I didn’t publish it. I intended to on the Monday before the vote, but after the assassination of Jo Cox a few days before, I felt writing anything seemed pointless. Furthermore, I had the nagging feeling that no matter how many people read it, I wouldn’t change a single mind.

Leave’s surprise win on Thursday night has confirmed that suspicion.

The initial signs from the fallout are not good — global stock markets crashed on Friday, and the pound devalued to such a degree that France is now the fifth largest economy in the world instead of the UK. Tremendous uncertainty now hangs over us — who the next Prime Minister will be, if the Leader of the Opposition will survive, whether we will have a snap election, what happens to Scotland (and Gibraltar), when negotiations to leave the EU will begin, and what the UK’s eventual relation with the EU will be.

There’s simply no plan and nobody has a clue — the referendum result is a disaster in itself, let alone the further pain we will suffer if and when the UK actually leaves the EU. Every single economic analysis before the referendum warned of a recession (and thus reduced tax revenues, and yet more austerity), and now we’re living through the opening days of their stark predictions.

And yet 17.4 million people willingly voted for this to happen.

Was it an ethical compromise — that the economic pain for a few years was a price worth paying for? That the “freedom” from the European Union was worth any price, even a few years’ economic uncertainty and misery, and we shouldn’t let it spoil Leavers’ celebrations?

The looks on the faces of the “winners” says otherwise: neither Gove nor Johnson have been seen out celebrating this weekend. Voters interviewed just a day after air doubts about their decision. The Sunday Times (which endorsed Leave) has “What has he done?” on its front page. Daily Mail commenters are now furious no-one told them of the financial risks.

Except of course, they were told. Repeatedly, and insistently, the Remain camp warned of economic uncertainty if not chaos. It didn’t matter. Leave voters simply ignored them: 69% thought there would be little economic impact.

Why did they ignore those concerns? Did that many people really think Europe was holding the country back so much, they were willing to sacrifice economic well-being for it? To be sure, a minority of people make leaving the EU their life’s cause, but at the general election last year Europe ranked just 9th in voters’ concerns (the economy was 2nd). It doesn’t lend itself to a natural majority — and at the start of the campaign, opinion polls showed Remain had a lead in the double digits.

And then that lead got eaten up. Why?

Will Davies’s piece on the sociology of Brexit is a very good read on the underlying historical factors that stretch back decades. Thatcher’s policy gutted out the industrial North, and New Labour’s solutions — tax credits, shuffling public sector jobs, instead of proper redistribution and investment— merely alleviated the symptoms not the causes. Alienated and relying on the largesse of London, decades of resentment have built up; and to make things worse, the crash of 2008 and resulting austerity gutted public services. With local economies stagnant, government services cut to the bone, and your best opportunities zero-hour contracts and Workfare, what’s your reaction going to be when Westminster politicians say Britain is “stronger” and “set to grow faster” than anywhere else?

The Leave campaign looked at the grievances of undecided or wavering voters and made Europe the focus of all of them. Cuts in the NHS or education bothering you? That’s because the EU costs £350m a week. Wages low, or jobs scarce? Not the fault of uncaring employers or sluggish demand, but because the immigrants keep taking them. A nagging sense things aren’t the way you want? That’s because Europe has control over every aspect of your lives.

This campaign was a stroke of malevolent genius — it capitalised on legitimate feelings of discontent and anger, and made Europe a convenient proxy to take the fall for all of them. It didn’t matter if it was true or not — of course it wasn’t, it was actually a pack of lies and exaggerations.

Never mind Trump being the master of post-truth politics, we have it here and we do it better than he does.

You can’t just blame the Leave campaign for lying. Ashcroft’s exit polling states 54% of Leave voters didn’t think Remain would win, that many saw it as a protest vote. Maybe that’s a hangover from the two-party system and first-past-the-post, perhaps, or maybe simple (and understandable) cynicism that voting never gets anything done for you.

The electorate were also more than willing to take those lies uncritically— “British public wrong about nearly everything, survey shows”, goes theheadline not from the Daily Mash, but the Independent. And FT research backs that up — while there are correlations between voting Leave and low income, as well as age, the strongest correlation is level of education.

Who was holding them to account? A predominantly right-wing, Eurosceptic press cheered, which on the Leave campaign to victory: 49.6% of national press circulation was from pro-Leave papers, while only 32.6% was pro-Remain. As a side note, it’s only one data point, but it’s worth noting that despite scoring highly on a set of Leave indicators such as post-industrial neglect, low income and education level, Liverpool came out for Remain. Liverpudlians, as it happens, also boycott The Sun.

(As for the BBC, the less said the better. The BBC’s coverage at times resembled its cravenly awful coverage of climate change — always seeking a “balance” of views rather than the truth)

Finally, the setup of the referendum gave Leave cause to run riot. Unlike the Scottish independence referendum, there was no obligation for Leave to outline a plan or costings for a Brexit. Unlike commercial advertising, there’s no penalty for lying in political advertising. And unlike a Parliamentary election, there’s no way of booting the winner out if it turns out they have lied.

And with only a simple 50% + 1 needed (not a supermajority, nor even a majority required in all the constituent countries), all that you needed to do was push the population over the edge for a couple of weeks before your campaign runs out of steam, and suffer no consequences if you turned out to be wrong, or lying, or both. Leave combined all of these vulnerabilities and used them to carry out a devilishly clever hack of our political system.

So, Europe was a totem to nail your discontent to. People thought their vote wouldn’t count. Many had a poor understanding of the facts, and a Eurosceptic press dominated discussion. And the Leave campaign were under no obligation to tell the truth, nor be held to their actions after the vote. These combined to make a perfect storm for a disastrous decision to be made — squeaking home by a 3.8% majority, and that mandate cannot be reversed.

We’ve uncorked the genie of post-truth politics out of the bottle. So what next? An angry electorate has got what it wanted, except it didn’t really know what it wanted. The actual problems on their mind — the NHS, the economy, jobs, housing — still weigh heavily, and leaving the EU is not going to solve them.

And that anger will now find other outlets. It’s already started — there’ve been numerous reports in the wake of victory, of harassment of migrants and minorities in the street, threatening notes through doors and racist graffiti on buildings. To be clear, only a minority of Leave voters are racist, but every racist is a Leave voter, and this result has emboldened them and made them more confident. They think they’re in the ascendancy now, and shamefully, their allies in the Leave camp are doing nothing to rein them in.

Where else is that anger going to go? Because angry Leave voters are only going to get angrier when they realise the promises of the Leave side were lies worth nothing. They’re already walking those lies back already. Nigel Farage has already poured cold water on spending the mythical £350m per week saved on the NHS. Daniel Hannan has said there won’t be strict controls on immigration. Of course they can do this, because they’ve won their battle but are free of any responsibility of the consequences.

What’s going to happen when these underlying problems are still not fixed and the people who are rightfully angry realise that they’ve been taken for mugs by the political class — ones wearing purple rosettes rather than red or blue—again? What option do they have when even the protest party turns out to be even worse than the others? Where will they direct their anger to next? If I were a politician I’d be worrying about that far more than the internal squabbles in my own party in the coming days.

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Jeremy Corbyn’s election as Labour leader is, we’re told, going to be a disaster for Labour. The party will fall apart. He is unappealing to swing voters and focus groups. He will not win the general election in 2020. 

This narrative is underpinned by the philosophy that the Labour party achieves more in power that out of it; therefore, the aim of the party should be achieving power. To achieve that power, if the electorate cannot be convinced to move leftward, then the party must move rightward. If certain principles have to be compromised or jettisoned, so be it, because it is more important to be in power than retain principles. That is the nature of pragmatic politics.

It sounds such a simple idea. Do X, and Y will follow. And it ties in with the status quo of managerialism in political thought. Governments, economies, whole systems, are treated as black boxes; just questions of inputs and outputs. Those participating in these systems are rational actors, motivated by incentives, whose behaviour can be predicted. Without pesky principles getting in the way, politics becomes a discussion of outcomes — which ones to achieve and the best way to achieve them.

Unfortunately for Labour’s believers in pragmatic politics, they are completely and utterly wrong.

There are no black boxes. Politics and economics are not simple systems where known inputs lead to predictable outcomes. They are complex, subject to major disruptions from minor inputs, and unpredictable. Most of the major era-shaping events of this century so far — the September 11th attacks, the Great Financial Crisis, the Arab Spring — were, at the time they happened, spontaneous and unpredictable. They’re Black Swan events, if you know your popular science books.

(Although this hasn’t prevented lots of self-proclaimed clever people saying they were predictable, in hindsight. Ignore them.)

There’s no better example of this than the rise of Corbyn himself. During the general election, he was such a peripheral figure he was mentioned just once in media coverage of Labour’s campaign. When he entered the leadership race, the very same people telling us he will be a disaster, were telling us he hadn’t a hope in hell of winning it.

And for all the talk of £3 entryism, that the Labour party had been infiltrated by outsiders, it’s worth noting that Corbyn still won 49.6% of the first round among party supporters, and 51.5% among party and union affiliates combined. He would have won easily without the new joiners — Labour members were already unhappy.

If you’re that bad at reading the mood of your own party members, the people you are closest to, then how bad must you be at predicting how an entire country or economy or global system will behave?

We need to cure ourselves of the delusion of pragmatic politics, and of all the philosophical baggage that comes with it. Perfect knowledge is not attainable. Black boxes are a poor theoretical model for political systems. People are not rational actors and aggregate behaviours are not predictable. Doing X will not automatically lead to Y, even if doing X led to Y in the past.

What does that alternative look like? An inbuilt assumption that systems are unpredictable, building things that are more accommodating of risk and unknowns, have more humility when you make your own assertions and be open to the possibility you may be disastrously wrong. That’s a start, at least.

Note that these are all things that are relevant to you regardless of where your political principles lie. As for those principles? Think of them of as the chart to navigate unpredictability by; to give you the grounding to deal with unpredictability as it hits you in the face.

(But don’t let those principles blind you to hard truths, else they become dogma, and dogma is useless)

In short, ignore the pundits’ predictions. Pundits are useless at predicting things, because everybody is useless at predicting things. Many (but not all) things coming up between now and 2020 will be unpredictable, and you owe it yourself to ignore those who are so certain about everything, and to be less stridently certain with your own predictions.

The post Why pragmatic politics is wrong appeared first on qwghlm.co.uk.

Also this week, Amazon have been in the news with a slew of articles and news reports on the working conditions of employees (particularly agency and temp workers, with it being Christmas and all) at one of Amazon’s distibution centres. The investigation is a good one, worth reading and highlights some of the problems (the lack of union representation being for me the biggest one). However, there is nothing uniquely evil about Amazon; they are not the first to exploit workers, and (although this doesn’t excuse their behaviour in any way) it’s certainly not comparable to the recent rise of slavery practices such as unpaid internships and Workfare.

Still, you see Tweets like this, and there is a point to them:

Sod the video of a fictional robot. I want the future in which Amazon pays tax and treats its workers well.— Phil Gyford (@philgyford) December 2, 2013

But I think the former story will end up being a more representative example of how labour relations are defined in the 21st Century than the latter.

Even if Amazon’s putative drones never make it, self-driving vehicles of some form will. Indeed, they already are a reality. Most people think they’ll revolutionise the car industry; I think they’ll undermine the delivery industry first. Fully automated, never fatiguing, possibly electric off cheap solar (if we ever get enough recharge points), and lightweight (what with no drive or passengers to harm in the event of a collision). Think of Adrian Hon’s deliverbots, and that might be what the future is like.

Self-driving takes a mundane but information-heavy task (you’ve got to pay attention to the road) and automates it. All the foundations are there to make this a reality – open-source embedded systems, cheap & fast networking, over-the-air connectivity and GPS; software able to handle voice recognition and visual recognition are no longer perpetually “a few years away” but are here now. This stuff is now so pervasive it will be quite difficult to uninvent.

This revolution in technology won’t just give us automated vehicles, moving goods in and out of warehouse, but inside, the staff will be replaced by robots themselves, picking products via automatic recognition and moving them about the place. It’s not just “blue collar” jobs – bots now write newspaper articles and trade stocks for us. Stephen Wolfram’s work teaching computers how to understand natural language could revolutionise how we program and the range of tasks computers could do in the future.

The 21st century threatens to automate mundane, service-oriented, information-heavy tasks in the same way the 20th century automated mundane, manufacturing-oriented labour-heavy tasks. That move from industrial to post-industrial wreaked havoc and left deep economic scars upon this country and others; the Left didn’t see it coming for too long, and when it did, much of it crossed to the other side, only for us to end up with even greater inequality and economic meltdown.

As we move from post-industrial to post-post-industrial (hey, it’s my blog, I’ll coin whatever neologisms I like), what will the Left do to avoid repeating the same mistakes? Millions of jobs will likely go, and millions of new jobs will likely replace them. Or maybe not – if everything gets automated it does raise the question: what anybody will actually do all day long? Should we even think about work as being normal, or such a defining part of our lives, any more? Maybe we’re close to Marx & Keynes’s vision of a leisured society empowered by automation than we think? Or maybe instead, having trained a generation to work in an information and service economy we’re about to wipe out any opportunities for them and let automation take over, leaving all but a tiny minority to fight over the scraps of Workfare and zero-hour contracts in a vastly unequal society?

The economic damage done to the move from an industrial Britain (particularly in the North) makes a mockery of neoclassical notions that labour markets are flexible and self-correcting; left to “market forces” the same structural damage will occur in the forthcoming upheaval. Can the Left get its head around the implications of information automation and a world where computers get as good at analogue as we do? The closest anyone has come to confronting the convergence of digital and analogue is the artistic movement known as the New Aesthetic, but the New Aesthetic maintains a deliberately detached facade (surveilling the surveillers, as it were) that avoids getting directly involved politics. Politics needs to provide more

To sum up, this is not a “Amazon workers, deal with it, you’ll be replaced with robots soon enough” post. What it is to remember, just as we look upon Amazon’s warehouse work using 20th Century labour relations as a framework, a revolution is happening that could redefine labour relations altogether for the 21st. The Left, if it is to avoid repeating the mistakes of the past, should be learning about the technological changes to come, grappling with their implications and actively shaping how society manages them, making sure our future is spent exploiting these advances rather than be exploited by them.

An aside – I’ve dealt with one pillar of how information automation will have an impact, our relation with capitalism & work. There are probably two other pillars, one being our relation with the state – military drones, pervasive surveillance, etc. – and the other our relation with each other – how will a society full of Google Glass wearers behave with each other? – that are also deserving of equal attention from the Left, but that can wait for another blog post.

The post Drones, Amazon & the future of labour relations appeared first on qwghlm.co.uk.

• If governments can do it, then so can agencies
• The GDS Design Principles for Agencies (Part 1 of 3)

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Five months ago I wrote a Twitter bot called @whensmybus. It took me a fortnight to code up and test the first version, which was pretty simple to begin with – it took a single bus number, and a geotag from a Tweet, and worked out when the next bus would be for you. And then people started using it, and really liking it. And because they liked it, they found ways of making it better (curse those users!). So I had to add in features like understanding English placenames, being able to specify a destination, handling direct messages, multiple bus routes, and tolerating the many many ways it’s been possible to break or confuse it, and this took up a lot of my time. And it was fun, to be honest.

At the same time, those bloody users also asked me when was I going to do a version for the Tube. But I was too busy adding the features for @whensmybus, and that’s one reason why it took me five months to write its counterpart, @whensmytube, which I launched last week. But there’s a stack of other reasons why it took so long. It didn’t seem too difficult to begin with. Just like with buses, Transport for London have made their Tube departure data open-source (via a system called TrackerNet), as well as the locations of all their stations. It would be pretty simple to do the same for tube data as it would for bus data, right?

Wrong.

So, for anyone interested in open data, software development, or just with a lay interest in why software doesn’t get new features quickly, here’s a run-down of why:

1. The Tube data isn’t complete

TfL helpfully provide details of all their Tube stations in a format called KML, from which it’s reasonably easy to extract the names and locations of every station. Well, they say “all”. That’s a bit of a lie. The file hasn’t been updated in a while; according to it, the East London Line is still part of the Tube network, and Heathrow Terminal 5 and Wood Lane stations don’t exist; neither do the stations on the new Woolwich Arsenal and Stratford International branches of the DLR. This has been griped about by other developers, but no update has been forthcoming. So it took time to do the ballache task of manually writing the data that hadn’t been included in the first place.

To make things more annoying, certain stations are left out of the TrackerNet system. If you want live updates from Chesham, Preston Road, or anywhere between Latimer Road and Goldhawk Road on the Hammersmith & City, you’re plain out of luck. Sorry, this is TfL’s fault and not mine. This also wasn’t documented anywhere, just omitted from the system documentation.

2. The Tube data isn’t built for passengers

To be fair to TfL, they do say what the TrackerNet service was meant for – it is built on their internal systems and was for non-critical monitoring of service by their staff, and there is a disclaimer saying this. The public version is useful, but unlike its bus counterpart there is a lot of data there which is not for public consumption. If anything, it’s too useful, as it contains irrelevant information such as:

• Trains that are out of service or “Specials”
• Trains that are parked in sidings
• Trains on National Rail systems, like Chiltern Railways, that run over Tube lines
• Data on whether a train is scheduled to go to a depot after its journey
• Some trains just don’t know what their final destination is yet, and are just labelled “Unknown”

And none of these special cases are documented in the system. So I had to spend a lot of time working out these odd edge cases and filtering out the chaff. And the code is by no means complete – I have to wait until irrelevant information is shown up to be able to filter it, because TfL don’t provide anywhere a list of possible values. This is annoying – so much so that I have even taken the step of submitting a Freedom of Information request to find out all the possible destinations a train can be given on the system to make sure, but I’m still waiting on it.

The documentation also falls down on being useful to reuse. For example, each station has a name (e.g. “King’s Cross St. Pancras”) and a code (e.g. “KXX”). Because spellings can vary, it’s easier to use the three-letter code when doing lookups for consistency. But the list of codes, and the station names they correspond to, were locked in a bunch of tables in a write-protected PDF, so it was impossible for me to create a table of code-to-station-name lookup table. In the end, I’m glad that someone had done the hard work for me, rather than I having to manually type them out.

On top of that, the system uses terminology more suited to insiders. For example, most stations have platforms labelled Eastbound/Westbound or Northbound/Southbound, which is fine. But the Circle Line and the Central Line’s Hainault Loop have designations “Inner Rail” and “Outer Rail”. And then to make my life even worse, some edge cases like White City and Edgware Road have platforms that take trains in both directions. This is confusing as hell, and so I had to spend a bit of time dealing with these cases and converting them to more familiar terms, or degrading gracefully.

This is a pain, but worth it. As far as I’m aware, no other Tube live data app (including TfL’s website, or the otherwise excellent iPhone app by Malcolm Barclay, which I regard as the gold standard of useful transport apps) takes this amount of care in cleaning up the output presented to the user.

3. Humans are marvellous, ambiguous, inconsistent creatures

And then on top of that there’s the usual complications of ambiguity. There are 40,000 bus stops in London, and typically you search for one by the surrounding area or the road it’s on, because you don’t know its exact name, and the app can look up roughly where you are, and give an approximate answer. But, there are fewer than 300 Tube stations, and so you’re more likely to know the name of the exact one you want. But, there are variations in spelling and usage. Typically, a user is more likely to ask for “Kings Cross” than the full name “King’s Cross St. Pancras” – punctuation and all. This all needs dealing with gracefully and without fuss.

4. Despite all my work, it’s still in beta

There’s plenty @whensmytube doesn’t yet do. It only accepts requests “from” a station and doesn’t yet accept filtering by destination “to”. This is because, unlike bus routes, most tube lines are not linear (and some even have loops). Calculating this is tricky, and TfL don’t provide an open-source network graph of the Tube network (i.e. telling us which station connects to which), and I haven’t yet had the time to manually write one.

5. But I’m still glad I did it

Despite all my problems with wrangling TfL’s data, I’m still pleased with the resulting app. Not least because, hey, it shipped, and that’s to be proud of in its own right. But more because everything I learned from it has kept me keen, and it’s had some pleasant side effects. The refactoring of the code I had to do has made @whensmybus a better product, and all the learnings of how to deal with the Tube network meant I was able to code and release a sister product, @whensmyDLR, with only a few days’ extra coding. Not bad.

But, here’s some quick conclusions from wrangling with this beast for the past five months:

1. Open data is not the same as useful data If it’s badly-annotated, or incomplete, then an open data project is not as useful. Releasing an API to the public is a great thing, but please don’t just leave it at that; make sure the data is as clean as possible, and updates are made to it when needed.
2. Open documentation is as important as open data It’s great having that data, but unless there’s documentation in an open format on how that data should be interpreted & parsed, it’s a struggle. All the features should be documented and all possible data values provided.
3. Make your code as modular as possible If you’re having to deal with dirty or incomplete datasets, or undocumented features, break your code up into as a modular a form you can get away with. The string cleaning function or convenience data structure you wrote once will almost certainly need to be used again for something else down the line, and in any case they shouldn’t clutter your core code.
4. In the end, it’s worth it Or, ignore all my moaning. Yes, it can be a pain, and annoying to deal with cleaning up or even writing your own data to go along with it; but in the end, a cleanly-coded, working product you can look on with pride is its own reward.
5. Thank you TfL Despite all my bitching above, I’m still really grateful that TfL have opened their datasets, even if there are flaws in how it’s distributed and documented. Better something than nothing at all – so thank you guys, and please keep doing more. Thank you.

The post Why it took me five months to write @whensmytube appeared first on qwghlm.co.uk.

But people don’t just take buses in London. They also take the Tube. And so it only seems fair to build a sister service for @whensmybus for the subterranean-inclined. So, introducing… @whensmytube. It does the exact same thing – taking advantage of Twitter’s realtime and geolocation capabilities and mashing them up with TfL’s open APIs to give you live Tube departure times for nearly any station on the Underground. Just Tweet:

@whensmytube Central Line

with a GPS-enabled Tweet, or:

@whensmytube Central Line from Liverpool Street

with an ordinary Tweet. More information and a full description of its abilities and how to use it are available here. Please use it! And break it! It’s still in beta, and any feedback would be much appreciated, thank you.

But, hang on. That’s not all! There’s not just the Tube in London. There’s also my beloved Docklands Light Railway. And it would be cruel to leave it out. So have two for the price of one – if you’re a DLR lover, please try @whensmyDLR for size as well:

@whensmytube DLR

with a GPS-enabled Tweet, or:

@whensmytube DLR from Poplar

with an ordinary Tweet. Like its Tube and bus counterparts, it’s reasonably flexible, so please check out out the help page. And please give any feedback you can, thank you!

The post When’s My… Anything appeared first on qwghlm.co.uk.

In higher education, although universities such as Bournemouth are praised by employers for working closely with industry, other universities and colleges have been criticised by businesses for running a significant number of “dead-end” courses in computer science, with poor prospects of employment for those enrolled.

And from my own anecdotal experience, that’s correct. For one reason or another, I’ve been reviewing CVs and interviewing people at work for developer roles last couple of months, and some of them were awful. They tended to have degrees or other qualifications from mid- and lower-tier universities and colleges, but had trouble telling the difference between PHP and JavaScript code, or were unable to provide even stock answers to well-versed problems such as sorting.

(Feel free to call me out as a snob on this one; I read my Bachelor’s in Computer Science at Cambridge, one of the few universities in this country where the majority of the course is spent not coding)

Anecdotal though my own experience, and many of the quotes in the article are, the Guardian’s campaign is laudable and I back teaching kids code in schools. But there are two issues I have with the campaign – it’s not just teaching, and not just code that needs to be taught (or learned).

Firstly, “digital literacy” is as broad a term as “literacy” or “numeracy”, and there are a range of different issues at stake. Take this complaint in the above article:

Ian Wright, the chief engineer for vehicle dynamics with the Mercedes AMG Petronas Formula One team, said: “There’s definitely a shortage of the right people. What we’ve found is that somebody spot on in terms of the maths can’t do the software; if they’re spot on in terms of the software, they can’t do the maths.

versus:

Kim Blake, the events and education co-ordinator for Blitz Games Studios, said: “We do really struggle to recruit in some areas; the problem is often not the number of people applying, which can be quite high, but the quality of their work. We accept that it might take a while to find a really good Android programmer or motion graphics artist, as these are specialist roles which have emerged relatively recently – but this year it took us several months to recruit a front-end web developer. Surely those sorts of skills have been around for nearly a decade now?

versus:

In a highly critical report last month, school inspectors warned that too many information and communication technology (ICT) teachers had limited knowledge of key skills such as computer programming. In half of all secondary schools, the level many school leavers reach in ICT is so low they would not be able to go on to advanced study, Ofsted said.

Computer Science is not Programming, and Programming is not Web Development, and Web Development is not ICT. What we have is a whole spectrum of different demands and of different roles, all of which have technology in common but often little else; producing computer models for a Formula One team or CGI Studio is going to demand a PhD-level or near grasp of maths or physics, combined with knowledge of highly specialised programming. Developing a front-end for a website still demands a reasonable degree of intelligence, but also a wider knowledge of languages and coding, and a better appreciation of more subjective issues such as usability, browser standards (or the lack of them) and aesthetics. Meanwhile, being adept with ICT doesn’t mean you have to be a genius or be an expert in code, but it needs to be more than how to make a PowerPoint presentation; how to use a computer properly and not just by rote, how to be confident in manipulating and understanding data, how to automate tedious tasks, how to creatively solve a problem.

Today technology is integrated to our lives to a quite frankly frightening degree. Should that mean everyone has to learn how to code? No. Should it mean everyone have an understanding of the basics, an appreciation of what computers can and can’t do, and the ability to use that knowledge to solve problems by themselves? Yes. But making everyone code is not the answer, and to me the Guardian is taking a bit of a “if it looks like a nail” approach to the problem of digital illiteracy.

That said, from my experience of the graduate CVs I read, the teaching of coding, as a practice, does need to improve. University courses should be better assessed and monitored and the “sausage factories” closed. Teaching how to code should be integrated into related subjects such as maths and physics wherever possible (and it’s worth noting many places do this well already). It shouldn’t just be coding that is taught, but how to define a problem, to break it down, and solve it. If anything, that’s more important – programming languages and technologies change all the time (e.g. how many Flash developers do you think will be about in five years’ time?) but the problems usually remain the same.

Secondly, there’s a spectrum of challenges, but there’s also a spectrum of solutions. It’s not just schools and universities that need to bear the burden. As I said, coding is a practice. There’s only so much that can be taught; an incredible amount of my knowledge comes from experience. Practical projects and exercises in school or university are essential, but from my experience, none of that can beat having to do it for real. Whether it’s for a living, or in your spare time (coding your own site, or taking part in an Open Source project), the moment your code is being used in the real world and real people are bitching about it or praising it, you get a better appreciation of what the task involves.

So it’s not just universities and schools that need to improve their schooling if we want to produce better coders. Employers should take a more open-minded approach to training staff to code – those that are keen and capable – even if it’s not part of their core competence. Technology providers should make it easier to code on their computers and operating systems out-of-the-box. Geeks need to be more open-minded and accommodating to interested beginners, and to build more approachable tools like Codecademy. Culturally, we need to be treat coding less like some dark art or the preserve of a select few.

On that last point, the Guardian is to be applauded for barrier-breaking, for making the topic a little less mysterious and for engaging with it in a way I’ve seen precious little of from any other media outlet. And the page on how to teach code is a great start – it should really be called how to learn code, because it’s a collection of really useful resources. For what it’s worth, I wrote a blog post nearly three years ago on things on things to get started on – though if I wrote it today I would probably drop the tip on regular expressions (what was I thinking?).

If I had one last thing to add, is that all of the Guardian’s campaign, and the support from Government, is framed around coding for work. Which is important – we are in the economic doldrums and the UK cannot afford to fall behind other nations. But, at the same time, the first code a beginner writes is going to be crap, and not very useful. Even when they get to a moderately competent level, it won’t be very useful beyond the unique task it was built for. Making really good code that is reusable and resilient is bloody hard work, and it would be off-putting to make the beginner judge themselves against that standard.

We need to talk a lot more about why we code as well as how we code. I don’t code for coding’s sake, or just because I can make a living out of it. I code because it’s fun solving problems, it’s fun making broken things work, it’s fun creating new things. Take the fun out of it, making it merely a “transferrable skill” for economic advantage, will suck the joy out of it just like management-speak sucks the joy out of writing. It doesn’t have to be like that. Emphasise on the fun, emphasise the joy of making the infernal machine do something you didn’t think it was possible to do, encourage the “Isn’t that cool?” or “Doesn’t that make life easier?”. Get the fun bit right first, and the useful bit will follow right after.

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Bugfixes are all very well, but… by and far away the most requested feature was to allow people to get bus times without needing a GPS fix, to allow use on Twitter via the web, desktop app or not-so-smartphone. And although using GPS is easier, and cool and proof-of-concepty, it’s plain to see that making access to the app as wide as possible is what makes it really useful. So, from now on you can check the time of a London bus by specifying the location name in the Tweet, such as:

@whensmybus 55 from Clerkenwell

This will try and find the nearest bus stop in Clerkenwell for your bus – in this case, the stops on Clerkenwell Road, which are probably what you’d want). The more precise the location given, the better; place names are OK, street names are better. It works great on postcodes and TfL’s SMS bus stop codes as well.

The geocoding that makes this possible is thanks to the Yahoo! PlaceFinder API, so my thanks goes to them for making a service free for low-volume use. (Aside: you may ask why not use Google Maps? Because Google Maps’s API terms only allow it to be used to generate a map, not for other geo applications like this).

So, play away, and let me know what you think. Of course, it may not always work – geocoding is tricky and not foolproof; if it doesn’t, please let me know in the comments here, or just ping me at @qwghlm on Twitter.

More information and FAQs can be found on the about page, and the technically-minded of you might want to check out the code on github.

The post @whensmybus gets a whole lot better appeared first on qwghlm.co.uk.

But, it’s a bit fiddly. The main website doesn’t automatically redirect you to the mobile version if you are on a phone. If you type in a location, (e.g. my local Tube station, “Limehouse Station”), you have to pick a match for the location first (from two identically-named options), then a second screen asking you to find a bus stop, and then you get the relevant times. On a phone, it’s just feels fiddly and frustrating especially when I know my phone has GPS in it and knows my location anyway.

Update/correction There is, as it turns out, the ability to find by geolocation on the mobile site, it’s just on a mobile browser I just get the main website and don’t get redirected to the special mobile site, which means I never knew about it (thanks to Ade in the comments for pointing this out).

If only there was a mobile-friendly, geolocation aware, real-time way of fetching information. Oh wait. There is. It’s called Twitter. Twitter has geolocation allowed on Tweets (if you opt in) and an API to fetch and send messages, so we have a system set up already in place for our needs.

I owe a big debt of gratitude to Adrian Short, who wrote a Ruby script to pull bus times from TfL. TfL have not officially released an API for Countdown just yet, but Adrian found it, and it’s there and accessible – providing the data in JSON format for each stop. That use got me thinking – if that data is available and can be parsed quickly and easily, why not make a Twitter bot for it?

With that, @whensmybus was born, and is now in beta. Try it out now if you like. Make sure your Tweet has geolocation turned on (for which you’ll need a GPS-capable smartphone), and send a message like:

@whensmybus 135

Or whatever bus you are looking for. Within 60 seconds, you’ll get a Tweet back with the times of the next buses for that route, in each direction, from the stops closest to your location.

Why each direction? Specifying a direction is fiddly and ambiguous; bus routes wind and twist, and some of them are even circular, so “northbound” and “southbound” are not easy things to parse. The name of your destination can have ambiguous spellings, and I haven’t yet got round to tying it in with a geocoding service like Google Maps. So, at the moment the bot simply tells you buses in both directions from the stops nearest to you. I might change this in future, once I’ve got my head around geolocation services and fuzzy string matching and all that.

It’s still beta (thanks to an early unveiling by Sian ;) ) and I plan in future to add enhancements such as the ability to use without GPS. I also need to write some proper documentation for it, and stick the source code on Github later tonight once I am home. The source code is now available on github, but do bear in mind the codebase is a bit unstable right now. So, if you are a Londoner, please do use it and tell me what you think, either on the comments below or on Twitter. @ me, don’t @ the bot – it will think it’s a request for a bus service and get confused. :) All suggestions are welcome.

(And now, some tech stuff for the more interested)

The bot is a Python script, run every minute via a cronjob. It’s quite short – 350 lines including comments for the main bit. As well as the live data API, the service also uses two databases officially provided by TfL’s syndication service for free; one is of all the routes, and one for all the bus stop locations. I converted these from CSV format to sqlite so the bot can make SQL queries on the data. TfL use OS Easting and Northing locations for the bus stops, so I have to convert the GPS longitude and latitude; I am indebted to Chris Veness and his lat/lng to OS conversion script, which I translated from JavaScript to Python; I am also now much more educated on subtleties like the difference between OSGB36 and WGS84. Finally, I use the Tweepy library to receive and send the Tweets, which is really rather excellent and saves a lot of faff. Finally, the whole project would not be possible without the ideals of open data and open source software behind it, so if you’ve written even a single line of free software, then thank you as well.

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Although this was not solely due to what came out of the latest Facebook f8* conference, it probably was some sort of straw that broke a proverbial camel’s back. At f8, Mark Zuckerberg announced the Facebook Timeline, a way of not just showing what you are up to right now, but your whole life as Facebook saw it, digitised and shown to all. And my reaction was along the lines of:

Fucking hell, I’m going to be spending the rest of my life tagging photographs of myself

I joined Facebook early in 2007 when they let ordinary civilians in, and at first I quite liked it. It was a cute way of tying in and aggregating one’s content, thoughts and photos, and keeping up with people I knew, or used to know. What a nice service. And for free! But over time, the fun faded. Facebook kept on quietly changing privacy settings and made a landgrab for copyright of uploaded photos (later rescinded).

So, I harrumphed, tightened my privacy (a tedious task), removed a lot of personal info and content (photos, imported blog posts) and despite my misgivings, carried on with a stripped-down profile to keep in touch with friends. But as Facebook matured, and my profile accrued information over time, another unwelcome feature came about.

The practice of “Friending” someone just because you met them at a party, or went to school ten years ago with them, or you work with them, seemed a good idea at the time; it’s nice, who doesn’t want more friends? Even if they are just Facebook friends. But these are people I do not see every day, for whatever reason; as sad as that may be, over time those social ties would normally fade. C’est la vie.

But Facebook ossifies these previously ephemeral social ties; they are there forever, reminding us of the past. Whereas before we would be able to let these ties fade passively, with them laid now we have to actively “unfriend” people we no longer associate with. That’s not very nice, is it – after all, isn’t the opposite of a friend an enemy? So out of politeness, we accumulate these ossified ties, even after we change jobs, cities, relationships, as a form of digital clutter.

This was as bad as it got, until now. While social ties lingered, other content on Facebook would gradually drop off your timeline and fade away. Indeed, as online archiving extraordinaire Jason Scott observed in an excoriating critique of Facebook:

So asking me about the archiving-ness or containering or long-term prospect of Facebook for anything, the answer is: none. None. Not a whit or a jot or a tiddle. It is like an ever-burning fire of our memories, gleefully growing as we toss endless amounts of information and self and knowledge into it, only to have it added to columns of advertiser-related facts we do not see and do not control and do not understand.

Be careful what you wish for. Now our Facebook profiles will have everything we ever have, dished up by default (and while Facebook’s UI has got easier to customise recently, I bet the default will still be everything). Now it’s impossible to escape your past. Everything you have ever done that has been digitally logged by you, or your friends, can now be potentially dished up as your very own digital This Is Your Life. There is, on Facebook, a photograph of me in my early twenties, passed out after drinking too much tequila on Mexican Independence Day (any excuse, my younger self would say). That’d be on my Timeline by default, no doubt.

But it’s not because of embarrassing photos that I’m off Facebook (far more cringeworthy ones exist, thankfully on analogue prints). It’s the sense that Facebook is very much about the past. The people you have known. The relationships you were in. The things you have done. And these hang around your neck and tie you down.

Whereas what’s really exciting about the web is the things you are going to do. The new fact you’re going to find out idly browsing Wikipedia. The amazing people you meet thanks to you sharing a joke on Twitter. The inspiring blog post you’ll find via Delicious. The silly lolcat you’ll find on Reddit. Facebook isn’t offering anything what makes the Internet fun, and it’s taken this change to make me realise.

With Timeline, we’re opening ourselves up with an ever-growing obsession with the past. A quote I saw last night was “We’re gonna need architectures for forgetting”. Poetic as that line is, that’s a cure when prevention might be better – for me, in any case.

I must stress that this is not to say Facebook is bad, or Timeline is going to be a failure. Plenty of people are happy to have ossified social ties – if you are in a small, close-knit social network that is relatively static, I can see it why is a boon. Timeline will be fantastic for you, if you have been on Facebook your entire adult life, and all that data is there and well-curated (which it will be, if you have been on Facebook your entire adult life). But it’s not for me; it’s not interesting to me as a user, any more. So I’m out. Bye, Facebook.^†

* Named for Fate, the all-knowing computer in V for Vendetta, right?
† Although I’m still keeping the Facebook Like button at the bottom, just for kicks and sheer hypocrisy ;)

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The episode started in the Republic of the Congo (indeed, with some material lifted & extended on from his piece It Felt Like A Kiss), and looked the near-unimaginable scale of slaughter in Congo/Zaire and neighbouring Rwanda, and the role of Western interference in the region: the Belgians’ attempts to install the Tutsis in Rwanda as political ruling class, the CIA’s anointing of Mobutu Sese Seko as leader of Zaire as a bulwark against communism, mining companies’ bloody landgrab for the mineral columbite-tantalite (used in the manufacture of chips in electronic devices such as the Playstation) in the modern Congo, and even the naturalist Dian Fossey‘s ongoing feud with Rwandans as she tried protect gorillas in the rainforest. Little to do with machines, loving or not.

The other story was more conventional Curtis fare: charting the lives of geneticists Bill Hamilton and George Price; Hamilton came up with a theory of gene-centric evolution, which Price took on further, formulating a model of altruism as a means of gene propagation. And why stop at altruism? Take it to its logical conclusion, and all manners of human behaviour can be described as evolutionary techniques and no more, and we end up being, er, gene-propogating machines. This is on much more familiar territory – the scientific establishment reducing humanity to a mere aggregation self-reproducing automata.

But unlike his usual form, Curtis didn’t attempt to draw causal attempts (the kind that usually infuriate) between the two stories. In fact, apart from Hamilton’s death in the Congo, there didn’t seem to be any link at all. Instead as the episode unfolded it focused more and more on the ongoing slaughter in central Africa, spurred on by the West’s demand for Africa’s mineral wealth. When Rwanda massacres happened in the 1990s, the developed world’s militaries stood by, while its NGOs (despite their good intentions) were powerless to stop the fighting spread to refugee camps. Curtis played a series of increasingly distressing images of atrocities with a backdrop of incongruent music.

And you begin to realise Adam Curtis isn’t even trying to make a connection, and this isn’t even a documentary. Curtis is provoking you into feeling uncomfortable, into dwelling on the loss of control, disillusionment even, with modern liberal Western society, using the history of West’s interaction with Africa – colonialism, decolonialism and the bloody end of mass capitalism – as emotional bait. Your grandparents’ generation subjugated them, your parents’ generation unleashed anarchy upon them, and now you’re fuelling the slaughter and chaos they created when you buy your Playstation. This is not a documentary designed to educate, but an art project designed to provoke – riffing off the aforementioned It Felt Like A Kiss rather than The Power of Nightmares.

And when you’re done feeling uncomfortable, Curtis gives the punchline to the film: this is why you feel so attached to bury yourself in the embrace of the machines, because deep down you no longer have faith in humanity to solve its own problems or its own inhumanity.

This is a leap of logic, a provocative one, a sign of desperation, even, but an intriguing change in style as well. Perhaps Curtis thought this the best way to make his point, perhaps he couldn’t think of any others. It’s certainly a departure from his usual form: of a triptych of tightly-wound, interconnected episodes exploring the concept. And to be honest – it didn’t work; it just made the piece look disjointed and the two storylines out of place with each other. It’s not his style – Curtis is not a polemicist – his flat, laconic commentary and his refusal to appear on camera make it impossible for him polemicise – and to use a tactic of deliberate provocation is as mechanistic a view of human beings as the very philosophy he is attacking.

And yet despite the flaws and non-sequiturs of the main story, I can’t find it easy to shake off the moral of the other tale in the episode: the demise of Price and Hamilton. The originators of the selfish gene theory were ultimately wracked by the implications of their own research: George Price’s fixation on biological determinism led to his descent into self-enforced poverty and Christian piety as a means of escaping it, and ultimately suicide when it offered him no salvation. Bill Hamilton swayed the other way, growing mistrustful of modern medicine as it was an obstruction to natural selection, leading to a belief HIV was a byproduct of vaccination programmes in the Congo, where he ended up dying. Beneath the provocation, Curtis’s underlying point, warning even, seems to be: this machinist view will drive you mad too, one day.

Coming up next: a review of episode two. Yes, I know that’s the wrong order. Consider it a homage to the man’s style…

The post ALL WATCHED OVER BY MACHINES OF LOVING GRACE, part 3: a review<br/><br/>Or… considering the documentary-maker as not really a documentary-maker appeared first on qwghlm.co.uk.

Four years on, we have his new series, ALL WATCHED OVER BY MACHINES OF LOVING GRACE, and the chance to see whether The Trap was an aberration from true form. Like its predecessor, Curtis delves into the technical not just the historical. His basic thesis (I’m summing up) is as follows: the selfish Objectivist philosophy of Ayn Rand inspired a generation of Silicon Valley geeks to create computer systems with the aim of removing the shackles of government to create a utopia of free individuals; these same system are then used by the creators of the New Economy (led by another Rand acolyte, Alan Greenspan) to create a new economic miracle controlled by the banks, Goldman Sachs and the Federal Reserve. But instead of creating a utopia they created chaos – the machines they had such faith in failed, and despite producing an economic crisis in Asia in 1997, we kept faith in them to create an even larger worldwide crisis a decade later, from which we can see no way out of.

The problem with this is that it’s seeing too many links where there aren’t any. Not every Silicon Valley company was inspired by Rand (Curtis named one or two examples at best, neither of who leading lights on the scene), and the area’s philosophy owes arguably more to the countercultural movement and political climate of California than Rand’s self-indulgent miserabilism. It’s certainly a long way away from the conservative, East Coast, market fundamentalist philosophy of Greenspan, Robert Rubin and indeed the entire neoconservative/Chicago School generation of politicians, economists and bankers who eventually assumed political control. Cyberlibertarianism envisions a future of individuals networked together, free of hierarchy or even the state; market fundamentalism celebrates harnessing the aggregate of individuals’ behaviour for greater prosperity and stability. In short, one coast’s philosophy created John Perry Barlow, the other Alan Greenspan.

Curtis’s other flaw is to confuse “machines” with what machines actually run. A computer is just a unit for processing numbers in any number of ways. They are just boxes, glorified calculators. It’s the software we run on them that makes them do “evil” and this software is made by human beings. Having spent so long talking about a generation brainwashed by Rand, Curtis now attributes all the evils to the machines. But who programmed them? Who first thought of using them for automated trading, just-in-time manufacturing, supply chain management and all the things that are now taken for granted in the New Economy? For a storyteller who loves to peel apart the unknown and the people behind history, Curtis instead frustratingly wastes his time on peripheral figures such as Ayn Rand (who died a recluse in 1982) and Bill Clinton (distracted by the Lewinsky affair and powerless to stop the SE Asia crisis), rather than the people who built and shaped the information economy.

The result is a mess, with Curtis making oversimplified and hurried connections between various subplots. But that doesn’t mean there isn’t a story to be told amongst this clutch of different tales. How did a bunch of so-called geeks and slackers, growing from the midst of the counterculture, create a multibillion dollar paragon of capitalism? How did the conservative, sleepy institutions of Wall Street become seduced by the wonders of technology and grow hypertrophically on computer models, automated trading and complex financial instruments? In short, how did Barlow and Greenspan’s generations become allies, intertwined and taking on each other’s aspects and practices? And finally, how have we become so dependent on these systems, making them become so ubiquitous and invisible, that we didn’t notice things were going badly wrong until it was too late?

If you think this sounds familiar, it’s because Curtis used this intertwined-dichotomy style of filmmaking so well with The Power of Nightmares: the story of how the ideological descendants of Leo Strauss and Sayyid Qutb ended up as putative enemies, yet neither could live without the other, and both were grounded in the same similar grievances with individualism and liberalism. It’s odd that Curtis was able to portray the balance of similarities and differences in that film, yet with AWOBMOLG he struggles to make sense of it all, and ends up merely telling the “what” rather than the “how”, giving us numerous red herrings in the process.

It’s easy (but patronising) to say that’s because “technology is hard” and it’s difficult to comprehend it and history together rather than history alone. But Curtis is not a stupid man. It’s perhaps more charitable to say it’s easy that when it comes to relatively-uncharted history of the information age, there is simple so much more information and so many possible narratives, it’s easier to see pattens where there are none than not. But, this was just part one, and maybe parts two and three are better, and a lot more coherent.

In the meantime let this not detract from Curtis’s earlier works – if you haven’t seen them, The Power of Nightmares and Century of the Self are both available from archive.org. His KABUL: CITY NUMBER ONE blog is a collection of blogging and archive clips about the Afghan capital, and well worth reading. And I retain a soft spot for It Felt Like A Kiss, an avant-garde experimental attempt at storytelling based on 20th century history commissioned by the Manchester International Festival. AWOBMOLG was disappointing but don’t let it put you off entirely.

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