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Of course, ST reserves the right to edit my letter for clarity and length. When said statistics in question were directly taken from their original article, though, one has to wonder if there hasn’t been a breakdown in communication over there. I’m dreadfully sorry, forum editors, I should have double-checked my original source (your journalist Ms Rachel Chang) before sending my letter.

take a look at how my pride in our meritocratic system in my originally letter has been transfigured into awe at Dr Ng’s background, for example! Dear friends, when an editor takes the time and effort to not just paraphrase but completely and utterly transform your piece in both intent and meaning, then what can we say but bravo.

There are surely no lazy slackers over at the Straits Times; instead we have evidently men and women who dedicate time and effort to correct their misguided readers, and protect them from the shame of having their real opinions published.

If I say I think it is fair in Singapore, because half of the bottom one-third of the people make it to the top two-thirds, it does not mean that someone can quote me and say that I said what I said because half the bottom one-third of people did not make it. I think it is alright to say that I do not agree entirely with what was said, because does it also mean on the flip side that half of the bottom one-third of the people did not make it? This is what I mean by quoting one out of context, by using statistics that I did not say, and implying that I did, or by innuendo.

Moreover, depending on the methodology, definition, sampling, etc, half of the  bottom one-third of the people making it, does not necessary mean that half did not make it, because some may not be in the population because of various reasons, like emigration, not turning up, transfer, whether adjustments are made  for the mobility of people up or down the social strata over time, etc. If I did not use a particular statistic to state my case, for example, I don’t think it is appropriate to quote me and say that you agree with me by citing statistics from a third party source, like the MOE chart in the Straits Times article, instead of quoting the statistics that I said.

I cannot find anything in any of the media reports to say with certainty that the Minister backed up his remarks with direct reference to the MOE chart. There is also nothing in the narrative that only 10 per cent  of children from one-to-three room flats make it to university – which is to say, 90 per cent  of them don’t. The ’90 per cent’ cannot be attributed to what the minister said, as at best it is the writer’s interpretation of the MOE chart.

Interesting exchange of letters. Samuel’s interpretation of the statistics provided by Ng Eng Hen and ST is correct. There is little doubt about it. While I can see where Leong Sze Hian is coming from, I don’t totally agree with him. Specifically, Samuel’s first statement (only ~10% of students living in 1-3 room flat make it to university) is directed at ST’s report that education is a good social leveller but not at Ng. It is therefore a valid point to make.

For instance, in terms of education levels, we no longer live in a world that is divided into the West and the rest; our world today stretches from Canada to Yemen with all the other countries somewhere in between. There’s a broad spectrum of levels

even when people act within a fact-based worldview, they are used to talking with sterile figures. They are used to standing on a podium, clicking through slide shows in PowerPoint rather than interacting with their presentation. The problem is that companies have a strict separation between their IT department, where datasets are produced, and the design department, so hardly any presenters are proficient in both. Yet this is what we need. Getting people used to talking with animated data is, to my mind, a literacy project.

What’s important today is not just financial data but child mortality rates, the number of children per women, education levels, etc. In the world today, it’s not money that drags people into modern times, it’s people that drag money into modern times.

I can demonstrate human resources successes in Asia through health being improved, family size decreasing and then education levels increasing. That makes sense: when more children survive, parents accept that there is less need for multiple births, and they can afford to put their children through school. So Pfizer have moved their research and development of drugs to Asia, where there are brilliant young people who are amazing at developing drugs. It’s realising this kind of change that’s important.

The problem isn’t that specialised companies lack the data they need, it’s that they don’t go and look for it, they don’t understand how to handle it.

What is so strong with animation is that it provides that mindset shift in market segmentation. We can see where there are highly developed countries with a good economy and a healthy and well-educated staff.

At the moment, I’m quarrelling with Sweden’s Minister of Foreign Affairs. He says that the West has to make sure its lead over the rest of the world doesn’t erode. This is a completely wrong attitude. Western Europe and other high-income countries have to integrate themselves into the world in the same way big companies are doing. They have to look at the advantages, resources and markets that exist in different places around the world.

And some organisations aren’t willing to share their data, even though it would be a win-win situation for everybody and we would do much better in tackling the problems we need to tackle. Last April, the World Bank caved in and finally embraced an open data policy, but the OECD uses tax money to compile data and then sells it in a monopolistic way. The Chinese Statistical Bureau provides data more easily than the OECD. The richest countries in the world don’t have the vision to change.

‘database hugging disorder’

we have to instil a clear division of labour between those who provide the datasets – like the World Bank, the World Health Organisation or companies themselves – those who provide new technologies to access or process them, like Google or Microsoft, and those who ‘play’ with them and give data meaning. It’s like a great concert: you need a Mozart or a Chopin to write wonderful music, then you need the instruments and finally the musicians.

The success suggests that socialbots could manipulate social networks on a larger scale, for good or ill. "We could use these bots in the future to encourage social participation or support for humanitarian causes," Hwang claims. He also acknowledges that there is a flip side, if bots were also used to inhibit activism.

The military may already be onto the idea. Officials at US Central Command (Centcom), which oversees military activities in the Middle East and central Asia, issued a request last June for an "online persona management service". The details of the request suggest that the military want to create and control 50 fictitious online identities who appear to be real people from Afghanistan and Iraq.

It is not clear, however, if any of the management of the fake identities would be delegated to software. A Centcom spokesperson told New Scientist that the contract supports "classified blogging activities on foreign language websites to enable Centcom to counter violent extremist and enemy propaganda outside the US".

Hwang has ambitious plans for the next stage of the socialbot project: "We're going to survey and identify two sites of 5000-person unconnected Twitter communities, and over a six-to-12-month period use waves of bots to thread and rivet those clusters together into a directly connected social bridge between those two formerly independent groups," he wrote in a blog post on 3 March. "The bot-driven social 'scaffolding' will then be dropped away, completing the bridge, with swarms of bots being launched to maintain the superstructure as needed," he adds.

The Wall Street Journal's examination of scraping—a trade that involves personal information as well as many other types of data—is part of the newspaper's investigation into the business of tracking people's activities online and selling details about their behavior and personal interests.

Some companies collect personal information for detailed background reports on individuals, such as email addresses, cell numbers, photographs and posts on social-network sites. Others offer what are known as listening services, which monitor in real time hundreds or thousands of news sources, blogs and websites to see what people are saying about specific products or topics.

One such service is offered by Dow Jones & Co., publisher of the Journal. Dow Jones collects data from the Web—which may include personal information contained in news articles and blog postings—that help corporate clients monitor how they are portrayed. It says it doesn't gather information from password-protected parts of sites.

The competition for data is fierce. PatientsLikeMe also sells data about its users. PatientsLikeMe says the data it sells is anonymized, no names attached.

Nielsen spokesman Matt Anchin says the company's reports to its clients include publicly available information gleaned from the Internet, "so if someone decides to share personally identifiable information, it could be included."

Internet users often have little recourse if personally identifiable data is scraped: There is no national law requiring data companies to let people remove or change information about themselves, though some firms let users remove their profiles under certain circumstances.

The freedom to hold opinions and to express opinions is a right expressly provided in international human-rights covenants. This includes the freedom to criticize other people's ideas and works. These freedoms are the basic premise for the transmission and exchange of knowledge among others. However, one of the very few restrictions to the exercise of these rights is the respect of the rights or reputation of others. An author, [like] any human being, is entitled to the respect of his reputation. The publication of works of course exposes an author to criticism, but it does not deprive him of the right to the respect of his reputation. Fair criticism does not automatically mean that rights of the authors were disregarded. ...

In my view, fair criticism of someone else's idea can initially be put on the Internet without the agreement of the author. If an author finds the criticism unfair or erroneous and informs the manager or editor of the site accordingly, the author should be entitled to respond and be granted the same space as was accorded to the criticism, and'"I want to emphasize'"not only in the form of a comment. Where the author considers the criticism to be libelous and harmful to his reputation, another mutually agreed-upon reviewer should be found and, whatever the outcome, it [the review] can be posted. But in the meantime, the criticism should be removed. Words can cause tremendous harm, and there are higher principles telling us not to do so.

3. Collaboration at scale Across many economies, the number of people who undertake knowledge work has grown much more quickly than the number of production or transactions workers. Knowledge workers typically are paid more than others, so increasing their productivity is critical. As a result, there is broad interest in collaboration technologies that promise to improve these workers' efficiency and effectiveness. While the body of knowledge around the best use of such technologies is still developing, a number of companies have conducted experiments, as we see in the rapid growth rates of video and Web conferencing, expected to top 20 per cent annually during the next few years.

4. The growing ‘Internet of Things' The adoption of RFID (radio-frequency identification) and related technologies was the basis of a trend we first recognised as "expanding the frontiers of automation." But these methods are rudimentary compared with what emerges when assets themselves become elements of an information system, with the ability to capture, compute, communicate, and collaborate around information—something that has come to be known as the "Internet of Things." Embedded with sensors, actuators, and communications capabilities, such objects will soon be able to absorb and transmit information on a massive scale and, in some cases, to adapt and react to changes in the environment automatically. These "smart" assets can make processes more efficient, give products new capabilities, and spark novel business models. Auto insurers in Europe and the United States are testing these waters with offers to install sensors in customers' vehicles. The result is new pricing models that base charges for risk on driving behavior rather than on a driver's demographic characteristics. Luxury-auto manufacturers are equipping vehicles with networked sensors that can automatically take evasive action when accidents are about to happen. In medicine, sensors embedded in or worn by patients continuously report changes in health conditions to physicians, who can adjust treatments when necessary. Sensors in manufacturing lines for products as diverse as computer chips and pulp and paper take detailed readings on process conditions and automatically make adjustments to reduce waste, downtime, and costly human interventions.

5. Experimentation and big data Could the enterprise become a full-time laboratory? What if you could analyse every transaction, capture insights from every customer interaction, and didn't have to wait for months to get data from the field? What if…? Data are flooding in at rates never seen before—doubling every 18 months—as a result of greater access to customer data from public, proprietary, and purchased sources, as well as new information gathered from Web communities and newly deployed smart assets. These trends are broadly known as "big data." Technology for capturing and analysing information is widely available at ever-lower price points. But many companies are taking data use to new levels, using IT to support rigorous, constant business experimentation that guides decisions and to test new products, business models, and innovations in customer experience. In some cases, the new approaches help companies make decisions in real time. This trend has the potential to drive a radical transformation in research, innovation, and marketing.

Using experimentation and big data as essential components of management decision making requires new capabilities, as well as organisational and cultural change. Most companies are far from accessing all the available data. Some haven't even mastered the technologies needed to capture and analyse the valuable information they can access. More commonly, they don't have the right talent and processes to design experiments and extract business value from big data, which require changes in the way many executives now make decisions: trusting instincts and experience over experimentation and rigorous analysis. To get managers at all echelons to accept the value of experimentation, senior leaders must buy into a "test and learn" mind-set and then serve as role models for their teams.

6. Wiring for a sustainable world Even as regulatory frameworks continue to evolve, environmental stewardship and sustainability clearly are C-level agenda topics. What's more, sustainability is fast becoming an important corporate-performance metric—one that stakeholders, outside influencers, and even financial markets have begun to track. Information technology plays a dual role in this debate: it is both a significant source of environmental emissions and a key enabler of many strategies to mitigate environmental damage. At present, information technology's share of the world's environmental footprint is growing because of the ever-increasing demand for IT capacity and services. Electricity produced to power the world's data centers generates greenhouse gases on the scale of countries such as Argentina or the Netherlands, and these emissions could increase fourfold by 2020. McKinsey research has shown, however, that the use of IT in areas such as smart power grids, efficient buildings, and better logistics planning could eliminate five times the carbon emissions that the IT industry produces.

7. Imagining anything as a service Technology now enables companies to monitor, measure, customise, and bill for asset use at a much more fine-grained level than ever before. Asset owners can therefore create services around what have traditionally been sold as products. Business-to-business (B2B) customers like these service offerings because they allow companies to purchase units of a service and to account for them as a variable cost rather than undertake large capital investments. Consumers also like this "paying only for what you use" model, which helps them avoid large expenditures, as well as the hassles of buying and maintaining a product.

In the IT industry, the growth of "cloud computing" (accessing computer resources provided through networks rather than running software or storing data on a local computer) exemplifies this shift. Consumer acceptance of Web-based cloud services for everything from e-mail to video is of course becoming universal, and companies are following suit. Software as a service (SaaS), which enables organisations to access services such as customer relationship management, is growing at a 17 per cent annual rate. The biotechnology company Genentech, for example, uses Google Apps for e-mail and to create documents and spreadsheets, bypassing capital investments in servers and software licenses. This development has created a wave of computing capabilities delivered as a service, including infrastructure, platform, applications, and content. And vendors are competing, with innovation and new business models, to match the needs of different customers.

8. The age of the multisided business model Multisided business models create value through interactions among multiple players rather than traditional one-on-one transactions or information exchanges. In the media industry, advertising is a classic example of how these models work. Newspapers, magasines, and television stations offer content to their audiences while generating a significant portion of their revenues from third parties: advertisers. Other revenue, often through subscriptions, comes directly from consumers. More recently, this advertising-supported model has proliferated on the Internet, underwriting Web content sites, as well as services such as search and e-mail (see trend number seven, "Imagining anything as a service," earlier in this article). It is now spreading to new markets, such as enterprise software: Spiceworks offers IT-management applications to 950,000 users at no cost, while it collects advertising from B2B companies that want access to IT professionals.

9. Innovating from the bottom of the pyramid The adoption of technology is a global phenomenon, and the intensity of its usage is particularly impressive in emerging markets. Our research has shown that disruptive business models arise when technology combines with extreme market conditions, such as customer demand for very low price points, poor infrastructure, hard-to-access suppliers, and low cost curves for talent. With an economic recovery beginning to take hold in some parts of the world, high rates of growth have resumed in many developing nations, and we're seeing companies built around the new models emerging as global players. Many multinationals, meanwhile, are only starting to think about developing markets as wellsprings of technology-enabled innovation rather than as traditional manufacturing hubs.

10. Producing public good on the grid The role of governments in shaping global economic policy will expand in coming years. Technology will be an important factor in this evolution by facilitating the creation of new types of public goods while helping to manage them more effectively. This last trend is broad in scope and draws upon many of the other trends described above.

it's in these companies' hands to do this ethically--to build algorithms that show us what we need to know and what we don't know, not just what we like.

why would the Googles and Facebooks of the world change what they're doing (absent government regulation)? My hope is that, like newspapers, they'll move from a pure profit-making posture to one that recognizes that they're keepers of the public trust.

most people don't know how Google and Facebook are controlling their information flows. And once they do, most people I've met want to have more control and transparency than these companies currently offer. So it's a way in to that conversation. First people have to know how the Internet is being edited for them.

what's good and bad about the personalization. Tell me some ways that this is not a good thing? Here's a few. 1) It's a distorted view of the world. Hearing your own views and ideas reflected back is comfortable, but it can lead to really bad decisions--you need to see the whole picture to make good decisions; 2) It can limit creativity and innovation, which often come about when two relatively unrelated concepts or ideas are juxtaposed; and 3) It's not great for democracy, because democracy requires a common sense of the big problems that face us and an ability to put ourselves in other peoples' shoes.

Stanford researchers Dean Eckles and Maurits Kapstein, who figured out that not only do people have personal tastes, they have personal "persuasion profiles". So I might respond more to appeals to authority (Barack Obama says buy this book), and you might respond more to scarcity ("only 2 left!"). In theory, if a site like Amazon could identify your persuasion profile, it could sell it to other sites--so that everywhere you go, people are using your psychological weak spots to get you to do stuff. I also really enjoyed talking to the guys behind OKCupid, who take the logic of Google and apply it to dating.

Nobody noticed when Google went all-in on personalization, because the filtering is very hard to see.

We could continuously sample a news source’s output to produce ongoing accuracy estimates, and build social software to help the audience report and filter errors. Meticulously applied, this approach would give a measure of the accuracy of each information source, and a measure of the efficiency of their corrections process (currently only about 3% of all errors are corrected.)

Real world reporting isn’t always clearly “right” or “wrong,” so it will often be hard to decide whether something is an error or not. But we’re not going for ultimate Truth here,  just a general way of measuring some important aspect of the idea we call “accuracy.” In practice it’s important that the error counting method is simple, clear and repeatable, so that you can compare error rates of different times and sources.

Subjective errors, though by definition involving judgment, should not be dismissed as merely differences in opinion. Sources found such errors to be about as common as factual errors and often more egregious [as rated by the sources.] But subjective errors are a very complex category

One of the major problems with previous news accuracy metrics is the effort and time required to produce them. In short, existing accuracy measurement methods are expensive and slow. I’ve been wondering if we can do better, and a simple idea comes to mind: sampling. The core idea is this: news sources could take an ongoing random sample of their output and check it for accuracy — a fact check spot check

Standard statistical theory tells us what the error on that estimate will be for any given number of samples (If I’ve got this right, the relevant formula is standard error of a population proportion estimate without replacement.) At a sample rate of a few stories per day, daily estimates of error rate won’t be worth much. But weekly and monthly aggregates will start to produce useful accuracy estimates

the first step would be admitting how inaccurate journalism has historically been. Then we have to come up with standardized accuracy evaluation procedures, in pursuit of metrics that capture enough of what we mean by “true” to be worth optimizing. Meanwhile, we can ramp up the efficiency of our online corrections processes until we find as many useful, legitimate errors as possible with as little staff time as possible. It might also be possible do data mining on types of errors and types of stories to figure out if there are patterns in how an organization fails to get facts right.

I’d love to live in a world where I could compare the accuracy of information sources, where errors got found and fixed with crowd-sourced ease, and where news organizations weren’t shy about telling me what they did and did not know. Basic factual accuracy is far from the only measure of good journalism, but perhaps it’s an improvement over the current sad state of affairs

But the problem is deeper than simply intellectual inertia. It goes back, ultimately, to the unconsidered differentiations we make—at every moment when we distinguish among objects—between those in the foreground of our consciousness and the background places in which the objects happen to be situated. Moreover, this distinction creates a hierarchy of objects. We are conscious not only of the skin that encloses and defines the object, but of bits and pieces of that object, each of which must have its own “skin.” That is the problem of anatomization. A car has a motor and brakes and a transmission and an outer body that, at appropriate moments, become separate objects of our consciousness, objects that at least some knowledgeable person recognizes as coherent entities.

Evelyn Fox Keller sees “The Mirage of a Space Between Nature and Nurture” as a consequence of our false division of the world into living objects without sufficient consideration of the external milieu in which they are embedded, since organisms help create effective environments through their own life activities.

The central point of her analysis has been that gender itself (as opposed to sex) is socially constructed, and that construction has influenced the development of science:If there is a single point on which all feminist scholarship…has converged, it is the importance of recognizing the social construction of gender…. All of my work on gender and science proceeds from this basic recognition. My endeavor has been to call attention to the ways in which the social construction of a binary opposition between “masculine” and “feminine” has influenced the social construction of science.

major critical concern of Fox Keller’s present book is the widespread attempt to partition in some quantitative way the contribution made to human variation by differences in biological inheritance, that is, differences in genes, as opposed to differences in life experience. She wants to make clear a distinction between analyzing the relative strength of the causes of variation among individuals and groups, an analysis that is coherent in principle, and simply assigning the relative contributions of biological and environmental causes to the value of some character in an individual

It is, for example, all very well to say that genetic variation is responsible for 76 percent of the observed variation in adult height among American women while the remaining 24 percent is a consequence of differences in nutrition. The implication is that if all variation in nutrition were abolished then 24 percent of the observed height variation among individuals in the population in the next generation would disappear. To say, however, that 76 percent of Evelyn Fox Keller’s height was caused by her genes and 24 percent by her nutrition does not make sense. The nonsensical implication of trying to partition the causes of her individual height would be that if she never ate anything she would still be three quarters as tall as she is.

In fact, Keller is too optimistic about the assignment of causes of variation even when considering variation in a population. As she herself notes parenthetically, the assignment of relative proportions of population variation to different causes in a population depends on there being no specific interaction between the causes.

Keller’s rather casual treatment of the interaction between causal factors in the case of the drummers, despite her very great sophistication in analyzing the meaning of variation, is a symptom of a fault that is deeply embedded in the analytic training and thinking of both natural and social scientists. If there are several variable factors influencing some phenomenon, how are we to assign the relative importance to each in determining total variation? Let us take an extreme example. Suppose that we plant seeds of each of two different varieties of corn in two different locations with the following results measured in bushels of corn produced (see Table 1). There are differences between the varieties in their yield from location to location and there are differences between locations from variety to variety. So, both variety and location matter. But there is no average variation between locations when averaged over varieties or between varieties when averaged over locations. Just by knowing the variation in yield associated with location and variety separately does not tell us which factor is the more important source of variation; nor do the facts of location and variety exhaust the description of that variation.