Wednesday, July 3, 2013
Tuesday, July 2, 2013
How algorithms rule the world ...............
The financial sector has long used algorithms to predict market fluctuations, but they can also help police identify crime hot spots or online shops target their customers. Photograph: Danil Melekhin/Getty Images
On 4 August 2005, the police department of Memphis, Tennessee, made so many arrests over a three-hour period that it ran out of vehicles to transport the detainees to jail. Three days later, 1,200 people had been arrested across the city – a new police department record. Operation Blue Crush was hailed a huge success.
Larry Godwin, the city's new police director, quickly rolled out the scheme and by 2011 crime across the city had fallen by 24%. When it was revealed Blue Crush faced budget cuts earlier this year, there was public outcry. "Crush" policing is now perceived to be so successful that it has reportedly been mimicked across the globe, including in countries such as Poland and Israel. In 2010, it was reported that two police forces in the UK were using it, but their identities were not revealed.
Crush stands for "Criminal Reduction Utilising Statistical History". Translated, it means predictive policing. Or, more accurately, police officers guided by algorithms. A team of criminologists and data scientists at the University of Memphis first developed the technique using IBM predictive analytics software. Put simply, they compiled crime statistics from across the city over time and overlaid it with other datasets – social housing maps, outside temperatures etc – then instructed algorithms to search for correlations in the data to identify crime "hot spots". The police then flooded those areas with highly targeted patrols.
"It's putting the right people in the right places on the right day at the right time," said Dr Richard Janikowski, an associate professor in the department of criminology and criminal justice at the University of Memphis, when the scheme launched. But not everyone is comfortable with the idea. Some critics have dubbed it "Minority Report" policing, in reference to the sci-fi film in which psychics are used to guide a "PreCrime" police unit.
The use of algorithms in policing is one example of their increasing influence on our lives. And, as their ubiquity spreads, so too does the debate around whether we should allow ourselves to become so reliant on them – and who, if anyone, is policing their use. Such concerns were sharpened further by the continuing revelations about how the US National Security Agency (NSA) has been using algorithms to help it interpret the colossal amounts of data it has collected from its covert dragnet of international telecommunications.
"For datasets the size of those the NSA collect, using algorithms is the only way to operate for certain tasks," says James Ball, the Guardian's data editor and part of the paper's NSA Files reporting team. "The problem is how the rules are set: it's impossible to do this perfectly. If you're, say, looking for terrorists, you're looking for something very rare. Set your rules too tight and you'll miss lots of, probably most, potential terror suspects. But set them more broadly and you'll drag lots of entirely blameless people into your dragnet, who will then face further intrusion or even formal investigation. We don't know exactly how the NSA or GCHQ use algorithms – or how extensively they're applied. But we do know they use them, including on the huge data trawls revealed in the Guardian."
From dating websites and City trading floors, through to online retailing and internet searches (Google's search algorithm is now a more closely guarded commercial secret than the recipe for Coca-Cola), algorithms are increasingly determining our collective futures. "Bank approvals, store cards, job matches and more all run on similar principles," says Ball. "The algorithm is the god from the machine powering them all, for good or ill."
Most observers blame the 'flash crash' of May 2010 on the use of algorithms to perform high-frequency trading. Photograph: Spencer Platt/Getty Images
But what is an algorithm? Dr Panos Parpas, a lecturer in the quantitative analysis and decision science ("quads") section of the department ofcomputing at Imperial College London, says that wherever we use computers, we rely on algorithms: "There are lots of types, but algorithms, explained simply, follow a series of instructions to solve a problem. It's a bit like how a recipe helps you to bake a cake. Instead of having generic flour or a generic oven temperature, the algorithm will try a range of variations to produce the best cake possible from the options and permutations available."
Parpas stresses that algorithms are not a new phenomenon: "They've been used for decades – back to Alan Turing and the codebreakers, and beyond – but the current interest in them is due to the vast amounts of data now being generated and the need to process and understand it. They are now integrated into our lives. On the one hand, they are good because they free up our time and do mundane processes on our behalf. The questions being raised about algorithms at the moment are not about algorithms per se, but about the way society is structured with regard to data use and data privacy. It's also about how models are being used to predict the future. There is currently an awkward marriage between data and algorithms. As technology evolves, there will be mistakes, but it is important to remember they are just a tool. We shouldn't blame our tools."
The "mistakes" Parpas refers to are events such as the "flash crash" of 6 May 2010, when the Dow Jones industrial average fell 1,000 points in just a few minutes, only to see the market regain itself 20 minutes later. The reasons for the sudden plummet has never been fully explained, but most financial observers blame a "race to the bottom" by the competing quantitative trading (quants) algorithms widely used to perform high-frequency trading. Scott Patterson, a Wall Street Journal reporter and author of The Quants, likens the use of algorithms on trading floors to flying a plane on autopilot. The vast majority of trades these days are performed by algorithms, but when things go wrong, as happened during the flash crash, humans can intervene.
"By far the most complicated algorithms are to be found in science, where they are used to design new drugs or model the climate," says Parpas. "But they are done within a controlled environment with clean data. It is easy to see if there is a bug in the algorithm. The difficulties come when they are used in the social sciences and financial trading, where there is less understanding of what the model and output should be, and where they are operating in a more dynamic environment. Scientists will take years to validate their algorithm, whereas a trader has just days to do so in a volatile environment."
Most investment banks now have a team of computer science PhDs coding algorithms, says Parpas, who used to work on such a team. "With City trading, everyone is running very similar algorithms," he says. "They all follow each other, meaning you get results such as the flash crash. They use them to speed up the process and to break up big trades to disguise them from competitors when a big investment is being made. It's an on-going, live process. They will run new algorithms for a few days to test them before letting them loose with real money. In currency trading, an algorithm lasts for about two weeks before it is stopped because it is surpassed by a new one. In equities, which is a less complicated market, they will run for a few months before a new one replaces them. It takes a day or two to write a currency algorithm. It's hard to find out information about them because, for understandable reasons, they don't like to advertise when they are successful. Goldman Sachs, though, has a strong reputation across the investment banks for having a brilliant team of algorithm scientists. PhDs students in this field will usually be employed within a few months by an investment bank."
The idea that the world's financial markets – and, hence, the wellbeing of our pensions, shareholdings, savings etc – are now largely determined by algorithmic vagaries is unsettling enough for some. But, as the NSA revelations exposed, the bigger questions surrounding algorithms centre on governance and privacy. How are they being used to access and interpret "our" data? And by whom?
Dr Ian Brown, the associate director of Oxford University's Cyber Security Centre, says we all urgently need to consider the implications of allowing commercial interests and governments to use algorithms to analyse our habits: "Most of us assume that 'big data' is munificent. The laws in the US and UK say that much of this [the NSA revelations] is allowed, it's just that most people don't realise yet. But there is a big question about oversight. We now spend so much of our time online that we are creating huge data-mining opportunities."
Algorithms can run the risk of linking some racial groups to particular crimes. Photograph: Alamy
Brown says that algorithms are now programmed to look for "indirect, non-obvious" correlations in data. "For example, in the US, healthcare companies can now make assessments about a good or bad insurance risk based, in part, on the distance you commute to work," he says. "They will identity the low-risk people and market their policies at them. Over time, this creates or exacerbates societal divides. Professor Oscar Gandy, at the University of Pennsylvania, has done research into 'secondary racial discrimination', whereby credit and health insurance, which relies greatly on postcodes, can discriminate against racial groups because they happen to live very close to other racial groups that score badly."
Brown harbours similar concerns over the use of algorithms to aid policing, as seen in Memphis where Crush's algorithms have reportedly linked some racial groups to particular crimes: "If you have a group that is disproportionately stopped by the police, such tactics could just magnify the perception they have of being targeted."
Viktor Mayer-Schönberger, professor of internet governance and regulation at the Oxford Internet Institute, also warns against humans seeing causation when an algorithm identifies a correlation in vast swaths of data. "This transformation presents an entirely new menace: penalties based on propensities," he writes in his new book, Big Data: A Revolution That Will Transform How We Live, Work and Think, which is co-authored by Kenneth Cukier, the Economist's data editor. "That is the possibility of using big-data predictions about people to judge and punish them even before they've acted. Doing this negates ideas of fairness, justice and free will. In addition to privacy and propensity, there is a third danger. We risk falling victim to a dictatorship of data, whereby we fetishise the information, the output of our analyses, and end up misusing it. Handled responsibly, big data is a useful tool of rational decision-making. Wielded unwisely, it can become an instrument of the powerful, who may turn it into a source of repression, either by simply frustrating customers and employees or, worse, by harming citizens."
Mayer-Schönberger presents two very different real-life scenarios to illustrate how algorithms are being used. First, he explains how the analytics team working for US retailer Target can now calculate whether a woman is pregnant and, if so, when she is due to give birth: "They noticed that these women bought lots of unscented lotion at around the third month of pregnancy, and that a few weeks later they tended to purchase supplements such as magnesium, calcium and zinc. The team ultimately uncovered around two dozen products that, used as proxies, enabled the company to calculate a 'pregnancy prediction' score for every customer who paid with a credit card or used a loyalty card or mailed coupons. The correlations even let the retailer estimate the due date within a narrow range, so it could send relevant coupons for each stage of the pregnancy."
Harmless targeting, some might argue. But what happens, as has already reportedly occurred, when a father is mistakenly sent nappy discount vouchers instead of his teenage daughter whom a retailer has identified is pregnant before her own father knows?
Mayer-Schönberger's second example on the reliance upon algorithms throws up even more potential dilemmas and pitfalls: "Parole boards in more than half of all US states use predictions founded on data analysis as a factor in deciding whether to release somebody from prison or to keep him incarcerated."
Norah Jones: a specially developed algorithm predicted that her debut album contained a disproportionately high number of hit records. Photograph: Olycom SPA/Rex Features
Christopher Steiner, author of Automate This: How Algorithms Came to Rule Our World, has identified a wide range of instances where algorithms are being used to provide predictive insights – often within the creative industries. In his book, he tells the story of a website developer called Mike McCready, who has developed an algorithm to analyse and rate hit records. Using a technique called advanced spectral deconvolution, the algorithm breaks up each hit song into its component parts – melody, tempo, chord progression and so on – and then uses that to determine common characteristics across a range of No 1 records. McCready's algorithm correctly predicted – before they were even released – that the debut albums by both Norah Jones and Maroon 5 contained a disproportionately high number of hit records.
The next logical step – for profit-seeking record companies, perhaps – is to use algorithms to replace the human songwriter. But is that really an attractive proposition? "Algorithms are not yet writing pop music," says Steiner. He pauses, then laughs. "Not that we know of, anyway. If I were a record company executive or pop artist, I wouldn't tell anyone if I'd had a number one written by an algorithm."
Steiner argues that we should not automatically see algorithms as a malign influence on our lives, but we should debate their ubiquity and their wide range of uses. "We're already halfway towards a world where algorithms run nearly everything. As their power intensifies, wealth will concentrate towards them. They will ensure the 1%-99% divide gets larger. If you're not part of the class attached to algorithms, then you will struggle. The reason why there is no popular outrage about Wall Street being run by algorithms is because most people don't yet know or understand it."
But Steiner says we should welcome their use when they are used appropriately to aid and speed our lives. "Retail algorithms don't scare me," he says. "I find it useful when Amazon tells me what I might like. In the US, we know we will not have enough GP doctors in 15 years, as not enough are being trained. But algorithms can replace many of their tasks. Pharmacists are already seeing some of their prescribing tasks replaced by algorithms. Algorithms might actually start to create new, mundane jobs for humans. For example, algorithms will still need a human to collect blood and urine samples for them to analyse."
There can be a fine line, though, between "good" and "bad" algorithms, he adds: "I don't find the NSA revelations particularly scary. At the moment, they just hold the data. Even the best data scientists would struggle to know what to do with all that data. But it's the next step that we need to keep an eye on. They could really screw up someone's life with a false prediction about what they might be up to."
Saturday, June 29, 2013
Ustad Rais Khan of Indore/Pakistan .....
I deserve better access to Indian fans: Rais Khan
Malini Nair | March 17, 2012
Even at 74, Rais Khan is every inch the flamboyant genius ustad with a remarkable knack for setting off controversies. Lahore has been home for him for two decades but this is where his music and heart lie.
He is the last of his tribe, the ustads with larger-than-life personalities who are impetuous, stylish, opinionated, acerbic and with fiery musical talents. Ustad Rais Khan, in fact, lives up to his name. There is nothing small or retiring about the sitar wizard who moved to Pakistan in 1986 and has since lived in a state of longing for his fan base back home in India.
"This is the gaddh (home) of classical music. I need to play here. I say give me a visa for a year, five years. I was born in Indore, grew up in Bhopal, studied at St Xavier's in Mumbai, got my taleem (education) here. Meri mitti yahan ki hai (I belong to this soil) Surely I don't deserve this, " he says querulously. 'This' is the never-ending visa battle the ustad has to wage every time he comes to India, which is often for half a year.
There is a fair chance that almost every Indian has heard Rais Khan play sitar. Not on the concert stage but as keen - or even chance listeners - of Hindi film classics. Unless you lead a hermit's life, you are likely to have heard the bright sitar strains of Baiyaan na dharo or Nainon mein badra chhaaye in a passing auto or at the istriwallah's table. And that is no mean achievement for a high-brow musician. From OP Nayyar to Madan Mohan, he has played for some of the most famous composers of Bollywood of the '60s and '70s.
"Everyone says classical music is up there, I say film music of those years was right next to it, " he says. The ustad is sitting at Rikhi Ram Music Shop in Delhi's Connaught Place getting his sitar sorted. Two months ago, instrument maker Sanjay Rikhi Ram managed to rig up a sitar that, the ustad says, is an instrument he has been searching for for 50 years.
The last few months have been good for the ustad. He managed to be 'home' for longer than visa red tape would allow him, performed at about four concerts, and is being invested next Thursday with the Pandit Amarnath Vaggeykar Samman instituted in the memory of Ustad Amir Khan's foremost disciple. "Bahut badi baat hai (it's a big thing)... for someone from Pakistan, " he adds.
His angst is easy to understand. Of his 100 listeners, says his very talented son Farhan, only five live in Pakistan. The rest are here. It is a limited but loyal fan base which never really grew because of his absence from the concert stage. Why did he move? That is a question which gets thrown at him a lot. "I ask aisa koi hai jisne mohabbat nahin ki (is there anyone who hasn't fallen in love)? " he says referring to the fact that he crossed the border for his Pakistani wife, Bilquees Khanum, and the mother of his two sons.
His move to Lahore had been fraught to say the least - he was said to have alleged a bias against Muslim artistes in India (he now denies this). The bitterness this caused swelled and survived over two decades and soured for good his relationship with the Indian music fraternity. There was even a call to prevent him from singing in Mumbai recently.
And then there is the unending, very acerbic and publicly fought gharana feud between him and the family of Ustad Vilayat Khan (his maternal uncle) over the authorship of the gayaki (singing) style of playing the sitar. In January, at a concert in Delhi, Khan had in a prelude to his performance spoken of how he evolved the gayaki style of playing his sitar. Vilayat Khan's daughter, Yaman, present in the audience had publicly berated him for appropriating the credit for what she maintained was her father's gift to music.
"I belong to Mewat gharana and I play the style my father Ustad Mohammed Khansaheb taught me. Mujhe aur kisi se matlab nahin hain (I'm not bothered about anyone else), " he says imperiously but this display of diplomacy is short lived. "Likho, " he says listing the names of his ancestors going back to the Hassu-Haddu-Nathu Khan triumvirate who are said to have founded khayal singing. "It takes three-four generations and more than 100 years for a gharana to be formed. Otherwise, who is to stop Bombay, Calcutta, Patna, Hyderabad gharanas?" he asks, bursting into an infectious cackle at his own joke.
His impetuousness has caused him more trouble than he would care to remember, including a falling out with the legendary Madan Mohan, a loss for music lovers because they were a crackling creative team (Khan's vocalised playing style worked wonderfully for movie tunes). Sitar was a constant base to Mohan's film tunes so much so that in many of his songs it is hard to figure out if the music director showcased Rais Khan's brilliance or the sitarist raised the tunes to greater heights (see box). Madan Mohan's son Sanjeev Kohli says that after the two men fell out over payment issues, his father never again used the sitar in his songs.
But his concert style is radically different from that of his contemporaries - Pandit Ravi Shankar and the late Vilayat Khan. There is a lot of banter, questions and chit chatting with the audiences, which is unheard of in sombre classical concerts. "Kyon bhai, pasand nahin aaya?" he calls out to a youngster scurrying out of the IIC auditorium last week in the middle of a lovely Charukeshi raga. And after playing a brilliant gamak, he peers into the hall and asks: "Kaisa laga (how was it)? "
He is defiant about his informal concert style. "Bana rehna chahiye (have to remain connected ). I am playing to connoisseurs so I need to ask 'Taan saaf hai na? (Is the phrase clear)' Arre, if they say no I can always rectify myself, " he says.
His sisters' home in Mumbai is his anchor in India. In Delhi, he has been frequenting the Rikhi Ram music shop which he has had a connection with since the patriarch of the business set up shop. "He has a unique style, his music is vocal, open and has unique tonal variations, bright, sharp and very sweet to hear, " points out Rikhi Ram, himself an accomplished musician.
SITAR SCORES
Ham hain mataye kucha | 'Dastak' | 1970
Aaj socha to aanso bhar aaye | 'Hanste Zakhm' | 1973
Maine rang li aaj chunariya | 'Dulhan Ek Raat Ki' | 1967
Nainon mein badra chhaaye | 'Mera Saaya' | 1966
Tumhari zulf ke saaye main | 'Naunihal' | 1967
Baiyaan na dharo | 'Dastak' | 1970
Meri ankhon se koyi | 'Pooja ke Phool' | 1964
The 'Pakeezah' theme | 1972
He is the last of his tribe, the ustads with larger-than-life personalities who are impetuous, stylish, opinionated, acerbic and with fiery musical talents. Ustad Rais Khan, in fact, lives up to his name. There is nothing small or retiring about the sitar wizard who moved to Pakistan in 1986 and has since lived in a state of longing for his fan base back home in India.
"This is the gaddh (home) of classical music. I need to play here. I say give me a visa for a year, five years. I was born in Indore, grew up in Bhopal, studied at St Xavier's in Mumbai, got my taleem (education) here. Meri mitti yahan ki hai (I belong to this soil) Surely I don't deserve this, " he says querulously. 'This' is the never-ending visa battle the ustad has to wage every time he comes to India, which is often for half a year.
There is a fair chance that almost every Indian has heard Rais Khan play sitar. Not on the concert stage but as keen - or even chance listeners - of Hindi film classics. Unless you lead a hermit's life, you are likely to have heard the bright sitar strains of Baiyaan na dharo or Nainon mein badra chhaaye in a passing auto or at the istriwallah's table. And that is no mean achievement for a high-brow musician. From OP Nayyar to Madan Mohan, he has played for some of the most famous composers of Bollywood of the '60s and '70s.
"Everyone says classical music is up there, I say film music of those years was right next to it, " he says. The ustad is sitting at Rikhi Ram Music Shop in Delhi's Connaught Place getting his sitar sorted. Two months ago, instrument maker Sanjay Rikhi Ram managed to rig up a sitar that, the ustad says, is an instrument he has been searching for for 50 years.
The last few months have been good for the ustad. He managed to be 'home' for longer than visa red tape would allow him, performed at about four concerts, and is being invested next Thursday with the Pandit Amarnath Vaggeykar Samman instituted in the memory of Ustad Amir Khan's foremost disciple. "Bahut badi baat hai (it's a big thing)... for someone from Pakistan, " he adds.
His angst is easy to understand. Of his 100 listeners, says his very talented son Farhan, only five live in Pakistan. The rest are here. It is a limited but loyal fan base which never really grew because of his absence from the concert stage. Why did he move? That is a question which gets thrown at him a lot. "I ask aisa koi hai jisne mohabbat nahin ki (is there anyone who hasn't fallen in love)? " he says referring to the fact that he crossed the border for his Pakistani wife, Bilquees Khanum, and the mother of his two sons.
His move to Lahore had been fraught to say the least - he was said to have alleged a bias against Muslim artistes in India (he now denies this). The bitterness this caused swelled and survived over two decades and soured for good his relationship with the Indian music fraternity. There was even a call to prevent him from singing in Mumbai recently.
And then there is the unending, very acerbic and publicly fought gharana feud between him and the family of Ustad Vilayat Khan (his maternal uncle) over the authorship of the gayaki (singing) style of playing the sitar. In January, at a concert in Delhi, Khan had in a prelude to his performance spoken of how he evolved the gayaki style of playing his sitar. Vilayat Khan's daughter, Yaman, present in the audience had publicly berated him for appropriating the credit for what she maintained was her father's gift to music.
"I belong to Mewat gharana and I play the style my father Ustad Mohammed Khansaheb taught me. Mujhe aur kisi se matlab nahin hain (I'm not bothered about anyone else), " he says imperiously but this display of diplomacy is short lived. "Likho, " he says listing the names of his ancestors going back to the Hassu-Haddu-Nathu Khan triumvirate who are said to have founded khayal singing. "It takes three-four generations and more than 100 years for a gharana to be formed. Otherwise, who is to stop Bombay, Calcutta, Patna, Hyderabad gharanas?" he asks, bursting into an infectious cackle at his own joke.
His impetuousness has caused him more trouble than he would care to remember, including a falling out with the legendary Madan Mohan, a loss for music lovers because they were a crackling creative team (Khan's vocalised playing style worked wonderfully for movie tunes). Sitar was a constant base to Mohan's film tunes so much so that in many of his songs it is hard to figure out if the music director showcased Rais Khan's brilliance or the sitarist raised the tunes to greater heights (see box). Madan Mohan's son Sanjeev Kohli says that after the two men fell out over payment issues, his father never again used the sitar in his songs.
But his concert style is radically different from that of his contemporaries - Pandit Ravi Shankar and the late Vilayat Khan. There is a lot of banter, questions and chit chatting with the audiences, which is unheard of in sombre classical concerts. "Kyon bhai, pasand nahin aaya?" he calls out to a youngster scurrying out of the IIC auditorium last week in the middle of a lovely Charukeshi raga. And after playing a brilliant gamak, he peers into the hall and asks: "Kaisa laga (how was it)? "
He is defiant about his informal concert style. "Bana rehna chahiye (have to remain connected ). I am playing to connoisseurs so I need to ask 'Taan saaf hai na? (Is the phrase clear)' Arre, if they say no I can always rectify myself, " he says.
His sisters' home in Mumbai is his anchor in India. In Delhi, he has been frequenting the Rikhi Ram music shop which he has had a connection with since the patriarch of the business set up shop. "He has a unique style, his music is vocal, open and has unique tonal variations, bright, sharp and very sweet to hear, " points out Rikhi Ram, himself an accomplished musician.
SITAR SCORES
Ham hain mataye kucha | 'Dastak' | 1970
Aaj socha to aanso bhar aaye | 'Hanste Zakhm' | 1973
Maine rang li aaj chunariya | 'Dulhan Ek Raat Ki' | 1967
Nainon mein badra chhaaye | 'Mera Saaya' | 1966
Tumhari zulf ke saaye main | 'Naunihal' | 1967
Baiyaan na dharo | 'Dastak' | 1970
Meri ankhon se koyi | 'Pooja ke Phool' | 1964
The 'Pakeezah' theme | 1972
The Ustad plays Raag Nand Kalyan......
Flowers are a kind of F-word ............
FLOWERS THAT CAN SPEAK
Applied Fashion: real or fake, flowers are nature’s walk-in wardrobe. For Rebecca Willis they burst with ready-to-wear allure
From INTELLIGENT LIFE magazine, July/August 2013
A curious thing happened to me not long ago. As I walked along a rather stuffy, upmarket street in central London, complete strangers smiled at me. Odder still, some stopped and spoke to me, and made complimentary remarks. It was like being in a twisted version of a Lynx advert. I was suddenly eye-catching and attractive to both men and women. And this is why: I was carrying an armful of enormous, glorious, in-full-bloom hydrangeas. Each flower-head was about six inches across, in shades from lovat green through powder-blue to inky violet. They were lush and bursting with life, a beautiful blast of nature in the middle of the city. And people could not resist them.
Even if we don’t talk to them, flowers communicate with us. People respond to them with lit-up faces and the "aaah" noises they usually reserve for babies and puppies. A coiffed dowager-type told me they made her want to dance; a Vietnamese man said that in his country hydrangeas were special. I love flowers, but I’d always thought Interflora’s "say it with flowers" slogan was really about levering money out of repressed males who couldn’t articulate their feelings. On that day, though, over the course of a few hundred yards, I realised that flowers can speak, and that what they say makes people happy.
Flowers are the most natural form of adornment. Nature’s jewellery, if you like. People have probably been plucking them and sticking them in their hair or behind an ear since, well, since people began. They show no signs of stopping. Flower-printed fabrics are ubiquitous in the clothing business, but I’m talking here about three-dimensional blooms. Last year, Lady Gaga wore a full-face helmet made of flowers. In 2007 Alexander McQueen showed his Sarabande dress, so embroidered with artificial and fresh flowers it looked like it needed a full-time gardener. Chanel has put tweed flowers on shoes, Prada suede ones. Lulu Guinness has made handbags that look like flower pots with a single large silken bloom on top. Flowers appear on hats and fascinators at weddings and the races, on flip-flops down at the beach and on hair-slides in kindergarten.
Now that artificial flowers have become so realistic, the attitude to them has changed and we’re less snobbishly resistant to them. Perhaps that’s one reason fake flowers now feature so much in what we wear. They still keep to their rightful seasons, though. The fashion industry has failed, despite repeated
efforts, to get us to wear even prints of flowers in winter. And they remain female territory: although Paul Smith has successfully appropriated floral prints for men’s shirts, you don’t often see men wearing real (or fake) flowers unless they’re on a catwalk or in morning dress. Even if they’re carrying a bunch on Valentine’s or Mother’s Day, they tend to have that self-conscious, these-are-for-someone-else look on their face.
efforts, to get us to wear even prints of flowers in winter. And they remain female territory: although Paul Smith has successfully appropriated floral prints for men’s shirts, you don’t often see men wearing real (or fake) flowers unless they’re on a catwalk or in morning dress. Even if they’re carrying a bunch on Valentine’s or Mother’s Day, they tend to have that self-conscious, these-are-for-someone-else look on their face.
The story of Western art has a trail of blossoms running through it: Botticelli’s possibly pregnant Primavera, Rembrandt’s portraits of his wife Saskia as Flora, goddess of flowers and spring, Manet’s Olympia, who has a bloom the same colour as her lips behind her left ear, Georgia O’Keeffe’s overtly sexual flower paintings, which depict petals like intimate folds of flesh. Flowers and fertility have always gone together, and that’s not symbolism, that’s biological fact. A flower is designed to attract pollinators with its colour and smell, and so aid reproduction. Fashion would be mad not to make use of such powerful, ready-made allure—often to the same end. In paintings of Adam and Eve there are images of fruit rather than flowers: the Fall happened in the Fall, when there were apples on the trees. Flowers are about both innocence and sexual promise, fruit is its fulfilment.
If you think about the sex-life of flowers for too long—and you might say I have—it begins to feel almost uncomfortably explicit to wear them. I don’t want to be part of the sexualisation of the modern world, but I am starting to see my stroll along the street with those gorgeous hydrangeas in a different light. They were pumping out fertility signals with the power of a radio beacon. It may be subliminal, but no wonder people paid attention. Now I know why they put a smile on people’s faces: flowers are a kind of F-word.
Rebecca Willis is our associate editor and a former travel editor of Vogue
Illustration Bill Brown
Thursday, June 27, 2013
"Beijing 2008" by Chinese-Canadian artist Liu Yi
P
ainting "Beijing 2008" by Chinese-Canadian artist Liu Yi.
The woman with the tattoos on her back is China. On the left, focused intensely on the game, is Japan. The one with the shirt and head cocked to the side is America. Lying provocatively on the floor is Russia. And the little girl standing to the side is Taiwan.
This painting, named “Beijing 2008”, has been the subject of much discussion in the west as well as on the internet. What’s interesting is that this painting is called “Beijing 2008”, yet it depicts four women playing mahjong, and conceals a wealth of meaning within…
China’s visible set of tiles “East Wind” has a dual meaning. First, it signifies China’s revival as a world power. Second, it signifies the military might and weaponry that China possesses has already been placed on the table. On one hand, China appears to be in a good position, but we cannot see the rest of her hand. Additionally, she is also handling some hidden tiles below the table.
America looks confident, but is glancing at Taiwan, trying to read something off of Taiwan’s expression, and at the same time seems to be hinting something at Taiwan.
Russia appears to be disinterested in the game, but this is far from the truth. One foot hooks coyly at America, while her hand passes a hidden tile to China, both countries can be said to be exchanging benefits in secret. Japan is all seriousness while staring at her own set of tiles, and is oblivious to the actions of the others in her self-focused state.
Taiwan wears a traditional red slip, symbolizing that she is the true heir of Chinese culture and civilization. In one hand she has a bowl of fruit, and in the other, a paring knife. Her expression as she stares at China is full of anger, sadness, and hatred, but to no avail; unless she enters the game, no matter who ends up as the victor, she is doomed to a fate of serving fruit.
Outside the riverbank is darkened by storm clouds, suggesting the high tension between the two nations is dangerously explosive. The painting hanging on the wall is also very meaningful; Mao’s face, but with Chiang Kai Shek’s bald head, and Sun Yat-Sen’s mustache.
The four women’s state of undress represent the situation in each country. China is naked on top, clothed with a skirt and underwear on the bottom. America wears a bra and a light jacket, but is naked on the bottom. Russia has only her underwear left. Japan has nothing left.
At first glance, America appears to be most composed and seems to be the best position, as all the others are in various states of nakedness. However, while America may look radiant, her vulnerability has already been exposed. China and Russia may look naked, yet their key private parts remain hidden.
If the stakes of this game is that the loser strips off a piece of clothing, then if China loses, she will be in the same state as Russia (similar to when the USSR dissolved). If America loses, she also ends up in the same state as Russia. If Russia loses, she loses all. Japan has already lost everything.
Russia seems to be a mere “filler” player, but in fact is exchanging tiles with China. The real “filler” player is Japan, for Japan has nothing more to lose, and if she loses just once more she is immediately out of the game.
America may look like she is in the best position, but in fact is in a lot of danger, if she loses this round, she will give up her position as a world power. Russia is the most sinister, playing along with both sides, much like when China was de-occupied, she leaned towards the USSR and then towards America; as she did not have the ability to survive on her own, she had to weave between both sides in order to survive and develop.
There are too many of China’s tiles that we cannot see. Perhaps suggesting that China has several hidden aces? Additionally China is also exchanging tiles with Russia, while America can only guess from Taiwan’s expression of what actions have transpired between Russia and China. Japan on the other hand is completely oblivious, still focused solely on her own set of tiles.
Taiwan stares coldly at the game from aside. She sees everything that the players at the table are doing, she understands everything that is going on. But she doesn’t have the means or permission to join the game, she isn’t even given the right to speak. Even if she has a dearth of complaints, she cannot voice it to anyone, all she can do is to be a good page girl, and bring fresh fruit to the victor.
The final victor lies between China and America, this much is apparent. But look closely; while America is capable, they are playing Chinese Mahjong, not Western Poker. Playing by the rules of China, how much chance at victory does America really have?
This painting, named “Beijing 2008”, has been the subject of much discussion in the west as well as on the internet. What’s interesting is that this painting is called “Beijing 2008”, yet it depicts four women playing mahjong, and conceals a wealth of meaning within…
China’s visible set of tiles “East Wind” has a dual meaning. First, it signifies China’s revival as a world power. Second, it signifies the military might and weaponry that China possesses has already been placed on the table. On one hand, China appears to be in a good position, but we cannot see the rest of her hand. Additionally, she is also handling some hidden tiles below the table.
America looks confident, but is glancing at Taiwan, trying to read something off of Taiwan’s expression, and at the same time seems to be hinting something at Taiwan.
Russia appears to be disinterested in the game, but this is far from the truth. One foot hooks coyly at America, while her hand passes a hidden tile to China, both countries can be said to be exchanging benefits in secret. Japan is all seriousness while staring at her own set of tiles, and is oblivious to the actions of the others in her self-focused state.
Taiwan wears a traditional red slip, symbolizing that she is the true heir of Chinese culture and civilization. In one hand she has a bowl of fruit, and in the other, a paring knife. Her expression as she stares at China is full of anger, sadness, and hatred, but to no avail; unless she enters the game, no matter who ends up as the victor, she is doomed to a fate of serving fruit.
Outside the riverbank is darkened by storm clouds, suggesting the high tension between the two nations is dangerously explosive. The painting hanging on the wall is also very meaningful; Mao’s face, but with Chiang Kai Shek’s bald head, and Sun Yat-Sen’s mustache.
The four women’s state of undress represent the situation in each country. China is naked on top, clothed with a skirt and underwear on the bottom. America wears a bra and a light jacket, but is naked on the bottom. Russia has only her underwear left. Japan has nothing left.
At first glance, America appears to be most composed and seems to be the best position, as all the others are in various states of nakedness. However, while America may look radiant, her vulnerability has already been exposed. China and Russia may look naked, yet their key private parts remain hidden.
If the stakes of this game is that the loser strips off a piece of clothing, then if China loses, she will be in the same state as Russia (similar to when the USSR dissolved). If America loses, she also ends up in the same state as Russia. If Russia loses, she loses all. Japan has already lost everything.
Russia seems to be a mere “filler” player, but in fact is exchanging tiles with China. The real “filler” player is Japan, for Japan has nothing more to lose, and if she loses just once more she is immediately out of the game.
America may look like she is in the best position, but in fact is in a lot of danger, if she loses this round, she will give up her position as a world power. Russia is the most sinister, playing along with both sides, much like when China was de-occupied, she leaned towards the USSR and then towards America; as she did not have the ability to survive on her own, she had to weave between both sides in order to survive and develop.
There are too many of China’s tiles that we cannot see. Perhaps suggesting that China has several hidden aces? Additionally China is also exchanging tiles with Russia, while America can only guess from Taiwan’s expression of what actions have transpired between Russia and China. Japan on the other hand is completely oblivious, still focused solely on her own set of tiles.
Taiwan stares coldly at the game from aside. She sees everything that the players at the table are doing, she understands everything that is going on. But she doesn’t have the means or permission to join the game, she isn’t even given the right to speak. Even if she has a dearth of complaints, she cannot voice it to anyone, all she can do is to be a good page girl, and bring fresh fruit to the victor.
The final victor lies between China and America, this much is apparent. But look closely; while America is capable, they are playing Chinese Mahjong, not Western Poker. Playing by the rules of China, how much chance at victory does America really have?
Wednesday, June 26, 2013
The ability to hire well is random
“We found that brainteasers are a complete waste of time. How many golf balls can you fit into an airplane? How many gas stations in Manhattan? A complete waste of time. They don’t predict anything. They serve primarily to make the interviewer feel smart.”
That was just one of the many fascinating revelations that Laszlo Bock, Google’s senior vice president for people operations, shared with me in an interview that was part of the New York Times’ special section on Big Data published Thursday.
Bock’s insights are particularly valuable because Google focuses its data-centric approach internally, not just on the outside world. It collects and analyzes a tremendous amount of information from employees (people generally participate anonymously or confidentially), and often tackles big questions such as, “What are the qualities of an effective manager?” That was question at the core of its Project Oxygen, which I wrote about for the Times in 2011.
I asked Bock in our recent conversation about other revelations about leadership and management that had emerged from its research.
The full interview is definitely worth your time, but here are some of the highlights:
The ability to hire well is random. “Years ago, we did a study to determine whether anyone at Google is particularly good at hiring,” Bock said. “We looked at tens of thousands of interviews, and everyone who had done the interviews and what they scored the candidate, and how that person ultimately performed in their job. We found zero relationship. It’s a complete random mess, except for one guy who was highly predictive because he only interviewed people for a very specialized area, where he happened to be the world’s leading expert.”
Forget brain-teasers. Focus on behavioral questions in interviews, rather than hypotheticals. Bock said it’s better to use questions like, “Give me an example of a time when you solved an analytically difficult problem.” He added: “The interesting thing about the behavioral interview is that when you ask somebody to speak to their own experience, and you drill into that, you get two kinds of information. One is you get to see how they actually interacted in a real-world situation, and the valuable ‘meta’ information you get about the candidate is a sense of what they consider to be difficult.”
Consistency matters for leaders. “It’s important that people know you are consistent and fair in how you think about making decisions and that there’s an element of predictability. If a leader is consistent, people on their teams experience tremendous freedom, because then they know that within certain parameters, they can do whatever they want. If your manager is all over the place, you’re never going to know what you can do, and you’re going to experience it as very restrictive.
GPAs don’t predict anything about who is going to be a successful employee. “One of the things we’ve seen from all our data crunching is that G.P.A.’s are worthless as a criteria for hiring, and test scores are worthless — no correlation at all except for brand-new college grads, where there’s a slight correlation,” Bock said. “Google famously used to ask everyone for a transcript and G.P.A.’s and test scores, but we don’t anymore, unless you’re just a few years out of school. We found that they don’t predict anything. What’s interesting is the proportion of people without any college education at Google has increased over time as well. So we have teams where you have 14 percent of the team made up of people who’ve never gone to college.”
That was a pretty remarkable insight, and I asked Bock to elaborate.
“After two or three years, your ability to perform at Google is completely unrelated to how you performed when you were in school, because the skills you required in college are very different,” he said. “You’re also fundamentally a different person. You learn and grow, you think about things differently. Another reason is that I think academic environments are artificial environments. People who succeed there are sort of finely trained, they’re conditioned to succeed in that environment. One of my own frustrations when I was in college and grad school is that you knew the professor was looking for a specific answer. You could figure that out, but it’s much more interesting to solve problems where there isn’t an obvious answer. You want people who like figuring out stuff where there is no obvious answer.”
Tuesday, June 25, 2013
Harvard study : Smart Phones
Smartphone use may make you wussy, says Harvard study
Harvard study shows that the size of a device, and your body posture using it, influences your behavior and demeanor.
Do you hunch when you work on your smartphone?
(Credit: Apple)
Your reputation as a tough, hard-nosed business go-getter may take a hit if you spend a lot of time using your little smartphone. A study conducted by researchers at Harvard Business School suggests that using devices with small screens can cause people to behave less assertively than those using larger screens.
"Grounded in research showing that adopting expansive body postures increases psychological power, we hypothesized that working on larger devices, which forces people to physically expand, causes users to behave more assertively," reads the abstract of the paper, titled "iPosture: The Size of Electronic Consumer Devices Affects Our Behavior."
The study used 75 participants who were randomly assigned to perform tasks on various devices. The researchers chose to go with Apple products representing a range of sizes, though the results could be extrapolated to other brands. Participants used an iPod Touch, aniPad, a MacBook Pro, or an iMac.
Once the tasks were finished, the researcher told the participant, "I will be back in five minutes to debrief you, and then pay you so that you can leave. If I am not here, please come get me at the front desk." The researcher then waited up to 10 minutes to return. Participants who had been using smaller devices took longer to go fetch the researcher than those using larger devices.
The paper concludes with a bit of advice. "Many of us spend hours each day interacting with our electronic devices. In professional settings we often use them to be efficient and productive. We may, however, lose sight of the impact the device itself has on our behavior and as a result be less effective. We suggest that some time before going into a meeting, and obviously also during it, you put your cell phone away."The researchers trace this correlation to the body posture people adopt when using devices. Smartphones and tablet users tend to hunch over their devices and contract their bodies. Desktops users tend to have a more open posture."Participants interacting with smaller devices were less assertive than participants interacting with larger devices," says the study.
How long the participants waited to get the researcher, and whether they left at all. (Click to enlarge.)
(Credit: Harvard Business School)
Subscribe to:
Posts (Atom)