"Stop saying robots are killing jobs"

An article in MIT Technology Review disputes that technology is destroying jobs, especially arguments from Brynjolfsson and McAfee which we've seen before.

Brynjolfsson and McAfee’s mistake comes from considering only first order effects of automation where the machine replaces the worker. But when a machine replaces a worker, there is a second order effect: the organization using the machine saves money and that money it flows back into to the economy either through lower prices, higher wages for the remaining workers, or higher profits. In all three cases that money gets spent which stimulates demand that other companies respond to by hiring more workers.

It's the traditional argument that demand simply shifts to new goods and services. But it relies on the traditional assumption that new needs are similar in economic terms to the old ones. In the example above, what of the higher wages for the remaining workers induce them to take more leisure, so total wages remain the same or even fall? That has not happened much to date, but it is a matter of taste rather than economic law.

The fundamental issue is how and when things fall outside the monetary economy, so the flow above springs a leak. I keep arguing that more and more of the things we value as we rise up the hierarchy of needs are harder to package in monetary terms, because they are not excludable nor rival goods. As the underlying nature of the economy changes, our institutions have to adapt too.

 

Moving on from Clippy

"Bill Gates says software assistants can save the world," says MIT Technology Review.

Readily accessible floods of data, combined with powerful cloud computing and advances in software, should allow personal assistants to “understand” what humans are doing and actively collaborate or help them out, said Gates. Smart assistant software could even be crucial in addressing some of the world’s most challenging problems, he said, as identified by his philanthropic organization the Gates Foundation.

Gates said, for example, that software able to intelligently interpret the available data about a person and respond could improve education.

The software agents could help make decisions, too.

Gates imagined an assistant helping a Kenyan farmer using the M-Pesa mobile banking system that handles roughly 30 percent of the country’s GDP (see “Shopping via Text Message”). “When I sell my crop after the harvest, it advises me to save some of my money and even makes that deposit,” said Gates, who praised the data M-Pesa has made available for such projects

Clippy, the notorious Microsoft paperclip "helper", had perhaps just been premature, he said.

Clearly, there's something to this argument. But for now, I find the services available surprisingly primitive. Nobody has yet developed an effective assistant to help prioritize an email inbox, for example (at least commercially). Junk filters and prioritizing some senders is about all email programs do. Compare this to the confident hopes about artificial intelligence and expert systems in the 1980s. Far from super intelligent computers taking over the world, they can barely sort important work time-sensitive email from routine information emails.

And for all the discussion of predicting wants and needs, I still find one of the most common examples, Netflix suggestions, amazingly primitive sometimes. It has not yet figured out there is a man and a woman in our house and they often like different movies.

The difficulty has always been computers have difficulty with context and meaning. Brute force and massive amounts of data, such as Google Machine translation, is starting to change that. However , it looks like we're just going to see specific small-scale helpers for the time being.

That could still have an impact in education or office productivity. But expectations have also fallen.

 

 

"Sympathy for the Luddites"

Paul Krugman says technological disruption is real, and argues redistribution is the only way to deal with it.

And the modern counterparts of those woolworkers might well ask further, what will happen to us if, like so many students, we go deep into debt to acquire the skills we’re told we need, only to learn that the economy no longer wants those skills?

Education, then, is no longer the answer to rising inequality, if it ever was (which I doubt).

So what is the answer? If the picture I’ve drawn is at all right, the only way we could have anything resembling a middle-class society — a society in which ordinary citizens have a reasonable assurance of maintaining a decent life as long as they work hard and play by the rules — would be by having a strong social safety net, one that guarantees not just health care but a minimum income, too. And with an ever-rising share of income going to capital rather than labor, that safety net would have to be paid for to an important extent via taxes on profits and/or investment income.

It's interesting evidence mainstream economics is starting to get worried about this issue. He's not providing a "but these fears have always been misplaced in the past" usual take.

The trouble is redistribution without some sense of who deserves what isn't going to fly. This is the left's problem: people don't believe equality is the same as justice (or "fairness".) We can't solve this without having some sense of what we value, or what the good life is. And liberal neutrality on that question, and its focus on material resources and income above all, makes that impossible.

Krugman's solution also assumes there will be supernormal profits, but technology may compete and innovate those away, too. In a perfect market profit is zero, after all, and tehnology is removing barriers to entry and market segmentation.

 

 

 

 

Siren Servers

The stories about NSA surveillance of email and phone metadata are one more boost to skepticism about the new digital economy.

Here's a separate article in the NYT about digital concentration of influence and wealth.

DISSECT almost any ascendant center of power, and you’ll find a giant computer at the core. In the past, power and influence were gained by controlling something that people needed, like oil or transportation routes. Now to be powerful can mean having the most effective computer on a network. In most cases, this means the biggest and most connected computer, though very occasionally a well-operated small computer can play the game, as is the case with WikiLeaks. Those cases are so rare, however, that we shouldn’t fall into the illusion of thinking of computers as great equalizers, like guns in the Wild West.

The new class of ultra-influential computers come in many guises. Some run financial schemes, like high-frequency trading, and others run insurance companies. Some run elections, and others run giant online stores. Some run social network or search services, while others run national intelligence services. The differences are only skin deep. I call this kind of operation a “Siren Server.”

The irony is the original image of the personal computer was of liberation, such as Apple's famous Superbowl ad in 1984. The Silicon Valley political vision of the world - a kind of libertarian paradise - is encountering increasing resistance and skepticism.

So the author of the NYT article suggests we should move towards micropayments for our personal information, to reduce the advantage of the "siren servers."

Of course, the counterargument is today's titans - Google, Facebook, Amazon, Apple - are likely to be tomorrow's Dell, Compaq, MySpace, or AOL, let alone earlier titans such as Bethlehem Steel or Pennsylvania Railroad. I doubt there are natural monopolies or network effects sufficiently powerful to entrench the current digital elite for long.

Algorithms can be replicated. That kind of information wants to be free, too. And if people find their personal data is being over-exploited, they will find alternative ways to communicate.

There can often be something of an arms race with technology. Take airline fares, for example. Large centralized computing power originally enabled the airlines to segment their customers in the 1970s and 1980s, and extract the maximum amount people would pay for a certain route. But the consumer caught up. Technology also brought transparency before long, including sites like Expedia or Kayak. Large centralized computers still price airline fares, but the airlines barely stay out of bankruptcy most of the time, and their only way to get pricing power is to cut capacity. Their industry became commoditized.

People have also feared the use of technology for surveillance for decades, but it usually enables transparency and less power for gatekeepers too.

The whole economy is changing in deeper ways, and that is irreversible. But I doubt that technology will enable any enduring center of power.

 

 

 

 

 

An Apple Watch?

This is quite a visionary and original speculation what might be the next device for Apple: a watch. I've seen excerpts over the past week, but it's worth reading the entire thing, not just for gadget gee-whiz but a sustained piece of practical imagination. The author worked for fourteen years at Apple and developed some of their original design guidelines.

 

The "Semantic Web" is next

This is an interesting piece on where Google Search is going in the future.

Until now, Google has been an unprecedented signposter of knowledge. It has not "known" the answer to anything itself but it has had an awfully clever way of directing you to exactly the place you can find out. In some senses, that attribute is in the process of changing. This year, Google will roll out what it calls its Knowledge Graph, the closest any system has yet come to creating what Tim Berners-Lee, originator of the web itself, called "the semantic web", the version that had understanding as well as data, that could itself provide answers, not links

 

More Robot news

Still more incremental improvements on the automation front, according to an article in MIT Technology Review.

That is why Budnick is now considering adding a new member to his team: a robot called Baxter. Baxter was conceived by Rodney Brooks, the Australian roboticist and artificial-intelligence expert who left MIT to build a $22,000 humanoid robot that can easily be programmed to do simple jobs that have never been automated before (see “This Robot Could Transform Manufacturing” and “Rebooting Manufacturing”).

The company hasn't sold any robots as yet but it is getting intense interest from American manufurers.

The ultimate goal is for robots like Baxter to take over more complex tasks, such as fitting together parts on an electronics assembly line. “A couple more ticks of Moore’s Law and you’ve got automation that works more cheaply than Chinese labor does,” Andrew McAfee, an MIT researcher, predicted last year at a conference in Tucson, Arizona, where Baxter was discussed.

We've seen other predictions of the impact on cheap Chinese labor before. Manufacturing will go the way of agriculture, with perhaps only 2-3% of the population working in the sector at very skilled jobs.

 

Abundance and Self-Realization

I'm looking at Robert Fogel's The Fourth Great Awakening and the Future of Egalitarianism, starting here.

Distribution of income matters less than distributiion of "spiritual resources", he says. That means there is a tendency in the "Fourth Awakening" to refocus on the individual again, rather than material conditions in society as a whole.

I have often talked about abundance on this blog, such as here and here. Fogel also emphasizes the saturation of material goods.

Our society is so well saturated with consumer durables, in fact, that even the poorest fifth of households are well-endowed with them. Consequently, the era of the household accumulation of consumer durables, which sparked the growth of many manufacturing industries in the many decades following World War II, is largely over in the United States. p189

So where are things going? Meaning becomes more important as survival challenges recede.

Today, people are increasingly concerned with what life is all about. That was not an issue for the ordinary individual in 1880, when nearly the whole day was devoted to earning the food, clothing and shelter needed to sustain life. A half century from now, perhaps even sooner, when increases in productivity make it possible to provide goods in abundance with half today's labor, the issue of life's meaning, and other matters of self-realization, will take up the bulk of discretionary time. p 191-192

Health and leisure time will be the focus of the future economy, although, he says, it is difficult to foresee the details.

The point is that leisure-time activities (including lifelong learning) - volwork - and health care are the growth industries of the late twentieth century and the early twenty-firsty. They will spark economic expansion during our age, just as agriculture did in the eighteenth century and the early nineteenth and as manufacturing, transportation and utilities didin the late nineteenth century and much of the twentieth. The growing demand for health-care services is due primarily, not to a distortion of the price system, but to the increasing effectiveness of medical intervention. p201

What does self-realization mean? Interestingly, Maslow is not mentioned at all, nor are the older classical ideas about virtue in any detail. Instead, Fogel develops his own list.

To those philosophers who have developed the concept, self-realization means the fullest development of the virtuous aspects of one's nature. ..Of all the maldistributed spiritual resources, sense of purpose may be the most important. p205

Others include "a vision of opportunity", "a sense of the mainstream of work and life" which means a sense of where opportunities are and how to pursue them. There must be "a sense of community", an "ability to engage with diverse groups", which entails an "ethic of benevolence". As self-realization is often achieved through an occupation, a "work ethic" and "sense of discipline" are required, as well focus and a "capacity to resist the lure of hedonism". There needs to be a "capacity for self-education", a "thirst for knowledge". an "appreciation of quality", and some "self-esteem." p205-206

To this updated list of virtues he adds a sense of balance or, as Aristotle would put it, the golden mean.

Each of the fifteen spiritual resources just outlined must be possessed in moderation. There is an optimal amount of each spiritual resource, which will vary from one individual to another. Too much of a sense of purpose turns dedication into ruthlessness. Too little sense of purpose may cause one to be uncompetitive in a given pursuit. p207

It isn't quite a virtue ethics, perhaps, as it is more a list of desirable psychological attributes, being well-adjusted rather than arete or excellence. But it comes close. It is not utilitarian, nor based on more simplistic ideas about happiness. It is certainly reconcilable with older virtues such as courage or temperance or practical wisdom. It is also reconcilable with other ideas we have looked at, such as the evolution of the economy from manufacturing to services to experiences to, finally, transformation of individuals, or the requirements for individual flourishing.

What it does not do (and no book can do everything) is explain what happens to labor markets and economic incentives when material needs are saturated. How might a post-scarcity economy work? How will people make a living?

In all, it is quite a radical book for an academic economist. It is also politically quite eclectic - egalitarian, but taking religion seriously; interested in the condition of the poor but skeptical of government intervention. It asks the right questions, even if the answers are not wholly developed.

The basic conclusion is income is no longer a suitable end-point for policy discussions. Nor are national income statistics. Like the rich sons of Athens two thousand years ago, the nature of the good life is the main question that confronts us once material needs are saturated. Even some Nobel Prizewinners in Economics can see that.

 

 

 

Waves of ethical and religious change

I'm looking at Robert Fogel's The Fourth Great Awakening and the Future of Egalitarianism, starting here.

So Fogel argues the main challenge is no longer material inequality, but spiritual inequality. He adds a theory of cyclical evolution of ethics in responses to changes in technology and the economy. This is quite intriguing.

While economic growth since 1700 has been relatively steady and technological change has accelerated, there has been a recurring lag between the vast technological transformations and the human adjustment to those transformations. It is this lag which has produced the crises that periodically usher in profound reconsiderations of ethical values, that produce new agendas for ethical and social reform, and that give rise to political movements that champion the new agendas. p8-9.

People must evolve new ethical perspectives to cope with technological transformations. Exactly, and it seems obvious when put like that. He does not appear to adopt a vulgar Marxist-type approach, however, where ethics and culture are simply superstructure above the real economic base. People adapt their ideas ro suit circumstances when external events force them to reevaluate their perspectives and needs. And those ideas in turn create political and legislative programs.

Interestingly, he argues that this revaluation shows up in religious movements first, long before electoral politics, which, because of its compromise and balancing tends to lag behind. For example,

The greatest of all reform movements in American history, the abolition of slavery, was for decades almost exclusively a religious movement until a number of religiously inspired Northern politicians developed brilliant tactics and strategies necessary to create a winning antislavery coalition. P7

So he has a theory of how and why ethical transformations occur, which is fascinating. Why should religious movements be more responsive? Because in the frenetic competition of American religious denominations, indepedent congregations are likely to evolve responses to new ethical needs far quicker than political parties. The Awakenings are more political than relgiious, but they show up more quickly in relgious reaciton to new technology and new circumstances.

The religious response has been more rapid because of the high degree of independence of specific evangelical congregations from hierarchical control and from the restraints imposed on political parties, which must often trim their policies to maintain coalitions. P9

 

Great Awakenings

Evangelical religion reacts more quickly than more hierarchical and less populist churches. It means there have been a series of "Great Awakenings" in American religious life, which spilled over into politics after a generation or two.

These Great Awakenings are reform movements with an ethical/programmatic phase followed by a legislative/political phase, both of which arise out of the lag between technological change and institutional adjustment. Each Awakening lasts about one hundred years, including a declining phase in which exponents of one great awakening clash with those of the next. The First Great Awakening began in the 1730s and ripened into the American Revolution against the British Crown. The Second Great Awakening began about 1800 and produced the crusade against slavery that eventuated in the Civil War. The Third Great Awakening arose at the end of the nineteenth century and led to the rise of the welfare state and policies to promote diversity. The Fourth Great Awakening, which began about 1960, has recently entered its political phase and is focused on spiritual reform. p9-10

Importantly, the Awakenings mostly came from the margins of society.

The Great Awakenings have not usually originated from the top; generally, they have welled up from below and have often been given voice by ministers and novice leaders on the fringes of the establishment. p42

The First Great Awakening eroded older Puritan beliefs and emphasized individial rights. The Second Great Awakening emphasized equality of opportunity, and moved even away from Calvinist ideas of predestination towards a sense , influenced by Methodist theology, that people could work towards their own salvation.

 

Individual sin versus Social Corruption

The third Great Awakening arose in large part because of the challenge of industrial development and the growth of huge enterprises. That produced a move away from emphasis on individual sin and corruption to social reform, as well as economic and social egalitarianism. Equality of condition mattered more than equality of opportunity.

The Third Awakening rejected the idea that poverty was the wages of sin, and came to terms with Darwinism and science. The innate depravity of man was abandoned in favor of a conception the innocent young corrupted by society.

Modernists in the mainstream denominations evolved into the Social Gospel movement.

Its leading figures argued that, if America was to realize itself, it would have to change not only its creed, its theory of man's relationship to God, but also its ethics. It would have to make poverty not a personal failure, but a failure of society, and evil would have to be seen, not as a personal sin, but as a sin of society...The victory of the modernists and the Social Gospellers laid the basis for the welfare state, providing both the ideological foundation and the political drive for the labor reforms of the 1930s, 1940s and 1950s, for the civil rights reforms of the 1950s and 1960s, and for the new feminist programs of the late 1960s and early 1970s. p24-5

The first three awakenings are part of mainstream historical scholarship, but Fogel is more isolated is seeing a fourth awakening, including the rise of the religious right in recent decades. Logically, however, major shifts in technology and transformation of the economy would entail some sort of Fourth Awakening in due course, however. And it is undeniable, as he points out, that the mainstream Protestant denominations have shriveled, and evangelicals have risen to over a third of the electorate.

Meanwhile, the Third Awakening forces have been secularized.

As modernist theory grew stronger, the supernatural aspects of religion diminished among those creating the New Theology, and conversions ceased to be central to their missionary work. Social reform increasingly replaced personal reform as the center of the struggle to perfect American society... The essence of religion became the elimination of poverty and inequality. p121

The rise of the professional classes has been one of the main economic transformations, and they tend to be secularized, along with a liberal mainstream media. The universities were originally founded largely to train one profession - the ministry. But the growth of new professions and vast increase in demand for skilled graduates transformed them. Academic disciplines which generally had their modern origin in 19th century theological disputes (such as economics, as founded in the American Economic Association) tended to forget the history of their disciplines.

It would be easy to quibble with this scheme of revivals and awakenings, and some would be uncomfortable putting religious feeling so close to the heart of economic and political life. Nonetheless, it is a viable and interesting theory of how and why changes in ethical perspective come about, and I had not read about these movements in any detail before. It is a story of how deep changes in the assumptions about human nature and possibility ramified through theological debate and into practical political outcomes over a period of generations.

The story is now more secularized, as ethical debate now takes place on a much wider sphere than it did one hundred years ago. But it is equally clear that purely secular perspectives can overlook much of the deeper changes going on in the world, which include the massive growth of evangelical religion in Asia, Africa and Latin America. Something is going on out there even if it is not evident in the New York Times or the New York Review of Books view of the world. The world is less secular on the whole than we think.

Inequality of Income

Moreover, many of Fogel's do not rely on his Awakening scheme for their force. He is skeptical of the Third-Awakening focus on income distribution, and he has good technical reasons for saying so. For one thing, that approach underestimates the massive improvement in nutrition, healthcare and life expectancy since the nineteenth century, as well as more leisure, both of which accrued more to the poor than the well-off.

The theory projected by the Social Gospelers, and embraced by modernism generally, held that cultural crises could be resolved by raising incomes. That theory has been given a long trial and has turned out to be incorrect. Despite the sharp rise in incomes, especially at the low end of the income distribution, the moral crisis of the cities remains unresolved. Although income transfers have gone far beyond the mild redistributions advocated by Bascom, Ely and Commons, such problem as drug addiction, alcoholism , births to unmarried teenage girls, rape, the battery of women and children, broken familitgies, violent teenage death , and crime are generally more severe than they were a century ago. p172

Income redistribution is at the core of the current political debate. But it is also increasingly irrelevant. We will conclude looking at the book tomorrow.

"Sure, Big Data Is Great. But So Is Intuition"

An NYT article is skeptical of inflated claims for Big Data:

The quest to draw useful insights from business measurements is nothing new. Big Data is a descendant of Frederick Winslow Taylor’s “scientific management” of more than a century ago. Taylor’s instrument of measurement was the stopwatch, timing and monitoring a worker’s every movement. Taylor and his acolytes used these time-and-motion studies to redesign work for maximum efficiency. The excesses of this approach would become satirical grist for Charlie Chaplin’s “Modern Times.” The enthusiasm for quantitative methods has waxed and waned ever since.

Big Data proponents point to the Internet for examples of triumphant data businesses, notably Google. But many of the Big Data techniques of math modeling, predictive algorithms and artificial intelligence software were first widely applied on Wall Street.

At the M.I.T. conference, a panel was asked to cite examples of big failures in Big Data. No one could really think of any. Soon after, though, Roberto Rigobon could barely contain himself as he took to the stage. Mr. Rigobon, a professor at M.I.T.’s Sloan School of Management, said that the financial crisis certainly humbled the data hounds. “Hedge funds failed all over the world,” he said.

The problem is that a math model, like a metaphor, is a simplification. This type of modeling came out of the sciences, where the behavior of particles in a fluid, for example, is predictable according to the laws of physics.

In so many Big Data applications, a math model attaches a crisp number to human behavior, interests and preferences. The peril of that approach, as in finance, was the subject of a recent book by Emanuel Derman, a former quant at Goldman Sachs and now a professor at Columbia University. Its title is “Models. Behaving. Badly.”

It really is a matter of proper scope, and consciousness of limits. Big Data is wonderful for finding the Higgs Boson among billions of particle paths, or tracking potential credit card fraud. It is not so good at many other tasks where the data is absent or incomplete or misleading. In those cases, it is little different from ancient farmers looking at the sky and seeing mythical animal patterns.

No flying cars, but there is still progress

Virginia Postrel writes that a spate of gloom about the rate of technological innovation is wrong. People lament the fortieth anniversary of the moon landings.

“You promised me Mars colonies. Instead, I got Facebook,” reads the cover of the current issue of MIT Technology Review. In an essay titled “Why We Can’t Solve Big Problems,” editor Jason Pontin considers “why there are no disruptive innovations” today.

But we hardly notice many of the improvements around us, she says.

The world we live in would be wondrous to mid-20th-century Americans. It just isn’t wondrous to us. One reason is that we long ago ceased to notice some of the most unexpected innovations.

Forget the big, obvious things like Internet search, GPS, smartphones or molecularly targeted cancer treatments. Compared with the real 21st century, old projections of The Future offered a paucity of fundamentally new technologies. They included no laparoscopic surgery or effective acne treatments or ADHD medications or Lasik or lithotripsy -- to name just a few medical advances that don’t significantly affect life expectancy... The glamorous future included no digital photography or stereo speakers tiny enough to fit in your ears.

 

Walking with Cavemen

I watched the BBC-produced series Walking with Cavemen on Netflix last night. It's an interesting recreation of life as it must have been for early precursors of people, in the style of a wildlife documentary.

It starts with Lucy (on the left here), a young Australopithecus Afarensis female in her twenties. She was discovered 3.5 million years later by a French-American expedition in Ethiopia. It moves up through homo ergaster and homo habilis to the Neanderthals, and the eventual appearance of us.

A few things struck me about the series. The reason some varieties of human survived, it says - us - was adaptability. Our lineage was a jack of all trades, rather than being superbly adjusted to just one particular niche.

In the final episode, the series argues that homo sapiens eventually outdid the Neanderthals and other closely related species because of our capacity for imagination. It was a close-run thing, too. The species almost died out 75-100,000 years ago. There were as few homo sapiens in the whole world then as there are orangutangs now. Only the most adaptable of an inherently adaptable lineage made it through that chokepoint.

There is one scene in which two humans bury an ostrich egg filled with water in the ground, on the off chance that they will be passing that way again and need the water. No other living thing has the foresight to imagine and plan.

In a way, that is the origin of our whole idea of wealth as well. It is a side-artifact of our motivation to plan ahead and have choices in the future. It is probably connected to contingent aids to survival.

Of course, squirrels do the same when they store nuts for the winter, and more systematically. But perhaps the difference is that is predictable behavior for predictable outcomes, and pure instinct. For us, it is more a store of adaptability and choice and material survival, because for four million years has been our distinctive specialization.

One other thing becomes very evident. The reason for the evolution of the massive human brain is not so much dealing with the external environment, but the human environment: such as reading people's intentions, motivations, propensity to cooperate and form alliances. We can cooperate, and also drive each other crazy with office politics.

The physical world is much simpler and predictable than the human social world, and needs less brainpower. Bacteria can move towards opportunities. Cats are extremely good at instantaneously calculating where to pounce. Even we are good at solving the quite complex mathematics of the trajectory of a ball thrown high in the air so we can catch it, without being aware of it. It is hardwired into our brains, even if we would struggle with the formal mechanics of ballistic trajectories.

Understanding people is the most difficult task the brain has. And that is why it evolved to be so large, despite the huge demands in terms of energy.

Dark social

This is a different view of the significance of Facebook and the social web that I only just noticed, by Alex Madrigal of the Atlantic. In summary:

1. The sharing you see on sites like Facebook and Twitter is the tip of the 'social' iceberg. We are impressed by its scale because it's easy to measure.

2. But most sharing is done via dark social means like email and IM that are difficult to measure.

3. According to new data on many media sites, 69% of social referrals came from dark social. 20% came from Facebook.

We should rewrite the history of the web, he says. People have shared ever since its early days. What Facebook does is provide a way to archive and monetize that sharing.

Companies which lose good ideas

I subscribed a month ago to a wonderful daily e-mail, delanceyplace, which provides excerpts from current non-fiction books, with links to Amazon which benefit a children's literacy project. Today's excerpt is from a book called Advocacy by John A. Daly, with remarkable examples of how people with good ideas could not get them accepted in their original companies. Check it out on the delanceyplace site. An excerpt from the excerpt:

"Business history is dotted with stories of opportunities lost because people within companies were unsuccessful in pitching their ideas. And those neglected opportunities were consequential. Competitors seized market share that could have been kept and increased if the good idea had been adopted. Take the minivan. Who came up with that idea -- Chrysler? No. Ford engineers came up with that idea -- they called it the van-wagon -- but they couldn't convince management that customers would buy it. In fact, one executive who endorsed it, Hal Sperlich, was fired and went on to lead the effort at Chrysler, which then dominated the minivan world for many years. Ford lost out. ...

"Sam Walton, the founder of Walmart, started his career as a franchisee in the Ben Franklin chain of stores. Walton tried to convince the Ben Franklin executives that his model of buying directly from manufacturers and offering deep discounts would lead to incredible opportunities. They didn't listen, Walton implemented the idea himself, and Walmart became an international phenomenon. ...

The same applies to Intel, and many other companies. But the best example is Apple.

"Steve Wozniak, a cofounder of Apple Computers, was working at Hewlett Packard when he and Steve Jobs designed their first personal computer. Wozniak had signed a document at HP saying that whatever he designed as an employee belonged to HP. He said, 'I loved [HP]. That was my company for life. So I approached HP .... Boy, did I make a pitch. I wanted them to do it. I had the Apple I, and I had a description of what the Apple II could do. I spoke of color. I described an $800 machine that ran BASIC (an early computer language), came out of the box fully built and talked to your home TV: And Hewlett-Packard found some reasons it couldn't be a Hewlett-Packard product.'

"Later, when HP began work on a computer, Wozniak approached the project managers and asked to work on it. 'I really wanted to work on computers. And they turned me down for the job. To this day I don't know why. I said, 'I don't have to run anything,' even though I'd done all these things and they knew it. I said, 'I'll do a printer interface. I'll do the lowliest engineering job there is.' I wanted to work on a computer at my company and they turned me down.' Think how different the computer industry would be if Wozniak had successfully pitched his ideas to HP. ...

I read a good book about pitching ideas and overcoming objections a while back, Buy-In: Saving Your Good Idea from Getting Shot Down by John Kotter. I've had good ideas shot down nonetheless. Sometimes no amount of persuasion will work. 

The reason capitalism works better as a system is not because it's efficient or elegant - I was talking about this concerning General Electric the other day - but because in the medium term, in aggregate, fewer good ideas are shot down. So it is more adaptable and innovative.


 

 

Food breakthrough?

This is pretty interesting. A new company is successfully growing food using just sea water and Australian scrubland.

Indeed, the work that Sundrop Farms, as they call themselves, are doing in South Australia, and just starting up in Qatar, is beyond the experimental stage. They appear to have pulled off the ultimate something-from-nothing agricultural feat – using the sun to desalinate seawater for irrigation and to heat and cool greenhouses as required, and thence cheaply grow high-quality, pesticide-free vegetables year-round in commercial quantities.

So far, the company has grown tomatoes, peppers and cucumbers by the tonne, but the same, proven technology is now almost ready to be extended to magic out, as if from thin air, unlimited quantities of many more crops – and even protein foods such as fish and chicken – but still using no fresh water and close to zero fossil fuels. Salty seawater, it hardly needs explaining, is free in every way and abundant – rather too abundant these days, as our ice caps melt away.

It could dramatically change world water usage.

It's an inspiring project, more important, it could be argued, than anything else going on in the world. Agriculture uses 60-80% of the planet's scarce fresh water, so food production that uses none at all is nothing short of miraculous.

I can't help wondering if there is a catch, or long-term problem that isn't evident yet. But a combination of hydroponic techniques and more efficient solar power may be durably effective.

It's bearing out some of the ideas and arguments and new technologies we discussed here.

 

The Internet of Things

GE is building up a huge new research center in the East Bay, near Silicon Valley, says this NYT article, because the same thing that powers sharing trivia on Facebook could also share much more significant data in the real economy. The industrial Internet is being born.

.. G.E.’s effort, analysts say, shows that Internet-era technology is ready to sweep through the industrial economy much as the consumer Internet has transformed media, communications and advertising over the last decade.

The key is adding sensors to machines, to help make them more intelligent.

Today, G.E. is putting sensors on everything, be it a gas turbine or a hospital bed. The mission of the engineers in San Ramon is to design the software for gathering data, and the clever algorithms for sifting through it for cost savings and productivity gains. Across the industries it covers, G.E. estimates such efficiency opportunities at as much as $150 billion.

I think this is very interesting, but the question is whether it will prove to be about transformation and new business models, not simply efficiency. There is a certain amount of big data "me-too-ism" about it.

I was watching an interview between Jeff Bezos and Charlie Rose the other day. Bezos said they never liked to enter a market just because they could. There isn't much money to be made doing the same thing as everyone else, entering a market late a in "me-too" way.

GE may be very good at efficiency, but I wonder if they can innovate as well. We've seen before that the rise of the modern world cannot be explained by greater efficiency, but by doing things in new ways. And I say that as a GE shareholder. Their share price is still near half what it was before the crisis.

They have such vast scale that more efficiency means millions of dollars for even tiny gains, and that could ripple across the economy in power and transportation sectors. But we need new possibilities as well.


 

Mobs and Marvels

The other end of the scale from medieval mobs burning schools in Pakistan: Microsoft demonstrates something just like a Star Trek Voice Replicator.

It could be the next best thing to learning a new language. Microsoft researchers have demonstrated software that translates spoken English into spoken Chinese almost instantly, while preserving the unique cadence of the speaker's voice—a trick that could make conversation more effective and personal.

 

Blaming a whale (and narrative) for defeat

From a David Brooks exchange with Gail Collins in the NYT:

David: This might be a good time for Republicans to redouble their commitment to the reality-based community. Did you see Byron York's reporting from inside the Romney campaign? They apparently had this giant computer model called Orca - named after a whale because it was bigger than anything the Democrats could imagine. It processed huge amounts of data and late in the day was still projecting a Romney victory until its head exploded. Garbage in. Garbage out.

Gail: The Republican Orca - stop me before I fall into a great pile of Moby Dick analogies.

I think that some people are a little transfixed by Nate Silver's accurate projection of the election, despite, as I've noted, his own much more self-awade mature grasp of the limits of models.

I think this is at root a particular problem with journalism.

Or, to put it more precisely, it is a problem with narrative. Human beings have a hardwired fascination with stories, probably dating from sitting around fires in the savannah fifty thousand years ago. It is often the prime way we transmit culture and values and pointers for behavior we should admire.

But stories can be too trite, and this is where journalism becomes very hedgehog-like sometimes. It is all to easy to link stories into an appealing broader narrative, to instinctively frame things in a way which makes for an entertaining read. Stories are much more interesting than data. Once you go looking for "stories", as opposed to drier mechanical reporting of facts, you introduce potential blindspots. Things can fit all too neatly into narrative buckets.

Journalism thrives on stories. Journalists are paid to look for them, rather than dry, ambiguous, complicated truth in isolation.

We've also seen that hedgehogs typically get more media attention, because big striking claims typically make better tv or better stories. Hedgehogs want an audience for their "one big thing." Journalists want a story, And "triumph of models" is itself a good story.

Of course, at the same time as the fivethirtyeight model did well, the Romney and other models performed badly. But why let that get in the way of a good story?

Self-awareness

This is the real explanation of Silver's greater success here. It is not so much a data-driven approach, as using the data to confront your presuppositions. That is why he does better than most journalists and opinion pundits.

It is not, as the story linked above puts it, simply a matter of primitive punditry against spanking new "data driven rationality".

The scientific method is at root about testing hypotheses, not mining data. You test a prediction or explanation against reality, and you revise your views if necessary based on the outcome. You can selectively use data to confirm all kinds of things if you are not careful. So you need to have a falsifiable hypothesis, a situation where at least in principle you may be forced to revise your view.

There's nothing in narrative that compels you to change your view, because you can always add a twist in the story. Indeed, most good stories will have the hero endure many setbacks and misunderstandings before being proved right in the end.

Even in science, as Thomas Kuhn famously pointed out in The Structure of Scientific Revolutions, conflicting data is often left aside as a "puzzle" or "anomaly" in periods of normal science until there is a sudden change of awareness: I.e. the "paradigm shift" which has become so overused a term it is almost a clichė. Even in the hard sciences, it can take a generation for data to settle arguments one way or another. Theories can sprout dozens of ad-hoc adjustments.

So data can be part of this process of self-awareness. But in a world where we have a blizzard of often conflicting and imperfect data, it may equally reinforce entrenched views.

Romney's big Moby Dick model was probably highly sophisticated, but likely being used to mine data more efficiently, not testing against reality.

Innumerate journalists may regard the statistical models as some sort of new semi-deity, partly because they don't understand it, or the many ways in which statistics can be used to obscure. (There is a famous book called How to Lie with Statistics).

But the real message is not statistics as some kind of new rational technique which guarantees prophetic success. Instead, it is self-awareness.


You need devices to help you retain self-awareness, to see things as they really are instead of ever-more elaborate stories or models. And humans typically find that very hard to do. I've got a few more things to say about Silver's book in that light.

 

Signal, Noise and Prediction

I'm now going to turn to Nate Silver's new book, The Signal and the Noise: Why So Many Predictions Fail-but Some Don't. Silver is the well-known political forecaster who parlayed his blog FiveThirtyEight into a prominent spot in the New York Times.

I didn't expect much when I bought it. I thought it would be one of those "my quantitative model explains the universe" books (and investment funds) which are so tiresome and common. The world, and especially the markets, are filled with quants who think all you need is Mathematica and some back issues of Econometrica to explain everything. They are usually overconfident, expert on code rather than decisions,and tend to blow up spectacularly like LTCM given time.

Nothing could be further from the truth in this case. The book massively exceeded expectations and turns out to be a thoughtful, mature and reflective. It is consistent with much of my experience and thinking, but I still learned a lot of things I didn't know. It's also fluent and well-written. I'd recommend it without hesitation, and I'll look at it in some detail.

The crux of the book, from someone known for his number-crunching models, is that there is no such thing as objective data-driven models, at least in human affairs.

The numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning. Like Caesar, we may construe them in self-serving ways that are detached from their objective reality. Data-driven predictions can succeed—and they can fail. It is when we deny our role in the process that the odds of failure rise. Before we demand more of our data, we need to demand more of ourselves.

The more information we have, the more we tend to screen out that which does not match our preconceptions. More information most often makes us narrower rather than wiser.

Alvin Toffler, writing in the book Future Shock in 1970, predicted some of the consequences of what he called “information overload.” He thought our defense mechanism would be to simplify the world in ways that confirmed our biases, even as the world itself was growing more diverse and more complex.

Information is no longer scarce, but much of it is not very useful.

Our biological instincts are not always very well adapted to the information-rich modern world. Unless we work actively to become aware of the biases we introduce, the returns to additional information may be minimal—or diminishing.

This does not mean we should just give up, or adopt lazy relativism. Instead, everything is approximate.

Some of you may be uncomfortable with a premise that I have been hinting at and will now state explicitly: we can never make perfectly objective predictions. They will always be tainted by our subjective point of view. But this book is emphatically against the nihilistic viewpoint that there is no objective truth. It asserts, rather, that a belief in the objective truth—and a commitment to pursuing it—is the first prerequisite of making better predictions. The forecaster’s next commitment is to realize that she perceives it imperfectly.

So what are the causes of failure to predict outcomes?

The most calamitous failures of prediction usually have a lot in common. We focus on those signals that tell a story about the world as we would like it to be, not how it really is. We ignore the risks that are hardest to measure, even when they pose the greatest threats to our well-being. We make approximations and assumptions about the world that are much cruder than we realize. We abhor uncertainty, even when it is an irreducible part of the problem we are trying to solve.

Indeed, experts have a particular tendency to ignore threats to their expertise. The rating agencies, for example, did not think through the possibility that default risk of various CDOs and CDO tranches might not be independent and uncorrelated.

The possibility of a housing bubble, and that it might burst, thus represented a threat to the ratings agencies’ gravy train. Human beings have an extraordinary capacity to ignore risks that threaten their livelihood, as though this will make them go away.

Our expectations about the future are riddled with blind spots, as anyone who has ever really thought about the policy process or had to predict events for a living - and been held accountable for it - knows.

We'll look at some other aspects of the book in more detail.

 

Is US Economic Growth Over?

Here is something I'll have to look at (from an NYT article):

The American economy is running on empty. That's the hypothesis put forward by Robert J. Gordon, an economist at Northwestern University. Let's assume for a moment that he's right. The political consequences would be enormous.

In his widely discussed National Bureau of Economic Research paper, "Is U.S. Economic Growth Over?" Gordon predicts a dark future of "epochal decline in growth from the U.S. record of the last 150 years." The greatest innovations, Gordon argues, are behind us, with little prospect for transformative change along the lines of the three previous industrial revolutions:

It is pretty gloomy.

Over most of human history, in Gordon's view, the world had minimal economic growth, if it had any at all - and "there is no guarantee that growth will continue indefinitely." Gordon's paper suggests instead that "the rapid progress made over the past 250 years could well turn out to be a unique episode in human history."

 

An open access version of The Gordon article is here, although I haven't read it yet. It sound similar to Tyler Cowen's arguments.