.”
Conditions lead to corruption
The project was prompted by an awareness of the failure of public policy measures against poverty. The Planning Commission estimates that only 27% of the spending reaches people on low incomes (3); 90% of the workforce is in the informal sector and still has no social protection. Direct cash payments cut out the many leaks and corrupt intermediaries. Delawa said: “The idea of unconditional income comes from the failure of conditional programmes. As soon as there are conditions, there is erosion. Conditionality means intermediaries, which means power, which means corruption.” According to Sewa, the state of Madhya Pradesh has 321 programmes for the distribution of land, food, gas, scholarships, bicycles, paid work — all subject to strict conditions regarding gender, caste, ethnicity, age, number of children or occupation. “The ‘true’ poor person — who is hungry and sick, homeless, and has no television — doesn’t exist,” said Delawa. “Many people live on the edge of poverty, and lose their right to public aid.” Only unconditionality can overcome these many difficulties.
The authorities are interested: on seeing the project’s promising results, the government of Madhya Pradesh asked Sewa to include an isolated tribal village, and Unicef agreed to finance the project for another six months, increasing the allocation to 300 rupees for adults and 150 rupees for each child. In November, Manmohan Singh’s federal government surprised the country by announcing an overhaul of aid programmes, under the title of Direct Benefit Transfers. From January, 29 programmes were converted to money paid into bank accounts, starting with 20 districts in 16 states. In June, this will go nationwide. The change was inspired by the success of Brazil’s Bolsa Familia (family allowance), which has taken 12 million families out of poverty and made a significant contribution to the country’s development. (It also ensured the re-election of President Luiz Inácio Lula da Silva in 2006).
With only a year before India’s next general election, the announcement of this reorganisation, and direct cash payments to India’s many poor, is appealing to the government. The idea could also appeal to the neoliberals, since the government has promised to bring the cost of social welfare down to 2% of GDP, from the current 3.5% (4). But the promise has been greeted with caution in some quarters: the minister for oil and gas has already asked for three more months in which to convert gas subsidies to cash payments (5). The neoliberal Economic Times estimates the programme will not be operational before October (6).
In this context, it’s unsurprising that Sewa’s direct cash transfers have made some wary, even if they have nothing to do with government policy. There have been rumours that the project is a prelude to the abolition of public aid, though Dewala said: “We don’t see it as a substitute, but as extra support.”
Left’s vision of a good society
The study’s economist, Guy Standing, professor of development studies at the School of Oriental and African Studies, London, and a founder member of the Basic Income Earth Network, has been defending the idea of an unconditional income for 25 years. The project team met to discuss their final evaluation at the offices of the Council for Social Development in Delhi. Standing said: “The debate has become respectable. In the face of the emerging informal sector and growing inequalities, increasing economic insecurity, a universal basic income is a necessary base for recreating social security — not as a panacea, but as a base.” He said the guaranteed income was seen by libertarians as a tool to promote individual freedom, while progressives regard it as the base level of social security. “The left have to rethink their vision of a good society. We need to think from the perspective of the precariat, not from the old proletariat. We need a combination of a redistributive agenda, a move to basic income, and a policy that strengthens the voice of the precariat.”
Is a universal income practical in India? To extend it “to the entire population may seem unjust and unaffordable,” said Standing, “but there’s no reason to think that the money could not be recovered either through income tax or ... higher taxes on luxury goods and services that only the rich consume.” The national coordinator of Sewa, Renana Jabhvala, prefers the term “unconditional” to “universal”. “Only 10% of Indians pay tax; 50% are self-employed; fewer than 20% have a regular job. Making this income universal might be difficult. But the government could consider giving it to half the population — the people who really need it.”
Sewa, founded in 1972 by textile workers in Gujarat State, has 1.7 million members and runs 112 cooperative enterprises, dozens of credit cooperatives, hospitals, legal services agencies and a bank. Jabhvala explained why Sewa had got involved in the basic income experiment: “The debate started four years ago; the neoliberals were defending it as a way to save money, and the left were criticising it because they saw it as an attack on public aid. But we run a bank, we manage money: we know that money is a powerful thing when you put it into people’s hands.”
‘Unconditional income gives equally to all’
There are issues, notably over public services: “When people have more money, they tend to switch to private services, which are not necessarily better, but which market themselves,” said Jabhvala. “Schools in Madhya Pradesh are terrible. The state must continue to work to improve the education and healthcare it provides.” The logistics of bank accounts are another problem. To fight corruption, the government plans to give each beneficiary a 12-digit biometric identification number: only 222 million Indians have such a number, though 720 million could be assigned one. And if the money doesn’t reach the beneficiaries at regular intervals, the government’s planned revolution could be an embarrassing failure. “The government is making a huge mistake,” said Standing. “The money should be handed out: cash first, then bank account. The banks must be given encouragement, maybe an incentive to have mobile banking units going to villages. Once you start a cash transfer scheme, the banking system is going to respond.”
Another 80km beyond Malibadodiya, in the hills of the southernmost part of the state, lies the isolated village of Ghodakhurd, which the state government asked Sewa to include in the last six months of the project. All 700 villagers are Bhils, and the slow pace of life is disrupted only by young children running almost naked among the buffalo and goats. But inside the modest dwellings there were changes: the walls had been strengthened with bricks and mortar, and there were large heaps of maize set aside for the dry season.
During the hot season, the inhabitants traditionally pick tandu leaves, which the government-owned bidi manufacturing company buys at 75 rupees for a bundle of 5,000 leaves. Until the Sewa project there was almost no cash in the village, but thanks to his unconditional income, Dinesh, the eldest of a family of five sons, was able to pay for private tuition, graduate from high school and go to university. The second son, Umesh, who followed his example and was now in his last year at school, said: “Unconditional income is like parents — it gives equally to all.”
As we left Ghodakhurd, Dewala told me the little white flowers growing among the wheat at the side of the road were called “besharam, flowers without shame, because they grow anywhere, with no regard for private property.”
BRUSSELS - Eurozone unemployment has risen to its highest level since the euro single currency was introduced, data showed on Tuesday, a day after EU leaders promised to focus on creating millions of new jobs to try to kickstart Europe's floundering economy.
For the last few months, I’ve been cautiously testing a radical-sounding hypothesis on smart people: entrepreneurs are the new labor. Or to put it in a more useful way, the balance of power between investors and entrepreneurs that marks the early, frontier days of a major technology wave (Moore’s Law and the Internet in this case) has fallen apart. Investors have won, and their dealings with the entrepreneur class now look far more like the dealings between management and labor (with overtones of parent/child and teacher/student). Those who are attracted to true entrepreneurship are figuring out new ways to work around the traditional investor class. The investor class in turn is struggling to deal with the unpleasant consequences of an outright victory.
In the small and incestuous technology world, where I make my living shouting advice from the peanut gallery, standing behind politically charged statements like this can do a good deal of damage, so I’ve been wary about sharing my views more publicly.
To my surprise though, I found a lot of people agreeing with me. In fact, many confided that they’d been thinking the same thing themselves, and even offered more radical formulations than my own. By contrast, I found very few people seriously arguing for the obvious antithesis (a sort of gung-ho “everybody can be a genuine entrepreneur” sentiment, which I find to be a vacuous rationalization of grim economic realities.)
The implications of this new state of play are extremely important, and extend far beyond the startup world to the economy at large. This is not just another quickie X-is-the-new-Y meme. Which is why it is going to take me some time to develop the arguments carefully. In this first of a three-part series, I will cover the history of this particular entrepreneurs-turning-into-labor pattern, which dates to the 19th century. In Part II, I will apply the pattern to our times, mutatis mutandis. In Part III, I will try to look ahead at how the landscape might evolve.
The Politics of the Shift
I should note that none of this is news to anybody even marginally involved in technology entrepreneurship. This entire three-part series is merely my attempt to assemble arguments made piecemeal by many others, into a coherent whole. But I suspect people far from the entrepreneurial world have no idea that all this is going on.
“Entrepreneurs as the new labor” is not necessarily a bad thing, unless you are among those who are attracted to the “masters of the universe” cachet rather than the substance of the “entrepreneur” label. There is dignity to labor just as there is romance to entrepreneurship.
There are many good things about the shift to a de facto management-labor game. Such a game is sorely needed as industrial models collapse and the work of defining an Internet-era corporate landscape, with new institutions capable of organizing work for a much larger population, begins.
There are still enlightened investors who use their new unchecked power wisely, and there are still entrepreneurs who are wily enough to stay inside the system and play the game on their own terms.
But for the most part, the collapse of the balance of power is not a good thing. Nor is a significant disconnect between nominal and actual narratives defining the lives of a significant and important population.
The good news is: this has happened before (in the late 19th century), and the last time around the system naturally self-corrected and defined a new labor class on its own terms, with the “entrepreneur” label being reclaimed by those it actually described. In the process, a new middle class was born. This was an external side-effect as far as entrepreneurs were concerned, but the main outcome of interest to everybody else. That’s the big hope on the horizon here: that the current travails of the entrepreneur class might eventually end with the formation of a new middle class to replace the one that is currently being gutted.
The transition was not without considerable pain, so we can and should learn from the previous episode and speed up the correction, this time around, hopefully with less pain and overcompensation. For those of you tempted to read this series as a blanket tarring-and-feathering of the investor class, keep in mind that they play an essential role, and that things aren’t particularly pretty when entrepreneurs are dominating investors either.
Real entrepreneurship can return, and those playing the new management-and-labor game can learn to understand themselves more clearly, with a new management-labor narrative, instead of an overloaded investor-entrepreneur narrative.
But however you read what is going on, such a shift is politically charged. I like to kid myself that I am a political neutral on these matters, so I’ll restrict myself to sketching out the contours of the new landscape, and leave you to form political opinions about it.
The Entrepreneur Class Today
Before I proceed, I should offer a very important qualification. By entrepreneurs I mean specifically the narrow class the term has come to define in the last decade: specifically technology entrepreneurs who start companies to build products or services with some sort of technological innovation at its core, with the Internet playing an important role in the venture.
This might seem to be a very narrow definition, but due to the dramatic ongoing impact of the Internet in every sector (“software eating everything”), and the collapse of traditional employment paths, this restricted class of entrepreneurs is quite significant in terms of both numbers and economic impact, and is growing rapidly.
My thesis specifically does not apply to other sorts of entrepreneur: the kind who start risky but non-innovative businesses of the coffee-shop variety, or the kind who steer a staid old family business onto an aggressive growth path. In recent years, the term entrepreneur has been glamorized, valorized and mapped to the technology-startup type entrepreneur, so I am using the unqualified term for simplicity.
And within this class I am specifically refering to the sub-category known as hustlers today. Technology startups typically have a hacker-and-hustler founding pair. Though the hustler can often do some hacking as well, the term has come to mean the person leading marketing, product management and fund-raising activities in the early stages.
So a more careful statement of my thesis would be: non-technical hustler founders of technology startups are the new labor.
What about the technical co-founders? Because of their very different risk exposures, compared to hustlers, they end up on a different path that effectively makes them mercenaries rather than entrepreneurs, a path that generally promises smaller jackpots, but better expected outcomes and survivability.
In brief, whereas hustlers have gradually been losing their information advantage with respect to investors (resulting in the balance of power collapsing), hackers have generally been gaining information advantage with respect to both, as Internet-era technology has gotten more complex and specialized. But their advantage does not lend itself well to being directly wielded. So the power of the technical community is organizing itself in other ways, which I covered in my earlier post on the rise of developeronomics.
Before we dive in, here are two versions of the argument that make my views seem almost moderate by comparison. I want to call these out so you can calibrate various positions in these debates (all the way from “everybody is an entrepreneur” cheer-leading to “evil VCs pwn innocent founders” despair).
- A friend who works at a hedge fund and is starting to dabble in startups on the side wanted a quick primer from me on the popular Lean Startup model. After outlining the basic idea, I added some of my own cautious critical commentary. My friend immediately leaped to the conclusion that I’d been unconsciously resisting: “So you’re basically saying that lean startups are great for investors, and not so great for entrepreneurs” (he also said “bwaahaahaa!”)
- Another friend, a battle-scarred tech veteran, reacted to my views with a metaphor that made even me cringe: “So incubators like Y-Combinator are basically a cloud resource for investors, from which to source interchangeable hustlers, who are prized primarily for their youthful energy rather than any deep market knowledge.” So much for the vaguely romantic notion of startup-founding as being somehow qualitatively different from interchangeable drones in a cubicle farm. Different farm, same metaphor.
I think these versions of the argument overstate the case, but viewed as rhetorical exaggeration, they do make valuable points. Lean startup models, applied with wisdom, can work for entrepreneurs. Applied naively, they become back-seat driving mechanisms with which investors can micromanage startups, to the detriment of both. But the model, being a product of our peculiar times, has the asymmetric balance of power between investors and entrepreneurs wired into its very DNA.
Startup incubators and angel investors can sometimes seem more like outsourced job-training for big companies, or even a substitute for college and graduate school respectively (in fact, many commentators proudly advertise that idea, and the “batch” and “graduating” language is a dead giveaway), but there are people graduating with genuine entrepreneurial skills.
So let’s take a look at the entrepreneurs-are-labor model. It is useful to start with the nineteenth century steel industry where a similar emergence of a labor class from an entrepreneurial class happened, with different outcomes for the hustlers and hackers.
The Nineteenth Century Steel Game
In attempting to make sense of today’s startup scene it is very useful to reflect on the evolution of the global steel industry in the nineteenth century, as it moved from its startup phase in England to its scaling and growth phase in America and Germany (similar things happened in mining, oil, railroads, telegraph and agriculture and machinery).
In the process, a two-tier reorganization occurred, reflecting the diverging paths of the hackers and hustlers of industrialization.
In the first tier, the artisan class of steelmakers (the hackers of their age), that had organized itself in intricate guild-like structures, gave way to two sub-classes: a mercenary-minded scientifically trained engineer class that organized itself into professional associations, and a manual labor class that organized itself into the modern labor movement.
On the internet and in the media there has been growing discussion of technological unemployment. People are increasingly concerned that automation will displace more and more workers-that in fact there might be no turning back at this point. We may be reaching the end of work as we know it.
Mandel Ngan | AFP | Getty Images If you meet Baxter, the latest humanoid robot from Rethink Robotics - you should get comfortable with him, because you'll likely be seeing more of him soon. Rethink Robotics released Baxter last fall and received an overwhelming response from the manufacturing industry, selling out of their production capacity through April.
Imagine that 7 out of 10 working Americans got fired tomorrow. What would they all do? It's hard to believe you'd have an economy at all if you gave pink slips to more than half the labor force. But that-in slow motion-is what the industrial revolution did to the workforce of the early 19th century.
“Technological revolutions happen in two main phases: the installation phase and the deployment phase,” observes Angel of the Year and new Andreessen Horowitz GP Chris Dixon, who says that the turning point between those phases for the Age of Information is…now.
Meanwhile, “profits have surged as a share of national income, while wages and other labor compensation are down,” notes Paul Krugman. Walter Russell Mead agrees: “The old industrial middle class…has been hollowed out, and no comparable source of stable high income employment has emerged.” Recent data supports that: “Incomes rose more than 11 percent for the top 1 percent of (American) earners during the economic recovery, but barely at all for everybody else … Median household income is about 9 percent lower than it was in 1999.”
Coincidence? Nope. The great tech revolution of the last 30 years is finally beginning to metastasize into every other human domain–in other words, software is eating the world, endangering almost every job there is. I argued a few weeks ago that this means America has now hit peak jobs. Let me now unpack that a bit.
For 50 years now Moore’s Law has been (to oversimplify) doubling computing power every two years. People like Ray Kurzweil and Vernor Vinge look at that astonishing history of nonstop exponential growth and predict a technological singularity within our lifetimes.
Me, I’m pretty skeptical. Kurzweil claims that whenever technology hits a limit, “a paradigm shift (i.e., a fundamental change in the approach) occurs, which enables exponential growth to continue.” That’s not much more than a convenient article of faith. As Peter Thiel points out, “technological progress has fallen short in many domains. Consider the most literal instance of non-acceleration: We are no longer moving faster. The centuries-long acceleration of travel speeds … reversed with the decommissioning of the Concorde in 2003.”
On the other end of the spectrum from Kurzweil and Vinge, there are people who think that nothing new is going on: witness Megan McCardle’s dismissal of the economic troubles faced by America’s middle class as “a slight expected income downshift during the Great Recession” in an otherwise bizarre and statistically nonsensical piece.
The reality seems to be somewhere in between. Moore’s Law has finally escaped the confines of the tech sector; as a result, our world is no longer changing linearly, and what’s more its rate of change is increasing; but Kurzweil’s would-be exponential growth is still damped down by the enormous technological barriers outside of the relatively simple world of semiconductors, by regulatory restrictions, and by simple human unwillingness to change that fast.
So I see no mystical Singularity on the horizon. Instead I see decades of drastic nonlinear changes, upheaval, transformation, and mass unemployment. Which, remember, is ultimately a good thing. But not in the short term.
That’s all pretty abstract. Let’s take a specific example: Google’s self-driving cars. What happens when they finally make their way onto American highways en masse? (Which, to be fair, Kurzweil predicted for 2019 back in 1999.) What happens if and when it turns out that they’re much safer than human drivers? Insurance costs will make human driving very expensive, and fewer vehicles will be sold–partly because cars will last longer, partly because fractional ownership of a pool of self-driving vehicles will make more economic sense than having your own.
Improved safety, lower insurance overheads, more efficiency–that’s all great, right? Sure! Of course it is! …Unless you’re one of the more than 2 million truck and taxi drivers out of work.
Self-driving cars are a striking example of software eating jobs, but far from the only one. Almost every job, in every field, probably including yours, will increasingly be threatened by obsolescence and/or automation. That’s a simple and inevitable corollary of software eating the world and the concomitant increasing rate of change. As that rate accelerates, technology will soon start destroying jobs faster than it creates them…if it isn’t already.
Think it can’t happen to you? Already “many of the jobs being displaced are high-skill and high-wage; the downside of technology isn’t limited to menial workers,” warns Krugman. The Economist concurs. Krugman goes on to add: “Still, can innovation and progress really hurt large numbers of workers, maybe even workers in general? I often encounter assertions that this can’t happen. But the truth is that it can, and serious economists have been aware of this possibility for almost two centuries.”
Mead argues in The Blue Elites Are Wrong that the information revolution is like the industrial revolution, and will lead to “empowering ordinary people.” Which, again, is true–eventually. Whether you believe that new and better jobs will be created, or whether you’re willing to think a little bigger and imagine that we’ve finally begun the slow evolution towards a post-scarcity society built around reputation economies rather than “jobs” as we understand them, almost all of these new disruptive technologies will ultimately be good for everyone. I’m no Luddite.
But in the interim, until we retool our societies around these new technologies and new economic realities, the next few decades will be extremely difficult for many people who have grown accustomed to thinking of themselves as middle class. Not everyone can become a computer programmer, genetic counselor, or startup CEO; a whole lot of Mead’s “ordinary people” will be stripped of their jobs and left behind in debt, poverty, and despair. No wonder the rich and skilled are doing their level best to entrench themselves at the top of our soon-to-be-rapidly-narrowing economic pyramid.
I’ve tried to make a point here by citing sources across America’s traditional and tedious left/right divide. This is bigger than that. (To the rest of the world: I’m sorry for fixating on the USA here. I’m not even American myself. But it’s almost certainly going to happen here first. Watch carefully.) If left-versus-right is the only lens through which you can view the world, then you really need to start thinking outside the box in which you have jailed yourself. Because everything will soon be changing, faster and faster, and I assure you that the future will be weirder than we imagine now–and you’ll need a flexible mind if you hope to prosper and thrive.
The robots are coming! Every day it seems we hear another story blaming robots and automation for the disappearance of not only menial jobs, but middle-class ones as well-the kind of work that pays enough to fund a pension, a health-care plan, and a home mortgage.
60 Minutes on CBS News: Are robots hurting job growth? - Technological advances, especially robotics, are revolutionizing the workplace, but not necessarily creating jobs. Steve Kroft reports.
World-renowned artificial intelligence expert and Google's new Director of Engineering, Ray Kurzweil, wants to build a search engine so sophisticated that it could act like a 'cybernetic friend,' who knows users better than they know themselves.
Slowly, but surely, robots (and virtual 'bots that exist only as software) are taking over our jobs; according to one back-of-the-envelope projection, in ninety years "70 percent of today's occupations will likewise be replaced by automation." Should we be worried? Kevin Kelly, "senior maverick" at Wired magazine, and source for the above guestimate, says we shouldn't.
Automation, artificial intelligence and employment
The combination of big data, automation and artificial intelligence looked like something new in 2012, from self-driving cars to e-discovery software to “robojournalism” to financial advisers to medical diagnostics. Wherever it’s possible, “software is eating the world.” In 2013, the federal government will need an innovation agenda to win the race against the machines.
video by DARPAtv
Working with the Marine Corps Warfighting Laboratory (MCWL), researchers from DARPA's LS3 program demonstrated new advances in the robot's control, stability and maneuverability, including "Leader Follow" decision making, enhanced roll recovery, exact foot placement over rough terrain, the ability to maneuver in an urban environment, and verbal command capability.
What all of these old solutions have in common is that they are premised on the continued growth of traditional jobs. If we want to make progress we first have to abandon that notion and have to think about a world in which there are fewer and fewer traditional jobs. Here then are three proposed solutions aimed at such a world:
Artificial intelligence researchers are acutely aware of the dangers of being overly optimistic. Their field has long been plagued by outbursts of misplaced enthusiasm followed by equally striking declines.
If the country is going to have a serious conversation about innovation, unemployment and job creation, we must talk about our race against the machines. For centuries, we've been automating people out of jobs. Today's combination of big data, automation and artificial intelligence, however, looks like something new, from self-driving cars to e-discovery software to "robojournalism" to financial advisors to medical diagnostics.
Foxconn, the Chinese electronics manufacturer that builds numerous mobile devices and gaming consoles, has been in the media lately because of labor issues, complaints over working conditions, rumored riots, and even suicides, all occurring in the past few years as demand for smartphones and tablets is skyrocketing. While consumers began [...]
Wall Street’s credit-derivatives traders, who before the financial crisis commanded $2 million of annual pay, are being replaced by machines as banks cut costs and heed new regulations.
UBS AG (UBSN), Switzerland’s biggest bank, fired its head of credit-default swaps index trading, David Gallers, last week, with no plan to fill the position, according to two people familiar with the matter. Instead, the bank replaced Gallers with computer algorithms that trade using mathematical models, said the people, who asked not to be identified because moves are private.
UBS joins Barclays Plc (BARC), Credit Suisse Group AG (CSGN) and Goldman Sachs Group Inc. (GS) in using computer programs to trade financial instruments that once generated some of their biggest fees. With regulators preparing rules under the 2010 Dodd-Frank financial reform that will push swaps toward exchange-like systems to improve transparency, credit dealers are going digital as automated trading makes humans too expensive.
“It’s natural to push away from humans and large size to machines and small size,” Peter Tchir, the founder of New York- based TF Market Advisors, said in a telephone interview. “It’s been gaining momentum.”
$250 Million
UBS’s algorithm, which can trade as much as $250 million of the Markit CDX North America Investment Grade index and $50 million on the speculative-grade benchmark in one transaction, was introduced last month, the people said.
Megan Stinson, a spokeswoman for Zurich-based UBS, declined to comment, as did Gallers.
Automated trading of swaps marks a shift in a market where transactions historically have been negotiated over the phone after dealers, acting as a go-between for clients, send out indicative prices by e-mail. The dealers offer to buy a swap from a client at one price and sell the same contract to another for a higher amount, profiting from the gap, known as the bid- offer spread.
Outstanding contracts ballooned to more than $62 trillion at the market’s peak in 2007 from $632 billion in 2001 as the derivatives gained popularity as a way to wager on debt without owning bonds or loans, data from the International Swaps and Derivatives Association show.
Human Costs
As late as 2005, managing directors on credit-derivative trading desks were being paid an average $250,000 in salaries and $1.75 million in bonuses, Michael Karp, co-founder of executive-search firm Options Group, said in a 2006 interview with Bloomberg News.
Building an algorithm may cost a few hundred thousand dollars, said Tchir, a former credit-derivatives trader.
Elsewhere in credit markets, Dow Chemical Co., the largest U.S. chemical company by sales, is planning its first benchmark bond issue this year. Volkswagen AG, Europe’s biggest carmaker, sold 2.5 billion euros ($3.2 billion) in bonds that will automatically convert to shares at maturity to boost liquidity following the purchases of Porsche and Ducati.
The U.S. two-year interest-rate swap spread, a measure of debt-market stress, rose 0.22 basis point to 10 basis points as of 11:48 a.m. in New York. The gauge, which widens when investors seek the perceived safety of government securities and narrows when they favor assets such as corporate bonds, has climbed from 8 basis points on Oct. 17, the lowest intra-day level in Bloomberg data back to 1988.
Credit Benchmarks
The Markit CDX investment-grade index, a credit swaps benchmark that investors use to hedge against losses or to speculate on creditworthiness, fell 0.5 basis point to a mid- price of 96.4 basis points, according to prices compiled by Bloomberg.
In London, the Markit iTraxx Europe Index of 125 companies with investment-grade ratings declined 3.3 to 126.2.
The indexes typically fall as investor confidence improves and rise as it deteriorates. Credit swaps pay the buyer face value if a borrower fails to meet its obligations, less the value of the defaulted debt. A basis point equals $1,000 annually on a contract protecting $10 million of debt.
Bonds of Itau Unibanco Holding SA are the most actively traded dollar-denominated corporate securities by dealers today, with 234 trades of $1 million or more as of 11:50 a.m. in New York, according to Trace, the bond-price reporting system of the Financial Industry Regulatory Authority. Brazil’s biggest bank by market value sold $1.87 billion of 5.125 percent subordinated notes yesterday that are due in May 2023, Bloomberg data show.
Dow Offering
Dow, the maker of chemical, plastic and agricultural products, may offer 10-year securities and 30-year debt as soon as today, according to a person familiar with the transaction, who asked not to be identified because terms aren’t set. Benchmark offerings are typically at least $500 million.
The company last issued benchmark debt in November 2011, selling $1.25 billion of 4.125 percent, 10-year notes and $750 million of 5.25 percent, 30-year bonds, according to data compiled by Bloomberg. The bonds due November 2021 traded at 109.4 cents on the dollar to yield 2.94 percent on Nov. 1, Trace data show.
Volkswagen’s three-year notes will pay an annual coupon of 5.5 percent, the Wolfsburg, Germany-based automaker said in a statement today. The minimum conversion price has been set at 154.50 euros and the maximum at 185.40 euros.
Swaps Volumes
Trading volumes in the current version of the Markit CDX high-yield credit swaps index have declined 20.4 percent through Oct. 26 from last year, according to Barclays analysts led by Brad Rogoff. The firm cited data from the Depository Trust & Clearing Corp., which runs a central credit-swaps repository.
Market makers have slimmed down as regulators have ordered them to raise capital to prevent a repeat of the taxpayer-funded bailouts that followed the 2008 collapse of Lehman Brothers Holdings Inc. Banks will hold more reserves against riskier assets under the rules, known as Basel III. Swiss capital rules, applicable to UBS and Credit Suisse, are among the most stringent.
“I don’t think it’s driven by a desire for efficiency as much as a desire to control costs,” Bonnie Baha, head of global developed credit at Los Angeles-based DoubleLine Capital LP, which oversees more than $45 billion, said in a telephone interview. “The cost of a major trading error which could possibly be avoided by having a real human person sitting and thinking about things will far outweigh the personnel costs they save by firing all these guys.”
‘Natural Fit’
Credit Suisse’s program, which started in early 2011, is “a natural fit with our other strong electronic-trading businesses in rates, FX, and commodities,” said Jack Grone, a spokesman in New York for Switzerland’s second-biggest bank.
Michael DuVally, a spokesman for Goldman Sachs in New York, didn’t immediately comment.
Barclays’s algorithm was designed to handle smaller trade sizes and began in April 2011 with the capacity to handle transactions as large as $25 million on the investment-grade index and $5 million on the high-yield benchmark, according to Drew Mogavero, head of U.S. credit-swaps trading. Those sizes have since doubled, he said.
For smaller trades in which there’s less at stake, “we want to automate that process as much as possible and free up the sales people and traders,” Fred Orlan, head of global credit trading, said in a telephone interview. “We want to spend our time driving ideas and solutions to things that have a bigger impact on clients’ overall returns, so that’s really what we’re here for.”
Liquidity Response
The algorithm is designed to respond to liquidity in the market, so the bid-offer spread widens and tightens according to flows, Mogavero said. In liquid markets, trading odd lots through the algorithm typically cuts down that spread, he said.
“It’s not hard to envision an environment given the growth and popularity of algo trading of indices where the sizes continue to increase,” Mogavero said.
The programs so far are primarily used when markets have a balance of buyers and sellers and are driven by dealers to make markets or hedge their own books, according to Nancy Davis, director of derivatives in New York at AllianceBernstein LP.
Barclays shut off its algorithm in Europe in May, deciding conditions and market structure weren’t yet suitable to support it, according to two people familiar with the decision.
Market Share
Dealers are “definitely fighting for market share,” Davis said in a telephone interview. “Once you get plugged, it just becomes operationally easy to trade, so that’s what the rush is to get all these algos out. It’s kind of a race to say who has the best plug-and-play-model right now to gain market share. I don’t think there’s a clear winner or loser at this point.”
Clearing and margin required by Dodd-Frank will also change the cost structure of trading, and algorithms may be one area where traders will be required to post less capital relative to other types of transactions, she said.
Algorithms may also get a boost if CDX futures get traction, Davis and Tchir said.
“You’ll see more people do it, and as these products become more easy for people to trade electronically there will be more participants” from firms such as Citadel LLC, Susquehanna International Group LLP, or Knight Capital Group Inc., Tchir said. “They’ll be able to add their algos to it once it becomes more mainstream.”
Like Stocks
The increasing popularity of algorithms is an example of how credit markets are becoming more like stocks, Tchir said, citing so-called E-mini S&P 500 futures, with a contract value of $70,513 as of yesterday and trading volume of as much as $200 billion a day with no real market maker, he said.
Banks will probably be successful in block trading or in systems resembling so-called dark pools where large orders are traded without identifying the brokers and institutions that buy and sell, he said. There will be “fewer market makers, but those that remain will provide very large-size block trades,” he said.
Computer-driven transactions and high-frequency trading have come under increased scrutiny after the so-called flash crash in May 2010, when a 20-minute plunge in stock prices temporarily erased some $862 billion of market value. A report by the U.S. Securities and Exchange Commission and the Commodity Futures Trading Commission pinned the decline partly on an algorithm employed by one firm trading stock futures.
“They have a bad rap on the street as driving the ’87 crash and they’re not considered by Main Street as friendly vehicles, but at the same time, they are liquidity providers and that’s the biggest change with Dodd-Frank,” AllianceBernstein’s Davis said. “Having more algos in the market in these products will help because it will give market makers a way to have more liquidity so when you call a dealer up they’ll have another outlet.”
To contact the reporter on this story: Mary Childs in New York at mchilds5@bloomberg.net
To contact the editor responsible for this story: Alan Goldstein at agoldstein5@bloomberg.net
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Million-Dollar Traders Replaced With Machines
UBS joins Barclays Plc, Credit Suisse Group AG and Goldman Sachs Group Inc. in using computer programs to trade financial instruments that once generated some of their biggest fees.
UBS joins Barclays Plc, Credit Suisse Group AG and Goldman Sachs Group Inc. in using computer programs to trade financial instruments that once generated some of their biggest fees. Photographer: Gianluca Colla/Bloomberg
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