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Revolutionary alphabet book spells out the benefits of socialism

Politics and picture books might not seem like logical bedfellows, but The ABCs of Socialism is all about providing a fresh take on an old idea. Filled with distinctive illustrations that lead you through the for against arguments surrounding socialism, the beautifully designed book reads like a more comprehensive version of some of the internet's best infographics.

“It was a privilege to play my part in this project,” says illustrator Phil Wrigglesworth, explaining that the book came about “through a new energy in both the US and Europe for socialist thinking, with both Bernie Sanders and Jeremy Corbyn leading the way.” The book shows a series of questions and answers, which are designed to debunk common ideas about socialism and each have an accompanying illustration.

“Traditionally visual communication on the left has been very loud and shouty,” remarks Wrigglesworth, on the design and colour scheme of the book. “Jacobin has a softer, more persuasive approach.” The illustrations are played out in a mirror image of the front and back cover of the book. “As the figures and setting are quirky and fun, the book is less a lecture and more about being fun and educational,” he adds.

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The ABCs of Socialism debunks left wing myths
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The book caters to a new wave of socialist enthusiasm
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The book's illustrations veer away from shouty, preachy messages
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Fun illustrations help to try and make the book educational and experimental

This article was originally published in Computer Arts magazine issue 258. Buy it here.

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Finding patterns in corrupted data

  • A team, including researchers from MIT’s   Science and Artificial Intelligence Laboratory, has created a new set of algorithms that can efficiently fit probability distributions to high-dimensional data.

    A team, including researchers from MIT’s __computer Science and Artificial Intelligence Laboratory, has created a new set of algorithms that can efficiently fit probability distributions to high-dimensional data.

    Image: MIT News

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  • Data analysis — and particularly big-data analysis — is often a matter of fitting data to some sort of mathematical model. The most familiar example of this might be linear regression, which finds a line that approximates a distribution of data points. But fitting data to probability distributions, such as the familiar bell curve, is just as common.

    If, however, a data set has just a few corrupted entries — say, outlandishly improbable measurements — standard data-fitting techniques can break down. This problem becomes much more acute with high-dimensional data, or data with many variables, which is ubiquitous in the digital age.

    Since the early 1960s, it’s been known that there are algorithms for weeding corruptions out of high-dimensional data, but none of the algorithms proposed in the past 50 years are practical when the variable count gets above, say, 12.

    That’s about to change. Earlier this month, at the IEEE Symposium on Foundations of Computer Science, a team of researchers from MIT’s Computer Science and Artificial Intelligence Laboratory, the University of Southern California, and the University of California at San Diego presented a new set of algorithms that can efficiently fit probability distributions to high-dimensional data.

    Remarkably, at the same conference, researchers from Georgia Tech presented a very similar algorithm.

    The pioneering work on “robust statistics,” or statistical methods that can tolerate corrupted data, was done by statisticians, but both new papers come from groups of __computer scientists. That probably reflects a shift of attention within the field, toward the computational efficiency of model-fitting techniques.

    “From the vantage point of theoretical computer science, it’s much more apparent how rare it is for a problem to be efficiently solvable,” says Ankur Moitra, the Rockwell International Career Development Assistant Professor of Mathematics at MIT and one of the leaders of the MIT-USC-UCSD project. “If you start off with some hypothetical thing — ‘Man, I wish I could do this. If I could, it would be robust’ — you’re going to have a bad time, because it will be inefficient. You should start off with the things that you know that you can efficiently do, and figure out how to piece them together to get robustness.”

    Resisting corruption

    To understand the principle behind robust statistics, Moitra explains, consider the normal distribution — the bell curve, or in mathematical parlance, the one-dimensional Gaussian distribution. The one-dimensional Gaussian is completely described by two parameters: the mean, or average, value of the data, and the variance, which is a measure of how quickly the data spreads out around the mean.

    If the data in a data set — say, people’s heights in a given population — is well-described by a Gaussian distribution, then the mean is just the arithmetic average. But suppose you have a data set consisting of height measurements of 100 women, and while most of them cluster around 64 inches — some a little higher, some a little lower — one of them, for some reason, is 1,000 inches. Taking the arithmetic average will peg a woman’s mean height at 6 feet 4 inches, not 5 feet 4 inches.

    One way to avoid such a nonsensical result is to estimate the mean, not by taking the numerical average of the data, but by finding its median value. This would involve listing all the 100 measurements in order, from smallest to highest, and taking the 50th or 51st. An algorithm that uses the median to estimate the mean is thus more robust, meaning it’s less responsive to corrupted data, than one that uses the average.

    The median is just an approximation of the mean, however, and the accuracy of the approximation decreases rapidly with more variables. Big-data analysis might require examining thousands or even millions of variables; in such cases, approximating the mean with the median would often yield unusable results.

    Identifying outliers

    One way to weed corrupted data out of a high-dimensional data set is to take 2-D cross sections of the graph of the data and see whether they look like Gaussian distributions. If they don’t, you may have located a cluster of spurious data points, such as that 80-foot-tall woman, which can simply be excised.

    The problem is that, with all previously known algorithms that adopted this approach, the number of cross sections required to find corrupted data was an exponential function of the number of dimensions. By contrast, Moitra and his coauthors — Gautam Kamath and Jerry Li, both MIT graduate students in electrical engineering and computer science; Ilias Diakonikolas and Alistair Stewart of USC; and Daniel Kane of USCD — found an algorithm whose running time increases with the number of data dimensions at a much more reasonable rate (or, polynomially, in computer science jargon).

    Their algorithm relies on two insights. The first is what metric to use when measuring how far away a data set is from a range of distributions with approximately the same shape. That allows them to tell when they’ve winnowed out enough corrupted data to permit a good fit.

    The other is how to identify the regions of data in which to begin taking cross sections. For that, the researchers rely on something called the kurtosis of a distribution, which measures the size of its tails, or the rate at which the concentration of data decreases far from the mean. Again, there are multiple ways to infer kurtosis from data samples, and selecting the right one is central to the algorithm’s efficiency.

    The researchers’ approach works with Gaussian distributions, certain combinations of Gaussian distributions, another common distribution called the product distribution, and certain combinations of product distributions. Although they believe that their approach can be extended to other types of distributions, in ongoing work, their chief focus is on applying their techniques to real-world data.


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    Oxfam rolls out Facebook Workplace to help 10,000 staff across 90 countries feel 'right down the digital corridor'

    Oxfam has rolled out Workplace, Facebook’s new communication and collaboration platform for businesses, and aims to add 8,000 internal users to the app over the next 12 months.

    The decision follows a successful soft launch of the cloud-based communication and collaboration platform last August. The platform proved particularly suited to the global nature of Oxfam’s workforce, which covers 10,000 staff members across 90 different countries.

    “You feel like you're very remote a lot of the time at Oxfam, so the challenge is how do you create an environment where you feel like you're close to your kindred spirits,” said Jim Daniell, COO at Oxfam America. 

    “In the past if you really wanted to bring all the specialists of a certain type together you'd have to spend a lot of money and time to fly them together to a meeting point. Now we're trying to create a digital equivalency where people can feel like they're right down the digital corridor."

    Read next: Facebook's Workplace pricing and features: What your business needs to know

    Among the early adopters at Oxfam was the global humanitarian team, responsible for coordinating humanitarian responses all over the world which normally involve multiple affiliates of Oxfam International.

    “One of the most important tools for them is to have a common set of collaboration spaces because time equals lives saved,” said Daniell.

    “If you're busy in the middle of a response the last thing in the world you want is to not be able to find important files and not be able to pass information quickly. “

    The mobile-first focus was a major selling point of Workplace. It was especially useful for the thousands of volunteers doing three-month stints in areas of the world where network links are often low, access to computers is limited and a car seat can be as common a workplace as an office desk.

    Facebook familiarity

    The ubiquitous presence of Facebook’s signature social network was one of the deciding factors when weighing the merits of Workplace against competitors such as Slack.

    “To standardise we ended up picking Workplace, primarily because of familiarity with the application by so many people," said Daniell. 

    “A big part of being a charity is you don't have the money to put in place lots of corporate training and tools, so when you roll something out you have to do it basically on a shoestring."

    The familiarity also made staff receptive to the launch of the professional version. 

    “It's not too often that you roll something out and you get kind of a cheer from your staff,“ he said.

    "What people like about it is that with almost no effort they know how to post on the wall, put information up, form a group. They get it."

    Read next: 15 top enterprise tech startups: How fast they're growing, how much funding they're getting and will they IPO?

    Another advantage of the platform was the integration with Oxfam’s existing tools, the cloud-storage system Box and the content management system (CMS) Drupal.

    “Getting the system to integrate into the systems you already have is key,” said Daniell.

    “To make it simple with integrated it all through Okta, and then through Okta we integrated into Facebook. We use Okta to both login and to provision the accounts.”

    Workplace security concerns

    Workplace was chosen only after receiving assurance that data security and privacy would be fully protected.

    “This is not a consumer app anymore, this is our data not yours. It's very important, some of the information contained in Workplace is sensitive," said Daniell.

    “We worked very hard to ensure that not only did we own the data, but that it was consistent with EU/US privacy guidelines and we could substitute the Facebook privacy statements and ULA [User Licensing Agreement] with an Oxfam-specific one.”

    Another priority was that access could be immediately granted but also quickly revoked. Oxfam was concerned that cloud-based tools such as Slack were being used by staff through their personal accounts rather than company ones, and when employees left Oxfam, the charity would also lost the the data. Workplace allowed Oxfam to control the data and the access to it through the charity's normal tools.

    “When we provision you as a new employee, automatically we can provision all of your Facebook account. As soon as you leave we can automatically turn off your access to it, but keep the account," said Daniell.

    Oxfam said the platform had increased productivity, real-time collaboration and decreasing operational inefficiencies. Daniell added that the data to statistically assess the improvements was not yet available, but the anecdotal evidence of the benefits was persuasive.

    “The jury's out as to whether or not social tools will increase productivity," he said. "For me, hard productivity numbers will be measured over time, but the soft issue is the sense of closeness that most people can't get.”

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    Making it easier to collaborate on code

  •  “Gitless

    “Gitless" removes complicated concepts like "staging" and "stashing," without fundamentally changing Git's core functionality.

    Image: Santiago Perez De Rosso

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  • Gitless (left) simplifies many of the more complicated concepts that exist in Git.

    Gitless (left) simplifies many of the more complicated concepts that exist in Git.

    Santiago Perez De RossoI

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  • Git is an open-source system with a polarizing reputation among programmers. It’s a powerful tool to help developers track changes to code, but many view it as prohibitively difficult to use.

    To make it more user-friendly, a team from MIT’s __computer Science and Artificial Intelligence Laboratory (CSAIL) has developed “Gitless,” an interface that fixes many of the system’s core problems without fundamentally changing what it does.

    “With Gitless we’ve developed a tool that we think is easier to learn and use, but that still keeps the core elements that make Git popular,” says graduate student Santiago Perez De Rosso, who co-wrote a related paper with MIT Professor Daniel Jackson. “What’s particularly encouraging about this work is that it suggests that the same approach might be used to improve the usability of other software systems, such as Dropbox and Google Inbox.”

    Gitless was developed, in part, by looking at nearly 2,400 Git-related questions from the popular programming site StackOverflow. The team then outlined some of Git’s biggest issues, including its concepts of “staging” and “stashing,” and proposed changes aimed at minimizing those problems.

    Because Gitless is implemented on top of Git, users can easily switch between the two without having migrate code from one to the other. Plus, their collaborators don’t even have to know that they aren’t big fans of Git.

    Perez De Rosso will present the paper at next month’s ACM SIGPLAN conference on “Systems, Programming, Languages and Applications: Software for Humanity” in Amsterdam.

    How it works

    Git is what’s called a “version control system.” It allows multiple programmers to track changes to code, including making “branches” of a file that can be worked on individually.

    Users make changes and then save (or “commit”) them so that everyone knows who did what. If you and a colleague are on version 10 of a file, and you want to try something new, you can create a separate “branch” while your friend works on the “master.”

    Makes sense, right? But things get confusing quickly. One feature of Gitless is that it eliminates “staging,” which lets you save just certain parts of a file. For example, let’s say you have a file with both finished and unfinished changes, and you’d like to commit the finished changes. “Staging” lets you commit those changes while keeping the others as a work-in-progress.

    However, having a file with both a staged and working version creates tricky situations. If you stage a file and make more changes that you then commit, the version that’s committed is the one you staged before, not the one you’re working on now.

    Gitless essentially hides the staging area altogether, which makes the process much clearer and less complex for the user. Instead, there’s a much more flexible “commit” command that still allows you to do things like selecting segments of code to commit.

    Another concept that Gitless removes is “stashing.” Imagine that you’re in the middle of a project and have to switch to a different branch of it, but don’t yet want to commit your half-done work. Stashing takes the changes you’ve made and saves them on a stack of unfinished changes that you can restore later. (The key difference between stashing and staging is that, with stashing, changes disappear from the working directory.)

    “The problem is that, when switching branches, it can be hard to remember which stash goes where,” says Perez De Rosso. “On top of that, stashing doesn’t help if you are in the middle of an action like a merge that involves conflicting files.”

    Gitless solves this issue by making branches completely independent from each other. This makes it much easier and less confusing for developers who have to constantly switch between tasks.

    Gitless certainly isn’t the first effort to improve Git. But according to Philip Guo, an assistant professor of cognitive science at the University of California at San Diego, who was not involved in the project, it is the first to go beyond Git’s interface and actually deal with core conceptual issues.

    “This work applies rigorous software-design research techniques to uncover shortcomings in one of the world’s most widely-used pieces of software,” Guo says. “In the past, many practitioners have made anecdotal arguments both for and against Git, but no prior work has taken a scientific approach to unpacking those arguments.”

    Results

    The team also conducted a user study to test Gitless’ performance against Git. The researchers found that Gitless users were more successful at completing tasks than Git users, and, for at least one task, performed it significantly quicker. (Perez De Rosso points out that the study’s participants were all well-versed in Git, and suggest that the results may have been even more pronounced if the team had tested Gitless on people with no Git experience.)

    In a post-task survey, participants were particularly impressed with Gitless’ ability to transition between branches, which they described as “very smooth” and “way more intuitive.”

    Guo describes Gitless as a valuable form of “training wheels” to help beginner programmers get started with Git. At a higher level, he says that the team’s framework could be an important tool for looking at other software systems.

    Perez De Rosso says that he is particularly excited by the possibility of analyzing Google Inbox’s concept of bundled “conversations,” as well as Dropbox’s notion of “shared folders.”

    “Perhaps the most long-lived contribution of this research is not the analysis of Git itself, but rather the methodology that the authors used to analyze, dissect, and redesign a popular piece of software,” Guo says. “The power of the authors' approach to analyzing design flaws can be applied to many kinds of popular software.”


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    Competition: Win a Mafia 3 gaming bundle from Numskull worth £40

    We have teamed up with Numskull to offer you the chance to win some great Mafia 3 gaming goodies.

    One lucky reader will win a Mafia Xbox One skin, 223rd Infantry Wallet and a Hanger 13 Snapback. You can take a closer look at all of the items in the giveaway on Numskull's website.

    If you'd like to get your hands on this brilliant bundle, all you need to do is use the giveaway form below to be in with a chance of winning. Simply log in to Gleam to use the entry options. You can choose to enter just once by picking one of the options after signing up below, or you can increase your chances of winning by choosing two or more options. If you already follow us on Twitter or Like us on Facebook, that'll count too. Simply press the +1 button and follow the instructions provided.

    Win a Mafia III Gaming Bundle

    The competition ends at midnight on 6 November and the winner (who will be chosen completely at random) will be notified shortly after. Click here for terms and conditions.

    Good luck!

    You'll also like: 2016's most anticipated games

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    London Theatre Direct's API strategy sees 600 percent rise in sales

    West End theatre ticket seller London Theatre Direct is using API connectivity with the major venues and theatre groups across the capital to allow customers to access more tickets across price points in real time, and is seeing sales surge as a result.

    The online ticket seller is investing heavily in its APIs, allowing the various theatre groups in the capital to plug into the booking platform, drastically raising inventory. London Theatre Direct saw a quarterly rise in sales at API partner venues of more than 600 percent as a result.

    Previously, websites like London Theatre Direct and its rivals Encore and Ticketmaster would be allocated a set number of tickets per show, meaning demand generally outstripped the supply any one site could provide, with 30 percent of West End tickets typically going unsold.

    Now with API connectivity it can sell all available tickets across price points up to half an hour before the performance. The business is seeing customers generally up-selling themselves when given the choice, choosing pricier tickets than before.

    Read next: TIBCO CTO returns to its roots to win new business beyond traditional IT

    TIBCO's Mashery API management tool allows London Theatre Direct to monitor the various partners plugging into the central API.

    As London Theatre Direct CEO Francis Hellyer describes it, Mashery is like "adding rocket fire underneath our existing API, adding additional security, scalability, speed and resilience."

    "We wanted to ensure easy onboarding of clients, relevant and up to date documentation and a distributed architecture that would allow us to provide the best API solution possible," Hellyer explains.

    Read next: 9 tips for building, managing and running APIs within your business: Four Apigee customers highlight API strategy pitfalls

    Only one major theatre group, Ambassadors (ATG), is resistant to API connectivity. It appears that a perceived handing over of control and data concerns are the remaining barriers for the owners of major theatres like the Apollo Victoria, Duke of York'' s and Savoy.

    This appears to be something of an industry-wide problem, with Steve Hurn, senior vice president, EMEA, at TIBCO saying that those "resistant to change and new technology can perceive APIs as a loss of control."

    However, the results of London Theatre Direct's use of APIs should be a clear sign of their overriding benefit, with Hurn adding that "they do in fact drive integration, collaboration, and flexibility, resulting in greater opportunities with the ability to sell tickets at the last minute, which is the ultimate game changer."

    In an unusual public acknowledgment, Hellyer says he was interested in one of TIBCO's clients as much as the business' software. "The fact that the TIBCO Mashery platform’s existing client base includes a major airline that we want to work with was another factor," he says. "If theyd put faith in the Mashery solution, then that was good enough for us." 

    Hellyer wants to extend the business' reach by getting its theatre-booking APIs onto other travel and leisure brands' sites, to sell them as auxiliary products. One name at the top of his list is budget airline Ryanair and its 120 million yearly customers.

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    4 ways to integrate design and strategy

    As part of a recent video series with johnson banks, account director Katherine Heaton joined Michael Johnson to discuss how the studio's immersive creative process works, the role of strategy and how to keep plates spinning. In this article they share four key ways creative directors can integrate design and strategy.

    01. Don't rely on jargon

    “We’re in the business of communication, so why use complicated jargon when talking to people who are not familiar with the industry?” reasons Heaton.  

    Johnson adds that not-for-profit clients may not have archetypal Stanford MBAs. “They’re more straightforward, down to earth,” he says. “If we talk about things like ‘inherent brand positioning perception’ we’re met with blank faces.”

    02. Blur the lines

    Fluidity between the stages of the design process is key. It starts with research, through interviews, audits and workshops. Next comes strategy, including positioning and brand narrative.

    “Technically our design stage is third, but we often blur stages two and three,” says Johnson. “It’s an issue for many companies: how to go from where they are verbally, to visually how they’re going to look.”

    Heaton and Johnson are experienced with handling difficult rebrands

    03. Help the strategy bed in

    Stage four includes guidelines and implementation, and for bigger clients, this is followed by ‘embedding’– or as Heaton puts it, “communicating the new brand to staff within the organisation, and helping them figure out their launch plans.”  

    “We don’t just finish the manual and run away,” insists Johnson. “If a brand doesn’t percolate down, it’s not going to work. It’ll be one of those stuck-on brands that people often criticise.”

    04. Remember: tough is good

    “The politics of a rebrand are far more complicated than straightforward new brand projects,” admits Heaton. “We have lots of experience dealing with the politics now, which is why many clients come to us.”

    “People say: ‘that project must have been difficult,’ and if we say, ‘Yes it was,’ they say: ‘Good! You’ll be able to do ours.’ That happens again and again. You’d be amazed how many clients need to know you can handle the personalities in the boardroom.”

    This article was originally published in Computer Arts magazine issue 258. Buy it here.

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