The recent revelations concerning widespread US government access to electronic communications data (including the PRISM system apparently run by the National Security Agency) leave many questions unanswered, and new facts are constantly emerging. Thoughtful commentators should be hesitant to make detailed pronouncements before it is clear what is actually going on.

Nevertheless, given the potential of these developments to fundamentally reshape the data protection and privacy landscape, I cannot resist drawing a few high-level, preliminary conclusions, from a European perspective:

Legal protection without political commitment is insufficient to protect privacy. In the regulation of data flows across national borders, trying to resolve conflicts between privacy regulation and government access requirements solely through legal means puts more pressure on the law than it can bear. In addition to strong legal measures, we need greater commitment to privacy protection at the political level, which unfortunately is lacking in many countries.

Government access to personal data is a global issue. International Data Privacy Law recently published a detailed legal analysis last year of systematic government access to private-sector data in nine countries (Australia, Canada, China, Germany, India, Israel, Japan, the UK, and the US), and concluded that a lack of adequate transparency and clear legal standards in this area is a global problem. Revelations about the US programs should not distract attention from issues regarding government access to data in other countries.

There should be more transparency around government data access. Governments have yet to learn one of the main lessons from data breach cases, namely that they need to be dealt with openly and transparently. It would have been preferable if there had been a reasoned public discussion about these law enforcement programs over the last few years, rather than having them explode in the press like a bombshell.

Penalizing discussion of the possibility of government data access is counterproductive. Laws that prohibit discussing the existence of government data access programs should be changed. How can we judge whether access is necessary and legally justified if we can’t even mention the fact that it is occurring? And I can’t believe that many terrorists nowadays are ignorant of the fact that their electronic communications may be subject to government surveillance.

The debate about the legality of these programs so far has been simplistic. Since news of these surveillance programs broke, some commentators have argued that all law enforcement surveillance is illegitimate, while others maintain that it is presumptively permissible as long as it is useful. Such a black-or-white approach is incorrect and unsatisfying. There is a need for a more sophisticated analysis, which could be based on well-established European legal concepts such as whether a particular surveillance program is proportionate, and whether it is necessary in a democratic society.

These revelations will cause embarrassment to European governments as well to the United States. The legal and political fallout will not be limited to the US. It is well-known that the US shares a good deal of intelligence with European countries, and awkward questions are already being raised about the extent to which European intelligence services may have accessed data collected by the US under PRISM and similar programs.

Distinguishing between privacy protection for nationals and foreigners is indefensible. On 7 June, President Obama attempted to reassure the American public by saying that access to Internet and e-mail data “does not apply to U.S. citizens, and it does not apply to people living in the United States”. Such statements will only cause concern among the billions of Internet users outside the US. Having stressed the need for a global system of privacy protection in its February 2012 report on “Consumer Data Privacy in a Networked World”, it is inconsistent for the White House imply that US citizens should be given a higher level of privacy protection than non-citizens.

These developments will have major consequences for data protection and privacy law. The long-term effect of these developments on data protection and privacy law cannot yet be foreseen, but some consequences are already apparent. For instance, the EU General Data Protection Regulation proposed in 2012 by the European Commission, final approval of which has been hampered by political disagreement, may receive new impetus from the recent revelations, while the proposed EU-US Free Trade Agreement may suffer.

The effectiveness of data protection and privacy regulation is ultimately dependent on individuals having confidence in how their data are processed. This confidence has been severely shaken in recent days; it is important for both governments and the private sector to take steps to strengthen it, before it is too late.

Dr. Christopher Kuner is editor-in-chief of the journal International Data Privacy Law. He is author of European Data Protection Law: Corporate Compliance and Regulation, and the new book Transborder Data Flow Regulation and Data Privacy Law in which he elaborates some of the topics discussed here. Dr. Kuner is Senior Of Counsel at Wilson Sonsini Goodrich & Rosati in Brussels, and an Honorary Fellow of the Centre for European Legal Studies, University of Cambridge.

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We’re planning to make several changes to the OUPblog this year to improve the site and your reading experience. Some of the first changes will be taking place over the next couple weeks.

We will change some of our navigation and categorization on the blog based on reader behavior: deleting, adding, shifting, and renaming several categories. For example, our current ‘dictionaries’ category will be renamed ‘language’ and sub-categories will better reflect the full range of our language publishing from lexicography to linguistics.

We will also migrate away from Feedburner, which currently delivers our RSS and email, to a new service. Feedburner has been unreliable and we believe Google is getting ready to shut down this service after they shut down Google Reader on 1 July 2013. If all goes well, your email and RSS notifications will not change. If not, please check back here and re-subscribe.

Remember you can find the raw RSS feeds on our Follow page.

You can also follow all of Oxford University Press’s academic news and information on Facebook, Twitter, Google Plus, Tumblr, YouTube, Vimeo, Sina Weibo, and soon to come Pinterest, as well as several social media outlets for various products, series, and disciplines.

We know a few of the problems the site is experiencing and have great plans for improving it over the coming months. We of course welcome your feedback too and appreciate any comments that can be left in the box below.

Thank you for your loyal readership,

Alice Northover
OUPblog Editor

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But how much do you know about the people behind the Internet? Who were the founding fathers and mothers of computer science? Do you know who coined the term ‘computer bug’ or who said “We don’t have the option of turning away from the future. No one gets to vote on whether technology is going to change our lives”?

Take our computing quiz, compiled from resources in Who’s Who, the Oxford Dictionary of National Biography, Oxford Reference, and the American National Biography, to see if you’re a computer genius or if you need an upgrade!

Who’s Who, published annually by A & C Black since 1897, and online exclusively by Oxford University Press since 2008, is the leading source of up-to-date information about over 35,000 influential people from all walks of life, worldwide, who have left their mark on British public life. Written by specialist authors, the Oxford DNB biographies will introduce you to the people behind British history’s great events as well as its literature, science, art, music, and ideas. Oxford Reference is the home of Oxford’s quality reference publishing bringing together over 2 million entries, and more than 16,000 illustrations, into a single cross-searchable resource. Discover the lives of more than 18,700 men and women — from all eras and walks of life — who have influenced American history and culture in the acclaimed American National Biography Online.

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Notwithstanding the many privacy concerns it raises, the role of video surveillance footage in cracking the Boston terror attack case in a matter of days is well known. Such footage played an equally critical role in tracking down the bombers of the 2005 London attacks. However, in 2005 investigators took weeks to manually sift through about two thousand hours of video footage. This time around, thousands of hours of video were analyzed in barely 48 hours.

The city of Boston is smaller than London; still, it has thousands of surveillance cameras, very similar to the London of 2005. What has changed is technology: video analysis has become significantly more sophisticated in the years since 2005. For example, pre-processing tools are able to filter hours of video footage in, say, an empty subway station at night. Investigators are able to focus only on periods of activity rather than patiently watch footage of an empty platform for hours on end.

Of course, more crowded scenes, especially those as packed as the sidewalks alongside the marathon route require far more sophisticated technology, much of which is still in its infancy. Today there are many commercial video analytics tools that claim to be able to detect a person leaving a bag or backpack and walking away. Such tools are certainly very useful in narrowing down portions of video footage to be analyzed manually during post-incident investigations. But can they reliably alert us in real-time without generating too many false positives? For example, you lay down a brief case and move behind a pillar to find a quiet place to make a phone call. A video surveillance system might well conclude that you have left the scene and your bag is a potential threat. Hundreds of such warnings might be generated every minute — who is to monitor and decide which ones to follow up on?

Another technique that has seen significant advances in recent years is tracking moving objects in videos, especially human beings. Further, it is now possible (only barely though), to track the same person as he moves across large distances as he moves in and out of the field of view of multiple cameras. So, in principle, a hypothetical `big brother’ central server that processes feeds from multiple cameras should be able to track anyone suspected in a ‘left bag’ event and verify whether they rapidly walk away from the scene or not. Of course, bandwidth remains a limitation, which is why many video analytics solutions rely on local ‘event detection’ at the camera level so as to minimize transferring too much data across a network. Further, in such situations, different cameras need to be ‘told’ to track a ‘particular’ person seen by another camera, and that too in a bandwidth efficient manner. So much work remains to be done for efficient large-scale multi-camera tracking.

But there is more: Many recent terror attacks, especially in India, share a similar modus operendi — the terrorist leaves his dangerous cargo on a bicycle that he parks in a crowded market and walks away, seemingly on an innocent shopping errand. Should our central server raise an alarm? After all, many people genuinely shop while their two-wheeled vehicle, bicycle or motorbike, lies parked nearby, perhaps also loaded with their recent purchases. Do we warn citizens of dire consequences if they leave packets on their bikes?

Clearly our central server needs to work harder, track more people, for longer. Most importantly, it needs to reason. However ubiquitous video cameras might be, they still cannot be everywhere — certainly not in every store, restaurant, or loo! The central server would need to explain away the actions of most of the people it tracked, and narrow down on only a few, such as someone entering a subway station, leaving a bag and then boarding a train. (Such ‘explaining away’ to home in on the right answer is an example of ‘abductive reasoning’. If it appears difficult for a machine to mimic, take note that just such reasoning has in fact already been used by IBM’s Watson program that won the 2009 Jeopardy! competition.)

Moreover, how might the video surveillance servers of the future come to know what is normal behavior and what is not? Certainly it would be impossible to catalogue every instance of normalness for the machine to ‘look up’ and compare against. Instead, the machine would need to learn, using massive amounts of ‘normal’ video footage. Difficult, but by no means impossible any more. Consider this: each year over 15 million hours of video is uploaded onto YouTube. In contrast, a human being is exposed to barely half a million hours of ‘video experience’ over a lifetime (90 years × 365 days × 16 hours/day). Yet we learn, and rather early on, the difference between normal and abnormal, be it suspicious or merely eccentric. Granted that eccentricity is not entirely absent from YouTube videos, still, there is more than enough ‘normal’ video available today for machines to learn from, if only they knew how.

Intelligent systems such as our hypothetical central video-surveillance server need to go beyond merely looking at the world while watching us. They also need to continuously learn from the data they experience, so as to see and focus on what is actually important. Only then can they connect the dots and make reasonably accurate predictions, so corrective action can be taken in time, and not only after a tragedy has occurred.

Finally, the cycle we just described above: Look, Listen, and Learn, so as to Connect, Predict and finally Correct, will be a common feature of the highly connected ‘web-intelligent’ systems of the not too distant future, be they for video surveillance, self-driving cars, or even the smart-grid.

Gautam Shroff is Vice President & Chief Scientist, Tata Consultancy Services and head of the TCS Innovation Lab in Delhi, India. He occasionally teaches in an adjunct capacity at the IIT Delhi and IIIT Delhi, as well as online via Coursera. He is the author of The Intelligent Web: Search, smart algorithms, and big data.

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Image credit: High tech overhead security camera at a government owned building. Photo © trekandshoot via iStockphoto.

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Mike was a doctoral student profoundly appreciated and esteemed by faculty, peers, staff, and all who came in contact with him. As is typical in our community, Mike was already a successful mid-career professional. He worked in the tech world and brought his expertise to us. He didn’t have a background in research psychology, but in the last year of his doctoral program, his work was published on nine occasions. Nine publications during the last year of graduate school is an incredible feat for anyone. But the heart-wrenching part of the story is that in the last eight months of his doctoral program, Mike also learned he had life-threatening cancer to which he finally succumbed about a month after graduation.

Mike’s family kept a blog of his progress and not long after graduation we learned that the end had come. Some of us attended the funeral in person. One member of our community gave the eulogy—a very stirring story of their travels, work, and time spent together in the program. The funeral was even livecast on the web so those who couldn’t be there physically could attend virtually.

Mike’s virtual wake

In the midst of these events, several of us wanted to commune so we held what amounted to a kind of virtual wake—a video chat with people from all around the country talking about our shared loss and joy of having had Mike in our lives. Several of us wrote eulogies for Mike and shared them with each other online. In mine, I spoke about how my relationship with Mike flashed through my mind like a dream sequence. In it, I remembered Mike and I in various settings: walking on the beach planning research, touring the MIT Media Lab, attending a presentation at Harvard’s Berkman Center for Internet research, and talking on the phone or Skyping.

People often grapple with the question of what is “real” versus “unreal” in the realm of media and technology. As a media psychologist I study how media use influences our feelings, actions and thoughts, and use media every day to teach a doctoral program that uses a hybrid model of higher education. While we do meet face-to-face (F2F), more often we use other forms of communication to meet virtually.

My students and I text, call, video chat, email, and post in social networking groups.  We discuss research walking the beach, brainstorm together in a seminar, or hold intriguing debates via video chat. Our F2F meetings are what one colleague calls “intense bursts of togetherness.” They’re the kind of thing where you might spend a week in morning-through-night meetings, classes, and social gatherings.  These varied means of communication have a deep reality for us, and through these experiences we are bonded together in unique ways. Our community is a kind of exciting world-within-a-world where we study what we do and we do what we study.

But for now, I’m honored to tell part of Mike’s story, and in some way, Mike’s presence in our virtual community is a legacy of the powerful ways technology can bring us together.

Karen Dill-Shackleford is the author of How Fantasy Becomes Reality and the editor of the Oxford Handbook of Media Psychology. She has testified before the US Congress about media violence and about representations of race and gender in the media. 

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How did the Automatic Computing Engine make it possible to invent the first modern computer?

Click here to view the embedded video.

B. Jack Copeland is the Director of the Turing Archive for the History of Computing, and author of Turing: Pioneer of the Information Age, Alan Turing’s Electronic Brain, and Colossus. He is the editor of The Essential Turing. Read the new revelations about Turing’s death after Copeland’s investigation into the inquest.

Visit the Turing hub on the Oxford University Press UK website for the latest news in the Centenary year (2012). Read our previous posts on Alan Turing including: “Maurice Wilkes on Alan Turing” by Peter J. Bentley, “Turing : the irruption of Materialism into thought” by Paul Cockshott, “Alan Turing’s Cryptographic Legacy” by Keith M. Martin, and “Turing’s Grand Unification” by Cristopher Moore and Stephan Mertens, “Computers as authors and the Turing Test” by Kees van Deemter, and “Alan Turing, Code-Breaker” by Jack Copeland.

For more information about Turing’s codebreaking work, and to view digital facsimiles of declassified wartime ‘Ultra’ documents, visit The Turing Archive for the History of Computing. There is also an extensive photo gallery of Turing and his war at www.the-turing-web-book.com.

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On 1 April 1913, Henry Ford symbolically pressed a lever that catapulted factory workers into the modern era. That lever was the assembly line, which was started at his Highland Park factory on that date. From then on the organized chaos and time-wasting labor of the typical factory floor were transformed into a process that was much quicker and economical, and far less strenuous. It allowed production to explode exponentially, which was good for everyone, for in the process employees made far more money, and that money was enough to buy the sophisticated standardized product they were producing: the Model T. So Ford got happier workers, and a brand new market among them. His practices spread quickly throughout industry and throughout the world.

The Ford Motor Company assembly line (1928)

The assembly line was a technical marvel that allowed the complete system of mass production to evolve. The revolutionary $5 a day wage he announced in January 1914 sustained it. But from the beginning, there was a great deal of controversy over these things.

Ford’s competitors thought he had lost his mind, especially when they heard that part of that $5 wage was to be a share in profits. To them he was a flaming radical, infringing on a sacred right of capitalism, the right of its owners to keep the profit it earned. Ford however was influenced by the Emersonian notion of just compensation: if you didn’t offer that, you got something else instead, something not at all good. Later he was to say he believed workers had a right to a share in profits, and that owners had an obligation to provide it. This was a truly radical statement.

But in truth Ford had to do something like this to meet overwhelming demand. His plant was in turmoil as new assembly lines were set up every day, amid clangorous noise and a constant need to go faster and faster. Turnover among the workers was nearly complete, as many of them felt no incentive to bear these new working conditions.

Work was now democratized, broken down to tiny units of standardized effort that anyone could do with a few minutes of training, even if they didn’t speak English. But it was also mind-deadening and infinitely repetitive. Furthermore, craft and skill were taken from the workers lives. Henceforward, those qualities were to be found only in planners and engineers. The only thing that mattered for laborers was that they showed up and did their jobs. In 1936, when Charlie Chaplin’s satire on factory work, Modern Times, was shown in Pittsburgh, nobody laughed because it was too close to the truth. So the $5 day was Ford’s necessary solution to this situation. People were willing to put up with almost anything to get it.

There was another problem with mass production. This one was for Ford himself, and it was both intractable and unexpected. He always said he was in the business of making men in his factories, but the kind of men he made were modern urban factory workers, many drawn from the rural America in which Ford himself was raised. He expected that they would share the same old fashioned homespun American values that he espoused, but now they were living in urban society with time and money of their own to spend on their leisure. They wanted to participate in the good citified life they saw all around them. So jazz and the Charleston replaced fiddlers and barn dances, and speakeasies and film palaces became the places where the sheiks and shebas of the modern urban workplace congregated after hours, drinking and smoking and raising hell. Ford was horrified, especially when he realized that this situation was irreversible, and a surprising consequence of his life’s work. More and more, he pulled back from the sort of men he was making in his factories.

Today the progeny of the proletariat whom Ford helped into the middle class with his system are told education and skill are the keys to a better life in modern society. The problem is that that there is an ever widening economic gulf between those who have acquired education and skills and those who have not, which many fear could sooner or later undermine the cohesion of the social fabric. Ford’s solution to the problem of dealing with those who were left behind was to provide a system that could bring them up to speed with everyone else. It was a businessman’s solution to business problems, and not eleemosynary, but it served the times well. But who is providing a modern solution for the millions and tens of millions who have never gotten ahead, or feel themselves slipping further and further behind those who have the resources to get ahead? Telling them to go out and get what they do not have and cannot get is no solution. Henry Ford brought the uneducated, unskilled common man new levels of material prosperity with mass production. Would that someone of equal genius and equal concern might come along now with a similarly effective idea for the problems of the common man of today.

Vincent Curcio is the author of Henry Ford; Suicide Blonde: The Life of Gloria Grahame; Chrysler: The Life and Times of an Automotive Genius; and, with Steven Englund, Charlie’s Prep. He was the General Manager and Producer of Lucille Lortel’s White Barn Theater for 25 years.

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Image credit: Literary Digest 1928-01-07 Henry Ford Interview / Photographer unknown via Wikimedia Commons

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In 2006, there appeared to be a remarkable consensus among Internet gurus, activists, bloggers, and academics about the promise of Web 2.0 that users would attain more power than they ever had in the era of mass media. Rapidly growing platforms like Facebook (2004), YouTube (2005), and Twitter (2006) facilitated users’ desire to make connections and exchange self-generated content. The belief in social media as technologies of a new “participatory” culture was echoed by habitual tools-turned-into-verbs: buttons for liking, trending, following, sharing, trending, et cetera. They articulated a feeling of connectedness and collectivity, strongly resonating the belief that social media enhanced the democratic input of individuals and communities. According to some, Web 2.0 and its ensuing range of platforms formed a unique chance to return the “public sphere” — a sphere that had come to be polluted by commercial media conglomerates — back in the hands of ordinary citizens.

Eight years after the apex of techno-utopian celebration, a number of large platforms have come to dominate a social media ecosystem vastly different from when the platforms just started to evolve. It’s time for a reality check. What did social media do for the public — users like you — and for the ideal of a more democratic public space? Do they indeed promote connectedness and participation in community-driven activities or are they rather engines of connectivity, driven by automated algorithms and invisible business models?  Online socializing, as it now seems, is inimically mediated by a techno-economic logic anchored in the principles of popularity and winner-takes-all principles that enhance the pervasive logic of mass media instead of offering alternatives.

Most contemporary social media giants once started out as informal platforms for networking or “friending” (Facebook), for exchanging user-generated content (YouTube), or for participating in opinionated discussions (Twitter). It was generally assumed that in the new social media space, all users were equal. However, platforms’ algorithms measured relevance and importance in terms of popularity rankings, which subsequently formed the quantifiable basis of data-driven interactivity wrapped in “social” rhetoric such as following, trending, or sharing. In this platform-mediated ecosystem, sponsored and professionally generated content soon received a lot more attention than user-generated content. Platforms like YouTube and Facebook gradually changed their interfaces to yield business models that were staked in two basic variables: attention and user data. By 2012, once informal social traffic between users had become fully formalized, automated, and commoditized by platforms owned and exploited by fast growing corporate giants. Although each of these platforms nurses its own proprietary mechanisms, they are staked in the same values or principles: popularity, hierarchical ranking, quick growth, large traffic volumes, fast turnovers, and personalized recommendations. A like is not a retweet, but most algorithms are underpinned by the norms of popularity and fast-trending topics.

The cultivation of online sociality is increasingly dominated by four major chains of platforms: Google, Apple, Facebook, and Amazon. These chains share some operational principles even if they differ on some ideological premises (open versus closed systems). Some consider social media platforms as alternatives to the old mass media, praising their potential to empower individual users who can contribute their own opinions or content to a media universe that was before pretty much closed to amateurs. Although we should not underestimate this newly acquired power of the web as a publishing medium for all, it is hard to keep up the tenet that social media are alternatives to mass media. Over the past few years, it has become increasingly obvious that the logics of mass media and social media are intimately intertwined. Not just on the level of platforms mechanics and content (tweets have become the equivalent of soundbites) but also on the level of user dynamics and business models; YouTube-Google now collaborates with many former foes from Hollywood to turn their platform into the gateway to the entertainment universe. Newspapers and television stations are inevitably integrated in the ecosystem of connective media where the mechanisms of data-driven user traffic determines who and what gets most attention, hence drawing customers and eyeballs.

This new connective media system has reshaped the power relationships between platform owners and users, not only in terms of who may steer information but also who controls the vast amount of user data that rushes through the combined platforms every day. What are the larger political and social concerns behind deceptively simple interfaces and celebrated user-convenient tools? Where in 2006 the notion of user power still seemed unproblematic, the relationship between users and owners of social media platforms is now contentious and embattled. In the wake of the growing monopolization of niches (Facebook for social networking, Google for search, Twitter for microblogging) it is important to redefine and reappraise the meaning of “social,” “public,” “community,” and “nonprofit.” The ecosystem of connective media has no separate spaces for the “public”; it is a nirvana of interoperability which major players argue for deregulation and which imposes American neoliberal conditions on a global space where boundaries are considered disruptions of user convenience. Common public values, such as independence, trust, or equal opportunities, are ready for reassessment if they need to survive in an environment that is defined by social media logic.

José van Dijck is a professor of Comparative Media Studies at the University of Amsterdam; her latest book, The Culture of Connectivity: A Critical History of Social Media has just been published by Oxford University Press (2013).

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Image credit: 3D little human character X9 in a Network, holding Tablet Computer. People series. Image by jojje9999, iStockphoto.

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Swartz was slated to go to trial this year but committed suicide in early January, prompting a public outcry against the prosecution in his case. Swartz was a prominent voice in the heated debate surrounding modern copyright law and public access and use (see his 2008 “Guerrilla Open Access Manifesto”). New York’s current issue contains a great feature from Wesley Yang discussing Swartz’s activism, his life, and the controversy in which he was embroiled.

In the ongoing debate over Swartz’s prosecution, we’ve pulled together a brief reading list on the issues surrounding American copyright in the digital age from OUP’s stable:

Copyright’s Paradox by Neil Weinstock Netanel

Netanel weighs current IP law against the basic right of freedom of speech. Like Swartz, he finds it unacceptably constricting.

The Oxford Introductions to U.S. Law: Intellectual Property by Dan Hunter

A concise overview of the current state and history of IP law in America from a prominent New York University IP expert.

Copyright and Mass Digitization by Maurizio Borghi and Stavroula Karapapa

Two UK scholars discuss “whether mass digitisation is consistent with existing copyright principles.”

How to Fix Copyright by William Patry

A Senior Copyright Counsel at Google takes a look at the changing economic realities of the globalizing, digitizing world and concludes that our government must “remake our copyright laws to fit our times.”

Democracy of Sound by Alex Sayf Cummings

An overview of music piracy stretching back to the advent of recorded sound. The RIAA made headlines throughout the last decade by litigating against users who shared music online, but musicians, record companies, songwriters, and fans were navigating this territory for nearly a century before the Internet became a factor.

Unfair to Genius: The Strange and Litigious Career of Ira B. Arnstein by Gary Rosen

The story of one early 20^th century musician who spent decades conducting high-profile lawsuits against the leading pop icons of the day. Though he never won a single case, Ira Arnstein managed to have a significant impact on the shape of music copyright through the decisions in his numerous cases.

Without Copyrights: Piracy, Publishing, and the Public Domain by Robert Spoo

Spoo homes in on the contested publication of Ulysses to reveal the impact on copyright of literary modernism (and vice versa). Characters such as Ezra Pound, the infamous publisher Samuel Roth, and of course James Joyce flesh out a revealing story about artists grappling with free speech and authorship.

Oxford University Press is committed to developing outstanding resources to support students, scholars, and practitioners in all areas of the law. Our practitioner programme continues to grow, with key texts in commercial law, arbitration and private international law, plus the innovative new ebook version of Blackstone’s Criminal Practice. We are also delighted to announce the new edition of the Max Planck Encyclopedia of Public International Law, one of the most trusted reference resources in international law. In addition to the books you can find on this page, OUP publishes a wide range of law journals and online products.

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Cyber attacks on Iran have been well publicised in the press and on Western television. General William Shelton, a top American cyber general, has now turned these attacks around saying that these events are giving Iran a strategic and tactical cyber advantage creating a very serious “force to be reckoned with.”

Since 2010, Iran’s infrastructure has been attacked hundreds of times by cyber viruses. To date the most documented and best known cyber attacks have been aimed at Iran and are known as cyber worms called Stuxnet. These electronic worms were used to attack Iranian nuclear power plants and connected systems. General Shelton, who heads up Air Force Space Command and Air Force cyber operations, gave a briefing to reporters in January 2013, where he said that the 2010 Stuxnet virus attack on Iran’s Natanz uranium processing plant had generated considered responses from Iran that have led to improved offensive and defensive cyber-capabilities.

In December 2012, the Stuxnet virus returned and hit computer and energy operations and companies in the southern Hormozgan region. Shelton claimed that Iran’s improved cyber defense capability had helped Iran protect it against subsequent attacks on oil terminals and other manufacturing plants. This new capability, he believed, will subsequently be used by Iran against its enemies in the near future. “They are going to be a force to be reckoned with,” said General Shelton, “with the potential capabilities that they will develop over the years.” At present he stated that America had over six thousand cyber specialists employed to monitor, analyse and counter cyber attacks, and he was intending to employ another thousand specialists over the next twelve months to improve America’s effectiveness in this vital area.

Moreover, assassinations and assassination attempts in conjunction with cyber attacks are thought to be part of an integrated plan of attacks on Iran’s nuclear research and manufacturing capabilities. A year ago on 11 January 2012, Ahmadi Roshan, a 32-year-old Iranian scientist, and his driver were both killed when a motorcyclist attached a bomb to their car as they were driving. So far these attacks, which seem to form part of the broader cyber-related strategy aimed at Iran’s nuclear program, have successfully killed five Iranian nuclear scientists in the last two years according to FARS, a Tehran news agency. However, in January 2013, the Iranian Intelligence Minister Heydar Moslehi claimed that his organisation had stopped a number of attempts to kill nuclear scientists so it is uncertain which reports are accurate.

These attacks on Iran’s electronic systems represent only a very small amount of the current cyber attack and threat capability. Increasingly, all governments and corporations must respond to the cyber reality. With an interconnected world, cyber attacks on infrastructure have become frequent and damaging. Cyber crime is costing businesses billions of pounds although they tend to keep quiet about the attacks. (The BBC reported that UK cyber crime costs £27bn a year.) Efforts to get a grip on the problem had been hampered by firms who don’t want to admit they had been the victims of attacks for fear of “reputational damage”. Baroness Neville-Jones, Prime Minister David Cameron, and Foreign Secretary William Hague met the bosses of some of Britain’s biggest businesses, including Barclays, HSBC, Tesco and BA, to urge them to take the problem more seriously.

In September 2012, a hacker called vorVzakone posted a message on a Russian online forum saying that a malevolent Trojan, called Project Blitzkrieg, was capable of attacking the American financial industry, that it had already critically affected up to five hundred American targets, and that it had stolen over five million dollars. “This attack combines both a technical, innovative backend with the tactics of a successful, organized cybercrime movement,” a McAfee report explained, adding that the next target would probably be investment banks.

Hackers, apparently working independently as criminal gangs, have grown in their specialization faster than most police and government intelligence organisations would have believed possible. Yet cyber hackers working for governments have targeted everything from computer systems to power plants from the US to Iran, Europe to China, Australia and beyond. These civil servant hackers are often employed by governments to help fulfill a strategy, to change information and publicity, or to gain information and bring systems down.

One example comes from Ray Boisvert, who recently retired from the post of Assistant Director of Intelligence for the Canadian Security Intelligence Service. He believes the current capabilities of most governments is not enough to counter the current cyber threats. He said that cyber threats were fundamentally undermining Canada’s “future prosperity as a nation.” He stated there is a lack of response on three levels. First from government and corporate policy-makers who do not, in his opinion, understand the technical complexities of digital telecommunications security. Second the government has not invested enough to protect Canada’s communications and electricity systems from cyber attacks. Third, he thought there was an inherent corporate shortsightedness regarding protecting Canada’s communications infrastructure.

The cyber issue is growing and will become a rising threat to governments and corporations. It may require a serious attack such as a massive electricity system shut down before a full government response is played out.

Alfred Rolington is the author of Strategic Intelligence for the 21st Century: The Mosaic Method, an industry insider’s assessment of current intelligence methods and offers a new strategic model, directed toward the police, military, and intelligence agencies. He was formerly CEO of Jane’s Information Group, responsible for such publications as Jane’s Defense Review and Jane’s Police Review, as well as CEO for Oxford Analytica. He has over thirty years’ experience of analytical publishing and media companies, producing information and intelligence for commerce, law enforcement, the, military and government. He has written about and given lectures on intelligence and strategic planning to Cambridge, Oxford, and Harvard Universities, and to organisations such as Thomson Reuters, the CIA, SIS (MI6), NATO Headquarters, and GCHQ.

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Image credits: Information Systems Technician 2nd Class Ryan Allshouse uses the intrusion detection system to monitor unclassified network activity from the automated data processing workspace. As a work of the U.S. federal government, the image is in the public domain via Wikimedia Commons;  Maps and charts are scanned from “Atlas of the Middle East”, published in January 1993 by the U.S. Central Intelligence Agency. [Public domain], via Wikimedia Commons

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Twitter is a joke factory, where professional comics and civilian jesters crank out one-liners round the clock.

In that joke factory, there are popular models. Every day, new jokes play on phrases such as “Dance like no one is watching,” “Sex is like pizza,” and “When life hands you lemons.” While the repetition can be maddening, I’m impressed by how, inevitably, there’s always another good joke lurking in even the most tired formula. “Give a man a fish” variations are endless, but there’s always a fresh catch, like this tweet by Erikka Innes:

Give a fish a man, he eats for a day. Teach a fish to catch a man and OH MY GOD DON'T STEAL MY AWESOME IDEA FOR A HORROR MOVIE

January 11, 2013 4:19 am via Twitter for iPhoneReplyRetweetFavorite

@nerdgirlcomedy

Erikka Innes

I can't believe it's almost 2013! I'm still writing a popular joke construction on all of my checks!

December 28, 2012 8:02 pm via webReplyRetweetFavorite

@gordonshumway

Jelisa Castrodale

I'm still writing hacky jokes on my checks.

January 1, 2013 4:09 pm via EchofonReplyRetweetFavorite

@bazecraze

Alex Baze

Ugh, I'm still writing this joke format on all my tweets.

January 1, 2013 3:26 am via webReplyRetweetFavorite

@ScottLinnen

Wile E. Quixote

Still writing "nobody accepts checks anymore, ya stupid check" on all my checks

January 1, 2013 4:50 pm via webReplyRetweetFavorite

@SarahThyre

Sarah Thyre

Ugh. I'm still writing "what is a check" on Twitter.

January 1, 2013 3:37 am via webReplyRetweetFavorite

@blondediva11

blondediva11

I’m still writing “WHY THE HELL IS THERE NO WAY TO PAY THIS ONLINE?” on all my checks.

December 31, 2012 11:37 pm via Tweetbot for iOSReplyRetweetFavorite

@TheNardvark

Bryan Donaldson

Ugh, still writing 2012 on my death threats.

January 10, 2013 9:50 am via Twitter for iPhoneReplyRetweetFavorite

@StellaRtwot

Denise

Dangit! I'm still writing "2012" on my suicide notes.

January 7, 2013 2:43 pm via webReplyRetweetFavorite

@jeffkreisler

jeffkreisler

So embarrassing, I'm still writing 2012 on my boss's car with my keys.

January 4, 2013 10:42 pm via webReplyRetweetFavorite

@RyanPurtill

Ryan Purtill

It's 2013, but I'm still writing "This will bounce" on all my checks.

January 10, 2013 12:20 pm via webReplyRetweetFavorite

@highwaytohelv

Highway To Helv

I'm still writing 112th Congress on my checks. (I don't have any money.)

January 3, 2013 9:46 pm via TweetDeckReplyRetweetFavorite

@slackmistress

Nina Bargiel

Ugh! It's 2013 and I can't believe I'm still writing "Child Support, choke on it Denise" on all my checks.

January 1, 2013 11:34 am via BufferReplyRetweetFavorite

@Ramsobot

Ramsey Ess

It's January 3. I can't believe I'm still writing "I’ve always viewed the smoke break as the golf course of the creative class" on my checks

January 4, 2013 1:29 am via Twitter for iPhoneReplyRetweetFavorite

@HitlerPuncher

I Punch Hitler

It's 2013, but I'm still writing "THE BLOOD OF MINE ENEMIES SHALL POUR DOWN LIKE RAIN" on my checks.

January 2, 2013 1:39 pm via webReplyRetweetFavorite

@ApocalypseHow

Rob Kutner

It's 2013 and I'm still writing "I want to go home" on all of my work emails.

January 7, 2013 11:45 am via Twitter for iPhoneReplyRetweetFavorite

@OhNoSheTwitnt

OhNo$heTwitnt

Ugh. I’m still writing “2082” on all the specimen jars in my time machine.

December 31, 2012 8:47 pm via Tweetbot for iOSReplyRetweetFavorite

@sween

Jason Sweeney

I'm still writing 2012 on allthsnarrgleflug HONK HONK

January 2, 2013 11:27 am via webReplyRetweetFavorite

@lanyardtwerk

lanyard

It's 2013 but hipsters are still writing 1890 on all their checks.

January 1, 2013 3:30 pm via EchofonReplyRetweetFavorite

@DanKennedy_NYC

Dan Kennedy

If you’re still writing 2012 on your cheques, the real question is, what’s with the British spelling?

January 7, 2013 12:51 pm via Tweetbot for iOSReplyRetweetFavorite

@mattthomas

Mαtt Thomαs

I'm still writing "KONY 2012" on all my children.

January 1, 2013 7:29 pm via Twitter for iPhoneReplyRetweetFavorite

@BeerBaron4life

Beer Baron

"I'm still writing 2012 on all my Czechs." -Guy who likes writing on people from Central Europe

January 1, 2013 1:19 pm via Twitter for iPhoneReplyRetweetFavorite

@TheDweck

Jess Dweck

Mark Peters is a lexicographer, humorist, rabid tweeter, and language columnist for Visual Thesaurus. He also writes Lost Batman Tales. Read his previous OUPblog posts.

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The uncharitable might say that I write the same book every four years or so. Some critics certainly accuse me of having said the same thing for many years. I don’t disagree. Since the early 80s, my enduring interest has been in the ways in which technology can modernize and improve the work of the legal profession and the courts. My main underpinning conviction has indeed not changed: that legal work is document and information intensive, and that a whole host of information technologies can and should streamline and sometimes even overhaul traditional methods of practicing law and administering justice.

What have changed, of course, are the enabling technologies. When I started out on what has become a career devoted largely to legal technology, the web had not been invented, nor had tablets, handheld devices, mobile phones, and much else. As new technologies emerge, therefore, I always have a new story to tell and more evidence that suggests the legal world is shifting from being a cottage industry to an IT-enabled information sector.

The evolution of my thinking reflects my own technical interests and career activities over the years. My first work in the field, in the 1980s, focused on artificial intelligence and its potential and limitations in the law. This began in earnest with my doctoral research at Oxford University. I was interested in the possibility of developing computer systems that could solve legal problems and offer legal advice. Many specialists at the time wanted to define expert systems in law in architectural terms (by reference to what underlying technologies were being used, from rule-based systems to neural networks). I took a more pragmatic view and described these systems functionally as computer applications that sought to make scarce legal knowledge and expertise more widely available and easily accessible.

This remains my fundamental aspiration today. I believe there is enormous scope for using technology, especially Internet technology, as a way of providing affordable, practical legal guidance to non-lawyers, especially those who are not able to pay for conventional legal service. These systems may not be expert systems, architecturally-defined. Instead, they are web-based resources (such as online advisory and document drafting systems) and are delivering legal help, on-screen, as envisaged back in the 1980s.

During the first half of the 90s, while I was working in a law firm (Masons, now Pinsent Masons), my work became less academic. I was bowled over by the web and began to form a view of the way it would revolutionize the communication habits of practicing lawyers and transform the information seeking practices of the legal fraternity. I also had some rudimentary ideas about online communities of lawyers and clients; we now call these social networks. My thinking came together in the mid-1990s. I became clear, in my own mind at least, that information technology would definitely challenge and change the world of law. Most people thought I was nuts.

A few years later, to help put my ideas into practice, I developed what I called ‘the grid’ – a simple model that explained the inter-relationships of legal data, legal information, legal knowledge, as found within law firms and shared with clients. I had used this model quite a bit with my clients (by this time, I was working independently) and it seemed to help lawyers think through what they should be doing about IT.

In the years that followed, however, I became even more confident that the Internet was destined to change the legal sector not incrementally and peripherally but radically, pervasively, and irreversibly. But I felt that, in the early 2000s, most lawyers were complacent. Times were good, business was brisk, and the majority of practitioners could not really imagine that legal practice and the court system would be thrown into upheaval by disruptive technologies.

Then came the global recession and, in turn, lawyers became more receptive than they had been in boom times when there had been no obvious reason why they might change course. Dreadful economic conditions convinced lawyers that tomorrow would look little like yesterday.

With many senior lawyers now recognizing that we are on the brink of major change, my current preoccupation is that most law schools around the world are ignoring this future. They continue to teach law much as I was taught in the late 1970s. They are equipping tomorrow’s lawyers to be twentieth century not twenty-first century lawyers. My mission now is to help law teachers to prepare the next generation of lawyers for the new legal world.

Richard Susskind OBE is an author, speaker, and independent adviser to international professional firms and national governments. He is president of the Society for Computers and law IT adviser to the lord chief justice. Tomorrow’s Lawyers is his eighth book.

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Image Credit: ‘The Grid’ courtesy of Richard Susskind. Used with permission. Do not reproduce without explicit permission of Richard Susskind.

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Try this experiment: Ask someone to name three tools, without thinking hard about it. This is a parlor game, not a scientific study, so your results may vary, but I’ve done this dozens of times and heard surprisingly consistent answers. The most common is hammer, screwdriver, and saw, in that order.

We seem to share a basic understanding of what tools are and how they’re used. This may be only natural; tools fill our lives. It’s hard to imagine going through your daily routine without them. You can’t brush your teeth or comb your hair; locked doors stay locked; mealtimes, in the preparation and the eating, are messy affairs. As Thomas Carlyle said, “Man is a tool-using animal. Without tools he is nothing, with tools he is all.”

But what does it mean to use tools? This question is of special interest in the area of animal behavior–many non-human animals use and even make tools. In 1980, Benjamin Beck published a book on the subject, Animal Tool Behavior, which catalogues hundreds of examples. (The first edition is out of print and was for a time extraordinarily expensive; when I first started searching for a copy online, I found just one at a price of $626.43. This is sometimes the nature of classic texts.)

Defining tool use is trickier than it might seem. A crow stripping a leaf stem and using it to fish for insects in soft wood? Tool use. Nest making with leaves and twigs? Not tool use. A wasp pounding earth down into a nest with the help of a pebble? Tool use. An otter balancing a rock on its chest to use as an anvil for pounding open molluscs? Tool use. A chimpanzee pounding open a nut on rocky ground? Not tool use. A gorilla using a stick to test the depth of water it intends to wade through? Tool use. A chimpanzee waving a leafy branch to intimidate an intruder? Only ambiguously tool use… The examples go on.

Beck directly took on the issue of definition:

Thus tool use is the external employment of an unattached environmental object to alter more efficiently the form, position, or condition of another object, another organism, or the user itself when the user holds or carries the tool during or just prior to use and is responsible for the proper and effective orientation of the tool.

It’s complex, in part because of the wide range of activities we interpret as tool use — and those we don’t. Notice that a definition purely in terms of physics won’t do. Using a rock held in the hand to break open an egg is tool use, but cracking the egg on a fixed hard surface is not, even if the forces are the same. And the intention of the tool user (Beck’s reference to responsibility) seems relevant as well. Incidental use of objects shouldn’t count. Sometimes a chimpanzee fleeing through the forest canopy might accidentally dislodge sticks that discourage a pursuer, but this doesn’t match our intuitions about tool use. Beck’s definition offers a reasonable compromise on a set of conditions for the behavior.

My students and I were interested in tool use because of its potential implications for robotics. Could the physical and cognitive abilities that enable animals (including humans) to use tools be translated into computational form? We worked with Beck’s definition for a time and eventually developed a simple software architecture that allowed a robot, which we called Canis habilis, to carry out a simple tool-using task.

Click here to view the embedded video.

Our interest in the use of tools by animals remained. We read the literature. We talked with cognitive scientists, animal behavior researchers, and philosophers of mind. I exchanged a few email messages with Dr. Beck. Gradually we developed a new perspective on tool use:

Tool use is the exertion of control over a freely manipulable external object (the tool) with the goal of (1) altering the physical properties of another object, substance, surface or medium (the target, which may be the tool user or another organism) via a dynamic mechanical interaction, or (2) mediating the flow of information between the tool user and the environment or other organisms in the environment.

I won’t go into a detailed motivation for the new definition, but I’ll note that we weren’t able to produce one that’s less complex than Beck’s, and some of the terms we use are themselves hard to define precisely. Do wasps have “goals”? Does “the flow of information” encompass communication? Despite its limitations, the new definition appealed to us, and Thomas Horton (my Ph.D. student at the time) and I eventually placed our work in the journal Animal Behaviour. We were happy. Thomas and I are computer scientists, outsiders to the field of animal behavior, but we’d learned enough to say something interesting. We discovered how interesting by asking experts in the field; our article went through three cycles of peer review before it was accepted.

Just last year Robert Shumaker, Kristina Walkup, and Benjamin Beck published a new edition of his book, which includes a new, refined definition of tool use that supersedes ours. We’re still happy. In some ways, doing research means holding a conversation in the literature, and it’s exciting to play even a small part. It’s the way science moves forward.

Robert St. Amant is an Associate Professor of Computer Science at North Carolina State University, and the author of Computing for Ordinary Mortals, from Oxford University Press. You can follow him on Twitter at @RobStAmant and read his Huffington Post column or his previous OUPblog posts.

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PB. The initials are not exactly as familiar as, say, BBC or NPR, but we’re not operating in a massively different environment. PB: Philosophy Bites.

Time was when to broadcast on the radio (or the ‘wireless’) you’d have to seek a license for permission to use a teeny weeny portion of the radio frequency spectrum. Broadcasting was time-consuming, bureaucratic, and above all expensive. It required staff and costly equipment and it was possible only with the support of highly-trained studio technicians and engineers.

No longer. The Philosophy Bites podcasts are recorded on a five-inch tape recorder in various offices (usually in Oxford or London) and edited on a laptop in a small (and unkempt) bedroom in North West London. Since it was launched five years ago, it’s had 15 million downloads. It is heard all over the world – in San Francisco, Tokyo, London and Sao Paolo – and its followers include professors, journalists, farmers and at least one American soldier stationed in Afghanistan (thanks for your email, Sir).

My background is in broadcasting, though I have an academic post. PB co-founder, Nigel Warburton, is a bona fide academic and makes successful forays into the media. We’re both passionate about philosophy, and Philosophy Bites tries to combine our skills and interests. But we’re essentially dependent on the knowledge and eloquence of our interviewees: we’ve conducted 200 interviews now – and by far the most rewarding aspect of our PB experience has been the free education we’ve received from some of the most significant philosophers in the English-speaking world.

And we have some advantages over traditional media. We can focus on our niche, the stuff we know about; we can post interviews when we like, and our interviews can be as long as we like – and as long as they deserve to be. There’s no red tape, and we’re not saddled with the broadcasters’ procrustean burden of cutting programmes to finish exactly on the pips at the top of the hour.

All this poses a threat to traditional media. If an increasing number of specialized podcasters cover their specialized topic as well or better than any general broadcaster can manage, audience figures for the powerful players will be slowly chipped away. They’ll probably have to focus on areas in which the minnows can’t compete — newsgathering, say, or live sporting events. But it’s good news for listeners — Philosophy Bites is part of a new landscape of content, provided by enthusiasts. CNN, BBC, NBC, ABC, and CBC will all survive, thankfully. But for the miniscule world of philosophy, another set of initials is on the scene: PB.

Here are a few of our most recent podcasts:

Or you can search the full back-catalogue, categorised by month and by topic.

David Edmonds is an award-winning documentary maker for the BBC World Service and a Research Associate at the Uehiro Centre for Practical Ethics at Oxford University. Nigel Warburton is Senior Lecturer in Philosophy at the Open University. They are co-authors of Philosophy Bites (OUP, 2010) and Philosophy Bites Back (OUP, 2012), which are based on their highly successful series of podcasts. You can also follow @philosophybites on Twitter.

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What does a computer scientist do? You might expect that we spend a lot of our time programming, and this sometimes happens, for some of us. When I spend a few weeks or even months building a software system, the effort can be enormously fun and satisfying. But most of the time, what I actually do is a bit different. Here’s an example from my past work, related to the idea of computational thinking.

Imagine you have a new robot in your home. You haven’t yet figured out all of its capabilities, so you mainly use it for sentry duty; it rolls from room to room while you’re not at home, turning lights and appliances on and off, perhaps checking for fires or burglaries.

Your robot is a simple reflex agent, in the jargon of artificial intelligence. It acts on reflexes, or rules: “If you sense such-and-such in the environment, then take such-and-such an action.” Your robot has a variety of sensors for identifying furniture and doorways and such, and you can write rules for it to follow: “When you sense a doorway with an end table to the right, then go through the doorway.” You can also place small signs in a room for the robot: “If you sense a sign with a red octagon next to a doorway, don’t go through that doorway.”

Here’s the question we became interested in: Given a specific behavior that you’d like the robot to carry out, and given the choice between making changes to either the robot’s program (writing new rules) or the environment (putting up new signs), what do you do?

We often choose between general versions of these two strategies (or apply both) in our everyday lives. For example, if my two-year-old niece is visiting, I can tell her not to play with various fragile knick knacks, but because “programming” a two-year-old isn’t very effective, I can also make some changes to the environment as a form of childproofing. I do the same to myself; I can “program” myself to remember to take a gift for a colleague to work in the morning, or instead I can place the package in front of the door so that I won’t leave without either picking it up or stepping over it. Cognitive scientists have studied such strategies under the umbrella of embodied and situated cognition, but less is known about how they might apply to interactive computer systems.

I set up an experiment with the help of David Christian, a graduate student working with me. Participants were given the task of directing a simulated robot through a small maze to reach a goal. At each intersection of the maze was a symbol: a square, a circle, a diamond, or a triangle. The robot was pre-programmed with a behavior for each symbol: turn left, turn right, or go straight. Here’s the tricky part. The robot’s program had a bug — the robot couldn’t reach the goal following its current program. To fix the problem, the participant could either change a rule or change a symbol at an intersection, making as many changes as needed (watching the robot run through the maze after each change) for the goal to be reached.

The robot is represented by an arrow, the goal by a yellow square

Our main question was this: Do participants have a natural preference between programmatic control of the robot versus modification of its environment? Each maze was set up so that a single change to either the robot’s program or its environment would produce the correct behavior. The two problem-solving strategies aren’t quite the same, though. Changing the robot’s program produces a “global” change in its behavior; if we were to change the green square symbol in the robot’s program to “Go straight,” that would apply in every intersection showing a green square. (If it’s not possible to go straight, the robot simply stops.) Changing the environment, on the other hand, is a “local” change; the difference is in the robot’s behavior at just one specific intersection.

About a third of the time participants chose only programming changes for a given maze, and about a third of the time they chose only environmental changes. In the cases where participants chose a mixture of programming and environmental changes, we saw an interesting pattern. They tended to choose one or more programming changes first, and then a series of environmental changes until the problem was solved. In 78% of the mixed cases, the first change was to the program, and in 89% of the mixed cases, the last change was to the environment. About half of our participants were computer programmers, but we saw no difference between programmers and non-programmers in our main performance measures.

The patterns in the mixed strategies are reminiscent of how we solve problems in the real world. For example, in government we have broad rules established at the federal level, with specialized problems handled at the local level. Business people sometimes talk about setting the ground rules for their cooperation and then dealing with specific situations as they arise. It turns out that this same pattern seemed to hold, at least some of the time, in the way people chose to solve problems in our robot control experiment. We make initial, global decisions that move us quickly through a problem, and then we make small, local changes until we hit upon a solution. We see this same approach in many areas of computing, from computer architecture to software engineering to artificial intelligence.

Let’s come back to computational thinking. Jan Cuny, Larry Snyder, and Jeannette Wing describe computational thinking as “the thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by an information-processing agent.” My own interest is in the commonality between strategies for computational thinking and strategies we apply for solving problems in our everyday lives. There are usually differences, but sometimes we can find basic similarities. Then we can say, “The way you go about solving this familiar problem is one version of a general strategy in computational thinking. Here’s how it works…”

Robert St. Amant is an Associate Professor of Computer Science at North Carolina State University, and the author of Computing for Ordinary Mortals, from Oxford University Press. You can follow him on Twitter at @RobStAmant and read his Huffington Post column or his previous OUPblog posts.

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Image credit: Maze image courtesy of Robert St. Amant. Used with permission.

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Some years ago I wrote a book on abortion that espoused women’s legal right to choose abortion, which was later cited in Roe v. Wade. It should have made me popular with feminists, but it did not and for one reason: I also argued that abortion is an ethical choice, and that not all abortions would necessarily be good choices. Trained as a philosopher, I pointed out that a traditional part of morality is deciding how to make good choices in the shaping of one’s life. No, I was indignantly told — the choice of abortion is a “personal choice” which needs no ethical justification, by either the woman or anyone else. That’s what women’s freedom is all about.

His Master's choice. (ca. 1932-1934) Arents Cigarette Cards. Source: NYPL.

I thought about those exchanges recently when I started to notice how choice seems to have become the all-purpose ethical term, used by liberals and conservatives, right and left. It is used by the left to defend gay marriage, almost any and all procreation choice, and the right to choose end-of life-care as one sees fit, including physician-assisted suicide.

“Choice” was used by the right to object to the requirement that everyone take out health insurance as part of the new health care legislation. People should be free to make their own choice about buying health insurance (though they lost out as a result of a recent Supreme Court decision). Mayor Bloomberg lost out last year on a proposal to tax people’s choice of sugared beverages, and came under fire this year for his proposal for a limit on their serving size (the ban was recently approved by the New York Board of Health). The beverage industry waged an all-out war against his proposals, citing people’s right to their own choice about how they care for their bodies.

Paul Ryan has been the leader of Republican efforts to reform Medicare by expanding the role of choice in deciding what kind of health insurance to buy under his plan to subsidize the program. But there is a twist in that instance about choice. The aim of that reform is to expand the range of choices not only in the name of freedom but also to control costs — putting “skin in the game,” as the saying goes. But it is well known that forcing money choices on patients often keeps them from doing things important for their health. The Republicans also rejected any feature in the drafting of the Affordable Care Act that would impose pressure on physicians to accept the results of good medical evidence from research. They should be completely free from government interference and allowed to make their own diagnostic and treatment choices.

Quite apart from the political use of the word, “choice” has also been a recurrent feature of the marketing of new medical technologies. Many are introduced in the name of expanding patient choices. Prenatal diagnosis for women at possible risk of a disabled child was introduced in the name of choice, putting no pressure on women one way or other to accept the procedure. But as a result of social pressure and in the name of responsible parenthood, it is almost as routine now as taking a pregnant woman’s blood pressure. A variety of new genetic tests can now determine someone’s likely medical future, including the possibility of Alzheimer’s and just about every other potentially lethal disease. No one will be forced to make use of that information; it will be a matter of choice, it is said. But if the history of new technologies is any guide, it will soon be considered ethically irresponsible not to make use of them.

What is to be made of the invocation of “choice” as a popular tool for winning a political battle — or of rejecting “choice” as the right way to win an ethical struggle? It depends on the other side of the coin. I believe public health trumps choice in the sugared beverage battle. Is it legitimate to use the word choice as a euphemism for unpopular causes? I don’t think so. Paul Ryan is using it in a way that hides the gradual reduction of Medicare benefits. Euthanasia supporters are either hiding or sugar-coating their policy goals. When new technologies are introduced in the name of choice should we believe it? Well, only if you want to ignore lessons from past technological innovations.

That’s all I choose to say for now.

Daniel Callahan is President Emeritus of The Hastings Center and author of the forthcoming book, The Roots of Bioethics: Health, Progress, Technology, Death (Oxford University Press).

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Happy 81^st Birthday, George Washington Bridge! The French architect Le Corbusier reportedly said you are “the most beautiful bridge in the world” – you “gleam in the sky like a reversed arch.” But are you really a work of art?

"George Washington Bridge. New York City." By Arthur Rothstein, 1941. From the Farm Security Administration - Office of War Information Photograph Collection at The Library of Congress.

The designer Othmar H. Ammann certainly was conscious of the need to make beautiful bridges. In 1958 he wrote: “Economics and utility are not the engineer’s only concerns. He must temper his practicality with aesthetic sensitivity. His structures should please the eye. In fact, an engineer designing a bridge is justified in making a more expensive design for beauty’s sake alone.”

Apart from its obvious elegance, I think that the George Washington Bridge (GWB) is notable perhaps for four reasons. First, at 3,500 feet it was nearly twice the span of the longest bridge at the time — the Ambassador Bridge at 1,850 feet. Second, Ammann was able to make huge cost savings by reducing the estimates of live load (i.e. due to traffic and trucks etc.) and relying on a relatively new so called ‘deflection theory’ to design the bridge. Third, the bridge was built during the Great Depression, but there wasn’t enough money — a cause of a change in appearance because the now famous steel towers were due to be faced in concrete and stone. Fourth, Ammann designed the bridge so that it could be added to, though that didn’t come about until 1962. With its 14 lanes of traffic it is now one of the busiest bridges in the world.

Given later events such as the collapse of the Tacoma Narrows Bridge — the famous ‘galloping Gertie’ which Ammann actually investigated — one could argue that Ammann’s design was ‘brave’. Large changes from what has gone before, as at Tacoma, can be challenging. It is interesting therefore that as a young man Ammann made his name early by writing a report on another famous bridge disaster — the Quebec Bridge that collapsed during construction in 1907. At the time the Quebec Bridge was also to be a very large span at 1800 feet, rivalled only by the Forth Railway Bridge in Scotland with main spans of 1710 feet and built in 1890. Ammann would have seen and learned how the many errors in the design and execution led to the downfall of Quebec. He would have contrasted that experience so strongly with the way Sir Benjamin Baker and Sir John Fowler took meticulous care with the Forth after they had witnessed the collapse of the Tay Bridge in Scotland in 1879. I suspect that he learned much from those experiences.

Suspension bridges are complex because the flow of forces in the structure is not easily calculated; engineers call them statically indeterminate. Only now with large computers can we model their behaviour with any confidence. Ammann was taught in Zurich at ETH by Wilhelm Ritter, the engineer who laid the basis for the new, but still rather approximate, deflection theory in 1877. Indeed Ritter taught arguably two of the greatest bridge designers of the early 20th century, Ammann and Robert Maillart, who was responsible for some beautifully elegant early reinforced concrete bridges in Switzerland including the world famous Salginatobel Bridge near Schiers. Ritter’s influence on two of his most accomplished pupils is clear in their work. Ritter emphasised the importance of visualising the flow of forces in the bridge and its relationship with aesthetics. Josef Melan improved the new deflection theory in 1888 and Leon Moisseiff used it to design the Manhattan Suspension Bridge in 1908. The theory was so-named because it took account of the deflections of the structure under live loads (i.e. the moving traffic, etc.). Moisseiff was confident that the theory was accurate but he later was to design Tacoma Narrows.

Perhaps Ammann was more aware of its limitations than some commentators, such as Henry Petroski, have intimated. He knew that the theory was based on quite severe simplifying assumptions. Darl Rastofer has written that Ammann was a reserved, self-effacing, and meticulous man, but one with a quiet inner confidence that meant he could hold his own. He was as comfortable at dealing with detail as well as taking an overview. Like others before him such as Thomas Telford at Menai Bridge in North Wales, Baker and Fowler at Forth, Ammann used theory. But unlike Theodore Cooper at Quebec and Sir Thomas Bouch at Tay, perhaps he was very careful to check and control the detail. I suspect that he was diligent in making sure he understood the flow of forces even if he knew he couldn’t calculate them precisely. I suspect that is why he went on to be so successful in leaving his mark on New York City with five major bridges that bear so much of the traffic flow to and from the city, and with his help on the high profile Golden Gate in San Francisco.

General view of North Side of Bridge from NJ Side of River. From the Library of Congress Prints and Photographs Division.

So is the GWB a work of art? Art is difficult to define but we can say it is a power of the practical intellect, the ability to make something of more than ordinary significance. Is the GWB an extraordinary bridge? Did Ammann achieve aesthetic sensitivity? He certainly achieved practicality; no-one can fail to be impressed. Le Corbusier liked it, so that is good enough for most of us. But of course Le Corbusier was a modernist, so he liked functionality; for example he saw buildings ‘as machines for living in’. All in all I think it is no accident that suspension bridges are some of the most beautiful structures we see around us. The graceful curves of the cables are the defining feature and they are entirely natural structures. They are the best examples of harmonious form and function. The GWB is one of the best as was Othmar Ammann.

Emeritus Professor David Blockley is a Senior Research Fellow at the University of Bristol, UK. He has won several awards including the Telford Gold Medal of the Institution of Civil Engineers. He has written over 160 technical papers and 7 books – the latest of which are Bridges: The Science and Art of the World’s Most Inspiring Structures and Engineering: A Very Short Introduction. Read his previous blog post: “The ingenious problem-solving of the modern-day engineer.”

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It’s widely held that computer programming is the new literacy. (Disagreement can be found, even among computing professionals, but it’s not nearly as common.) It’s an effective analogy. We all agree that everyone should be literate, and we might see a natural association between writing letters for people to read and writing programs for computers to carry out. We also find a historical parallel to the pre-Gutenberg days, when written communication was the purview mainly of the aristocracy and professional scribes. Computation is an enormously valuable resource, and we’re only beginning to explore the implications of its being inexpensively and almost universally available.

But is programming-as-literacy an appropriate analogy? We tend to think that basic literacy is achieved by someone who can say, “Yes, I can read and write.” Let’s see what this means in the context of programming.

Historically, programming has been a matter of writing down instructions for a computer to follow, a style now called imperative programming. This is trickier than giving instructions to a human being, though. You’re a human being, which means you know what others are capable of doing and what they will understand. For example, if you were writing down instructions as part of a recipe, you might say, “Place two cups of frozen peas in the microwave for six minutes.” You don’t bother to add that the microwave should be on for those six minutes, that the peas should be in a container, or that “cups” means the English measuring units rather than, say, two coffee mugs. The capabilities of a computer are less obvious, though, which makes instructions harder to write. Worse, they don’t “understand” anything at all, at least in the same sense that people do. In 1998, for example, the Mars Climate Orbiter was lost, because one programming team used English units, and another team used metric units. A reasonable person given a set of instructions for maneuvering through space might wonder, “Are we all clear on what we’re talking about?” A computer would need to be given instructions to do the same.

Other approaches to programming have emerged over the years, and they involve something different from writing instructions. In some environments programming has the flavor of creating a rulebook, as you might do for a new board game. Your rules aren’t directly concerned with the details of specific games: “If Jane rolls a four with her dice and moves her piece to a red square, then…” Instead, your rules govern the flow of a game — any game — at a more abstract level. “If a player lands on a red square, then…” You develop comparable rules when you write a spreadsheet macro. Your macro (a tiny program in itself) isn’t concerned with specific numbers, but more generally with the mathematical relationships between cells that contain those numbers. “The number in this cell is the sum of the numbers in these other cells.” Ideally, your program will work on cells that contain any numbers at all; it depends on the structure of a given spreadsheet rather than its specific contents. Thinking about how to express these rules, or constraints, is part of constraint-based programming.

Yet other kinds of programming are like writing out appropriate responses for workers in a customer service department. Such-and-such a request from a customer should be handled with this procedure; business rules behind the scenes govern what’s possible and what’s not. Programming a graphical user interface means thinking along similar lines. The application waits for a button press or a menu selection, runs the relevant procedure, and then responds. This is event-driven programming, in which each event triggers its own small program to do the right thing.

Does all this sound like literacy? I’d argue yes, that these are no less forms of literacy than being able to write a business plan, a compelling legal brief, or perhaps an evocative concrete poem. In these more familiar examples of writing, literate people are expressing themselves with knowledge of a set of underlying concepts, conventions, and goals. But we wouldn’t expect hundreds of thousands of people in any given year to try to become businesspeople, lawyers, or poets in their spare time. What makes programming special?

One answer comes from Alan Turing, the father of computer science. In 1950, he wrote:

This special property of digital computers, that they can mimic any discrete state machine, is described by saying that they are universal machines. The existence of machines with this property has the important consequence that, considerations of speed apart, it is unnecessary to design various new machines to do various computing processes. They can all be done with one digital computer, suitably programmed for each case. It will be seen that as a consequence of this all digital computers are in a sense equivalent.

It seems obvious that our everyday world can’t be shoehorned into a perspective that’s all about business or legal briefs or even poetry. But a computational perspective? The universality of computers makes the idea more promising. Konrad Zuse, a German computing pioneer, speculated in 1967 that all of physical existence might be interpreted in terms of computation, and this possibility has seen growing attention in the years since. Even if we can’t reprogram the basic principles of the universe, it’s a fascinating thought that the principles might be computational. That seems worth understanding, and learning how to program is one way to start.

If this isn’t compelling enough, we can be more practical. A few years ago, for example, I was curious whether the Democratic and Republican candidates for President used different words in their debate. I could have spent a few minutes looking for a text analysis application online and figuring how to use it, but instead I spent the time writing a small program of my own that counted unique words, ignoring the non-meaningful ones, and compared the results. This was easy, partly because I know how to program, but probably more because I’ve learned a useful set of concepts, strategies, and skills for solving computational problems. A side benefit of learning to program. The results my program generated were nothing unexpected, but after I was finished I felt a small, familiar sense of accomplishment. I’d built something new, by myself, rather than depending on what others had given me.

Literacy, even programming literacy, can be its own reward.

Robert St. Amant is an Associate Professor of Computer Science at North Carolina State University, and is the author of Computing for Ordinary Mortals, out this December from Oxford University Press.

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Image credit: Lines of computer code in different languages with circuit board on the background. Image by tyndyra, iStockphoto.

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Innovation: A Very Short Introduction

By Mark Dodgson and David Gann

The next big thing in innovation lies in the ways we innovate using technology. We’re used to thinking about innovations that are technologies — the computer, the Internet, the laser, and so on. But technology is now being used to produce better innovations than ever before. By better, we mean innovations that meet our personal, organizational, and social requirements in new and improved ways, and aren’t just reliant on the technical skills and imagination of corporate engineers and marketers.

Here’s some examples of what we mean. If you have ever been lucky enough to design and build a home, you would have been confronted by technical drawings that are incomprehensible to anyone but trained architects. Nowadays you can have a computerised model of your house that lets you move around it in virtual reality so that you get a high fidelity sense of the layout and feel of rooms. You get to know what it really will look like, and make changes to it, before a brick is laid.

Move up a level and consider the challenges confronting the redesign of Cannon Street station in London. This project involved not only redesigning the station, but also building an office block above it, whilst maintaining access to the fully operational Underground station beneath it. The project used augmented reality technology to assist the design and planning process. Using a smartphone or tablet, augmented reality overlays a digital model on the surrounding real world, so you can see hidden infrastructure such as optical fibers, sewers, and gas lines — and get a sense of what things will look like before work begins. This is especially valuable for dealing with various vintages of infrastructure in busy city environments and when there are concerns about maintaining the integrity of listed buildings.

The key principle in these examples is that non-specialists can become involved in decisions that were previously only made by experts.

Other technologies that encourage this ‘democratization’ of innovation include rapid prototyping. This technology changes the economics of manufacturing, so it becomes feasible to make bespoke, individualized products cheaply. If you design something yourself, you don’t need expensive molds, dies, and machine tools to make it. We are quickly developing technologies that can produce your designs on the spot on your desk.

The Internet underlies much of the advance in the ways we innovate. It allows us to collect information from a massively increased population of designers, producers and users of innovation. It connects ideas, people and organizations. Also important is the ‘Internet of things’ that is the vast number of mobile devices and sensors that are connected together and produce data that can be valuably used to make better decisions. Drivers’ mobile phones, for example, can locate cars and traffic jams and allow better planning of transport flows. We have it from a reputable source that more transistors — the building blocks of sensors and mobile devices — were produced last year than grains of rice were grown. And they were produced at lower unit cost.

We’re all much better attuned at processing images rather than text and data. Half our cerebral cortex is devoted to visualization. Technologies developed in the computer games and film industries — think Toy Story and World of Warcraft — are being used to help innovators in areas ranging from pharmaceuticals to emergency response units in cities. The capacity, which these new technologies bring to produce dynamic images of what was previously opaque technical information, underlies the greater engagement in innovation by a wider range of people.

The technology that seems likely to have the greatest impact globally on innovation is the smartphone. Just think how short a period of time we’ve been using them and yet how much we use them for. Quite apart from putting us in direct contact with the majority in the world’s population, we use them to shop, bank, pay bills, and map our way. We use a myriad of apps for all sorts of productive and entertaining purposes. Nearly 6 million of the world’s 7 million people have mobile phones and in many developing countries there are more mobiles than people.

These devices provide opportunities for innovation amongst billions of people that have previously been excluded from the global economy for lack of information and money. Smartphones provide everyone with access to all the staggering amount of information available on the web. They can also allow access to finance, especially small amounts of money. Less than 2 billion people in the world have bank accounts and banking on smartphones allows billions of previously disenfranchised people to borrow, trade, and be reimbursed for their ideas and initiative. In this way, technology makes innovation more inclusive and less the privilege of corporations with research and development departments. We look forward to a massive wave of exciting new and unimaginable ideas from all sorts of people from everywhere around the world.

Mark Dodgson is Director of Technology and Innovation Management Centre, University of Queensland Business School, and David Gann is Head of Innovation and Entrepreneurship at Imperial College London. They co-authored Innovation: A Very Short Introduction.

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Image credit: Above Cannon St Station, London, by Tom Morris (Creative Commons License). Source: Wikimedia Commons.

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Computational analysis and feminist theory generally aren’t the first things that come to mind in association with fairy tales. This unlikely pairing, however, can lead to important insights regarding how cultures understand and represent themselves. For example, by looking at how characters are described in European fairy tales, we’ve been able to show how Western culture tends to bias the younger generation, especially the men. While that result probably won’t shock anyone more than passingly familiar with the Western world, the method of reaching these results allows us to look at cultural biases in a new light. Our study and many others like it are part of a growing trend in applying the power of computing and quantitative analysis toward understanding ourselves.

This is not a new idea. Isaac Asimov’s science fiction Foundation novels, dating back to 1942, explore the repercussions of being able to mathematically predict human activity based on an analysis of history. In the early 20th century, the Annales school of history began crunching historical numbers to learn more about cultures on a large scale. Various groups since then have risen with similar goals, including the cliometricians in the 1960s and the cliodynamicists more recently.

Folklorists, too, have always been interested in tracing large-scale patterns in expressive culture ranging from storytelling to pottery. In one now-classic example of structural analysis, Russian folklorist Vladimir Propp separated fairy tales into plot components based upon the action being performed regardless of the character performing it (hence it doesn’t matter whether a witch or dragon steals the princess; what matters is that the princess has been removed from the civilized sphere, creating the need for a hero and a quest). More recently, folklorists such as Kathleen Ragan and Timothy Tangherlini  have been using statistical analysis and geographical information systems to study gender bias in folktale publications and storytelling diffusion over time and space.

The biggest news to hit the streets recently combined the power of Google, a few Harvard mathematicians, and five million digitized books covering the last two centuries. They dubbed their computational study of culture “culturomics”, and several more research projects have grown in its wake.

This type of research has traditionally been limited by inadequate technology, incomplete data, and the scarcity of scholars well-versed in both computation and traditional humanities research. That scene is now changing, due largely to efforts from both sides of the cultural divide, the humanities and the sciences. It is in this context that we undertook a study of European fairy tales, yielding interesting and occasionally unexpected results.

An analysis of over 10,000 references to people and body parts in six collections of Western European fairy tales can reveal quite a bit. Understanding fairy tales pays off twofold: they reveal the popular culture and beliefs of the past, while simultaneously showing what cultural messages are being transferred to modern readers. There is no doubt that the Disney renditions of classic fairy tales both reflect assumptions of the past and helped shape the gender roles of the present.

One finding from this analysis dealt with the use of adjectives when describing bodies or body parts in the stories. The most frequently-used adjectives cluster around the themes of maturation, gaining and maintaining beauty or wealth, and the struggle for survival, all concepts that still have a prominent place in our culture.

The use of age in these stories is of particular interest. While young people are described more than twice as frequently as old, the word old (and similar words indicating old age) appears more frequently than the word young (and related terms). That means the tellers of these stories rarely find it necessary to mention when someone is young, but often feel the need to describe the age of older people.

In fact, old people tend to attract more adjectives than their younger counterparts in general. If someone is going to be described in any way at all, whether it be about their beauty or their age or their strength, it’s far more likely that those descriptions are attached to the old rather than the young. This trend also holds true with regards to gender; men are described significantly less frequently than women. Combining these facts, it appears that although old women are brought up relatively infrequently, they are described much more frequently than would be expected.

The fact that women are described more frequently than men fits with a common feminist theory suggesting Western culture treats the male perspective as universal, unmarked, public, and default. Extending that theory further, the fairy tale analysis reveals that the young perspective is also default and unmarked. Older people and especially older women must be described in greater detail and with greater frequency, marking them as old or as women or both, because otherwise the character is assumed as young and masculine, maintaining those traits which are considered defaults.

These results just scratch the surface of what can be discovered using the automated and quantitative analysis of cultural data. As technology and data sources improve, there will be an increasing number of studies which combine algorithms and statistics with traditional humanistic theories and frameworks. The holy grail, which we are reaching ever-closer to, is the successful bridging of traditional close reading approaches of humanistic inquiry and the distant reading quantitative methods being developed by researchers like Franco Moretti and the Google Ngrams Team. This is another step on that path.

Scott B. Weingart is an Information Science Ph.D. student at Indiana University studying the history of science. and Dr. Jeana Jorgensen is a recent graduate of Indiana University who specializes in folklore and gender studies. This work is from a paper they co-presented at Digital Humanities 2011, for which they won the Paul Fortier Prize for best young researchers at the conference. The paper ’Computational analysis of the body in European fairy tales‘ is in the journal Literary and Linguistic Computing, and is available to read for free for a limited time.

Literary and Linguistic Computing is an international journal which publishes material on all aspects of computing and information technology applied to literature and language research and teaching. Papers include results of research projects, description and evaluation of techniques and methodologies, and reports on work in progress.

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Image credits:
The Oxford Treasury of Fairy Tales, ed. Geraldine McCaughrean & Sophy Williams, Oxford University Press, 2012.
Fairy Tales and Other Stories by Hans Christian Andersen, ed. W.A. & J.K. Craigie, Oxford University Press, 1914: via digitized content at the New York Public Library.

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