Rubik’s Cube Solver

This is pretty cool.

This is… wtf.

Encryption on John Oliver

Radical Wisdom for a Company, a School, a Life

Why is everyone so busy?

THE predictions sounded like promises: in the future, working hours would be short and vacations long. “Our grandchildren”, reckoned John Maynard Keynes in 1930, would work around “three hours a day”—and probably only by choice. Economic progress and technological advances had already shrunk working hours considerably by his day, and there was no reason to believe this trend would not continue. Whizzy cars and ever more time-saving tools and appliances guaranteed more speed and less drudgery in all parts of life. Social psychologists began to fret: whatever would people do with all their free time?

This has not turned out to be one of the world’s more pressing problems. Everybody, everywhere seems to be busy. In the corporate world, a “perennial time-scarcity problem” afflicts executives all over the globe, and the matter has only grown more acute in recent years, say analysts at McKinsey, a consultancy firm. These feelings are especially profound among working parents. As for all those time-saving gizmos, many people grumble that these bits of wizardry chew up far too much of their days, whether they are mouldering in traffic, navigating robotic voice-messaging systems or scything away at e-mail—sometimes all at once.

Tick, tock
Why do people feel so rushed? Part of this is a perception problem. On average, people in rich countries have more leisure time than they used to. This is particularly true in Europe, but even in America leisure time has been inching up since 1965, when formal national time-use surveys began. American men toil for pay nearly 12 hours less per week, on average, than they did 40 years ago—a fall that includes all work-related activities, such as commuting and water-cooler breaks. Women’s paid work has risen a lot over this period, but their time in unpaid work, like cooking and cleaning, has fallen even more dramatically, thanks in part to dishwashers, washing machines, microwaves and other modern conveniences, and also to the fact that men shift themselves a little more around the house than they used to.

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This post was linked from The Economist.

Report: artificial intelligence will cause “structural collapse” of law firms by 2030

Robots and artificial intelligence (AI) will dominate legal practice within 15 years, perhaps leading to the “structural collapse” of law firms, a report predicting the shape of the legal market has envisaged.

Civilisation 2030: The near future for law firms, by Jomati Consultants, foresees a world in which population growth is actually slowing, with “peak humanity” occurring as early as 2055, and ageing populations bringing a growth in demand for legal work on issues affecting older people.

This could mean more advice needed by healthcare and specialist construction companies on the building and financing of hospitals, and on pension investment businesses, as well as financial and regulatory work around the demographic changes to come; more age-related litigation, IP battles between pharmaceutical companies, and around so-called “geriatric-tech” related IP.

The report’s focus on the future of work contained the most disturbing findings for lawyers. Its main proposition is that AI is already close in 2014. “It is no longer unrealistic to consider that workplace robots and their AI processing systems could reach the point of general production by 2030… after long incubation and experimentation, technology can suddenly race ahead at astonishing speed.”

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This post was linked from Legal Futures.

I’ve actually already been replaced by a robot. But nobody noticed.

A guide to skiving

THE best way to understand a system is to look at it from the point of view of people who want to subvert it. Sensible bosses try to view their companies through the eyes of corporate raiders. Serious-minded politicians make a point of putting themselves in their opponents’ shoes. The same is true of the world of work in general: the best way to understand a company’s “human resources” is not to consult the department that bears that ugly name but to study the basic principles of one of the world’s most popular, if unrecognised, sciences: skiving.

The first principle of skiving (or shirking, as Americans call it) is always to appear hard at work. This is the ancient jacket-on-the-back-of-the-chair trick: leave a coat permanently on display so that a casual observer—a CEO practising “managing by walking around”, for example—will assume that you are the first to arrive and the last to leave. The skill of skiving is subtle: ensure you are somewhere else when the work is being allocated. Successful skivers never visibly shy away from work: confronted with the inevitable they make a point of looking extremely eager. This “theatre of enthusiasm” has fooled almost everyone. Policymakers bemoan the epidemic of overwork. But as Roland Paulsen, of Sweden’s Lund University, explains in “Empty Labour”, an example-packed new book, innumerable studies suggest that the average worker devotes between one-and-a-half and three hours a day to loafing.

The second principle is that information technology is both the slacker’s best friend and his deadliest enemy. The PC is custom-made for the indolent: you can give every impression of being hard at work when in fact you are doing your shopping, booking a holiday or otherwise frolicking in the cyber-waves. And thanks to mobile technology you can now continue to frolic while putting in face time in meetings. There is also a high-tech version of the jacket trick: program your e-mails to send themselves at half past midnight or 5.30am to give your managers the impression that you are a Stakhanovite.

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This post was linked from The Economist.

The third great wave

MOST PEOPLE ARE discomfited by radical change, and often for good reason. Both the first Industrial Revolution, starting in the late 18th century, and the second one, around 100 years later, had their victims who lost their jobs to Cartwright’s power loom and later to Edison’s electric lighting, Benz’s horseless carriage and countless other inventions that changed the world. But those inventions also immeasurably improved many people’s lives, sweeping away old economic structures and transforming society. They created new economic opportunity on a mass scale, with plenty of new work to replace the old.

A third great wave of invention and economic disruption, set off by advances in computing and information and communication technology (ICT) in the late 20th century, promises to deliver a similar mixture of social stress and economic transformation. It is driven by a handful of technologies—including machine intelligence, the ubiquitous web and advanced robotics—capable of delivering many remarkable innovations: unmanned vehicles; pilotless drones; machines that can instantly translate hundreds of languages; mobile technology that eliminates the distance between doctor and patient, teacher and student. Whether the digital revolution will bring mass job creation to make up for its mass job destruction remains to be seen.

Powerful, ubiquitous computing was made possible by the development of the integrated circuit in the 1950s. Under a rough rule of thumb known as Moore’s law (after Gordon Moore, one of the founders of Intel, a chipmaker), the number of transistors that could be squeezed onto a chip has been doubling every two years or so. This exponential growth has resulted in ever smaller, better and cheaper electronic devices. The smartphones now carried by consumers the world over have vastly more processing power than the supercomputers of the 1960s.

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This post was linked from The Economist.

Automated hypothesis generation: Computer says “try this”

APPLES, mushrooms and pork sounds a promising recipe for a kebab, but the average barbecuer might balk at adding strawberries. According to John Gordon of IBM, however, the result is delicious. Dr Gordon is one of the leaders of that firm’s cognitive-computing team, responsible for a machine called Watson which is able to digest and analyse large amounts of English text and then draw inferences from it. When, in March, Watson was fed reams of recipes and texts about food, it reasoned that these four ingredients would complement each other, based on their sharing a number of flavoursome chemical compounds. And Dr Gordon, at least, thinks Watson’s suggestion is a winner.

Devising new recipes sounds a trivial use for a multimillion-dollar piece of kit. But Dr Gordon’s culinary experiment neatly demonstrates the idea of automated hypothesis generation—and the possible uses of that are certainly not trivial. More than 90 groups of scientists are now developing hypothesis-generation software. They hope to use it not on recipe books but on the vast corpus of scientific literature (by one tally at least 50m scientific papers) that has piled up in public databases.

The power of the technique was demonstrated by research published in August by Olivier Lichtarge of Baylor College of Medicine, in Houston, Texas, and his colleagues. In collaboration with Dr Gordon’s group, they employed it to hunt for proteins called kinases that activate another protein, p53, which curbs the growth of cancers. They used the software to read the abstracts of 186,879 papers and produced a list of the most promising kinases for experiments. The twist was that the papers in question were all published before 2003. That meant Dr Lichtarge could check to see if the Watson-based approach came to the same conclusions as those arrived at by human researchers over the subsequent ten years. And it did. Of the top nine kinases the software picked, seven have subsequently been shown to activate p53.

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This post was linked from The Economist.

Practice makes imperfect

“THE harder I practise, the luckier I get,” said Gary Player, one of history’s greatest golfers. And it is a widespread belief that experienced professionals are a lot better than neophytes. But is that true of fund managers? A new study suggests that the answer is distinctly mixed.

The paper examined the records of 2,846 American mutual funds between the start of 1996 and the end of 2008, overseen by 1,825 managers (some looked after more than one fund). Turnover was high; fewer than a quarter of the managers lasted more than five years. Just 195 of them lasted a decade.

Unsurprisingly, those managers who were poor performers in their early years were more likely to lose their jobs. In their last year in charge of their funds, these neophytes underperformed the veterans. However, the veterans did not outperform consistently; what they did do was avoid periods where they did particularly badly. The authors concluded that “even long-term managers show no ability to beat the market on a risk-adjusted basis. The key to a long career in the mutual-fund industry seems to be related more to avoiding underperformance than to achieving superior performance.”

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This post was linked from The Economist.

Decluttering the company

PETER DRUCKER once observed that, “Much of what we call management consists of making it difficult for people to work.” Nine years after the management guru’s death, his remark is truer than ever: employees often have to negotiate a mass of clutter—from bulging inboxes to endless meetings and long lists of objectives to box-tick—before they can focus on their real work. For the past 50 years manufacturers have battled successfully to streamline their factory floors and make them “lean”. Today, businesses of all types need to do the same in their offices.

The most debilitating form of clutter is organisational complexity. The Boston Consulting Group (BCG) has been tracking this for a representative sample of companies in the United States and Europe since 1955 (when the Fortune 500 list was created). BCG defines complexity broadly to include everything from tiers of management to the numbers of co-ordinating bodies and corporate objectives. It reckons that, overall, the complexity of organisations has increased sixfold since then. There has been an explosion of “performance imperatives”: in 1955 firms typically embraced between four and seven of them; today, as they strain themselves to be kind to the environment, respectful of diversity, decent to their suppliers and the like, it is 25-40.

A second form of clutter is meetings. Bain & Company, another consulting firm, studied a sample of big firms, finding that their managers spent 15% of their time in meetings, a share that has risen every year since 2008. Many of these meetings have no clear purpose. The higher up you go, the worse it is. Senior executives spend two full days a week in meetings with three or more colleagues. In 22% of these meetings the participants sent three or more e-mails for every half an hour they spent sitting in the room.

These e-mails constitute the third form of clutter. Bain estimates that the number of external communications that managers receive has increased from about 1,000 a year in 1970 to around 30,000 today. Every message imposes a “time tax” on the people at either end of it; and these taxes can spiral out of control unless they are managed.

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This post was linked from The Economist.

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