Aaah – another site about The Future of Journalism.

A dull one.  Without the  invective and ideology about free vs. paid, pajama-clad bloggers vs. stick-in-the-mud mainstream media curmudgeons, and Utopian visions of crowdsourced news vs. dark fears about falling standards you can find elsewhere.  It has words like taxonomy and persistent content in it; discusses business models and revenue streams in dull, accountant-like language; and tries to dissect the sparkling prose journalists turn out into tiny bytes of data.

But there is a purpose here, and it’s based around the idea that we as journalists haven’t really thought about how people are changing they’re accessing information, or about how we need to fundamentally rethink the way we carry out journalism and the kinds of – for want of a better word – products we turn out for them.

There’s much hand-wringing over the loss of the traditional business model of news, it’s true.  Perhaps too much.  And this site will contribute its share.  But hopefully it’ll also explore some of the less-explored questions about where the profession goes in a digital age.   And lay out some of the thinking behind one concrete idea that might help move the business forward: Something I’m calling Structured Journalism.

So, welcome – and I hope you find this interesting.

Just a quick post to say there was a nice turnout at our session at ONA, with a great panel of Laura Amico, Bill Adair and Miguel Paz (with yours truly moderating after a short intro/powerpoint, which I’ll post if I can ever figure out how to do that.)

Chris Amico did much to live-tweet the discussion – as did many others – and you can see much of that here.

So how did it go? Pretty well, at least from our point of view.  Laura did great work to ensure a community of people already involved in doing various forms of structured journalism were in the room, among them David Cohn of Circa and Melissa Bell of Vox.  We heard from others working on projects, such as David Caswell of Structured Stories, who’s building an interesting platform/CMS for structuring narrative.  And many more.

Having all those people in a single room meant we could share experiences, talk about the ideas and obstacles, and generally riff on where we thought all this might go. As Laura noted (and Chris tweeted):

While the concept seems really simple, we’ve really lacked the words to talk about this.

So just convening everyone, and having a common vocabulary was a big step forward. And then there were good points that were raised – from the cultural challenges of getting reporters to focus less on the stories they’re crafting and more on the information they’re collecting, to the future problems of maintaining ever-growing databases, to the possibilities inherent in having better newsroom calendars that we could build structure off.

Another point that stuck to me: How committing to collect some types of information regularly can upturn some of the notions of mission and news judgment in newsrooms. News organizations typically focus on outliers

It’s hard to make predictions, especially about the future – attributed to various people

How fast is the world changing – and how fast are we adapting to it?

Executive Summary:  Faster than we think, and not fast enough.  At least those are my takeaways from The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, by Erik Brynjolfsson and Andrew McAfee. an interesting book that’s simultaneously uplifting, optimistic, terrifying and worrying.  And definitely worth a read.

I’m not sure that’s what Messrs Brynjolfsson and McAfee intended as the main takeways – and there’s certainly plenty else in there about the economics (and inequalities) of the machine age, the spread of robotics, data and algorithms into our lives, the likely policy implications, and all that sort of thing – but at least that’s how I read it.

Not that it’s necessarily bad news – in fact, one of the best frames they put on the new digital age that we’re in is around the notion that, just as the industrial age freed us from the constraints of animal and human muscle power, this revolution is set to augment the human brain in ways we can’t yet really understand.

As they point out, a whole slew of new capabilities have emerged in the last few years that were effectively dismissed as essentially impossible in the near term less than a decade ago – self-driving cars, effective voice recognition, human-like text generation, visual recognition systems, and so on.  Even machine translation services, which are in many ways laughably bad, are a minor miracle in that they even exist.

What’s driving all this?  Increasingly powerful computing, decreasingly expensive senors and processors that are proliferating in devices and objects, and the masses of data they’re generating every minute.  All that data isn’t necessarily useful – and certainly will be misused at some point – but it opens up lots of potential new capabilities.  But first we have to imagine them.

Look at Waze, for example, which took the ubiquitous location – and hence speed – data available on phones to build real-time traffic maps.  Before that, we had various mapping apps, that while useful, basically took what was static information and put them on mobile devices and added search and other capabilities.  Very useful, but much more an extension of existing systems.  It took the folks at Waze to reimagine what they could do with completely unrelated data.  So what other tricks are we missing?  (What if we used cellphone location data to help the blind navigate around other people in crowds?)

And, of course, I’m still plugging structured journalism.

Frederic Filloux, in a recent Monday Note, pointed to a host of potential news applications that could be built off the data in our mobile phones, going beyond simply the notions of shorter stories/small screen-friendly articles/quick updates that dominates a lot of the discussion of mobile apps.

Just a quick post to say I’ll be heading to Chicago at the end of September for the ONA conference, where Laura Amico, Bill Adair, Miguel Paz and I will be on a panel discussing structured journalism.

We’ll talk about Homicide Watch, Politifact, Poderopedia and Connected China, of course, but what we really want to do is discuss more broadly ways to embed the ideas of structured journalism into more newsrooms, the advantages and challenges that brings, and hopefully brainstorm other areas of coverage where this approach might be helpful.  We promise no long presentations – I’m spending loads of time cutting down a short intro –  lots of interaction, and we’re hoping we’ll have an involved and engaged audience bringing lots of ideas, questions and answers.

Please show up if you can – it’s on Saturday afternoon, September 27, 2.30 pm, in Chicago Ballroom IX.  (The hashtag is #structuredjourn.)

We’ve also set up – or more precisely, Chris Amico has set up (thanks, Chris!) – a Google group where we’re discussing structured journalism and related subjects.  Come join us there, too, and say hi.

Any sufficiently advanced technology is indistinguishable from magic – Arthur C. Clarke

It’s not often I can squeeze a picture of Tricia Helfer, a reference to Battlestar Galactica and a quote from science fiction author Arthur C. Clarke in a single post, but that really speaks to the power of not having an editor. And incoherence.

But there is an underlying theme here, and it’s this: Robots!

There’s even an underlying point, and it’s about what we think about when we think of robots, automation and how our world is changing – and how we might want to think about how we cover all that.

This is all apropos of a number of articles that have come out recently about robots and automation – from a Pew Report on AI, Robotics and the Future of Jobs, a handy (and smart) Quartz graphic about what jobs are likely to be automated, an Atlantic story about the original paper that the Quartz graphic was based on, and an Economist piece just before a book on the subject came out. They’re all interesting articles that focus largely around how the rise of smarter and more capable machines will affect employment – an important theme that certainly needs covering.

But the trouble with words like “robot,” or even “automation,” is that they make us think of discrete changes to our worlds – in other words, of new species come to live among us. Or, as the Pew report noted:

Depictions of robotics and artificial intelligence in popular culture often lean towards powerful anthropomorphic robots (Transformers, The Terminator) and hulking mainframes with human-like intelligence (HAL in 2001). But many of the experts who responded to this survey expect technology to evolve in the opposite direction, with machine intelligence being hidden deep in the complex workings of outwardly simple or even invisible devices and digital interactions.

In other words, we shouldn’t think about robots as the clunky Robby the Robot that you saw in Forbidden Planet, but more as the advanced “skin jobs” – as embodied by Ms. Helfer, above – that the Cylon machine race used to infiltrate human worlds in Battlestar Galactica (an aside: Best. Show. Ever. Stop reading now and binge watch all four seasons. I’ll wait.)

Or, to put it yet another way, the robots are already here.

Not here in terms of lumbering thousand-pound hunks of steel that cunningly hide themselves as cars, but as lines of code even more cunningly embedded in the whole range of daily devices, processes and appliances we use – part of our ordinary fabric of life, from the prices we’re quoted at Staples to augmented reality shopping apps to

Who should you trust? (Or, for all you pedants out there, whom should you trust?)

It’s an important question for all of us, not least when you’re buying a used car (and believe me, I know.)

But it’s probably even more important for journalists, who talk to strangers on a regular basis and need to make snap judgments about how much faith we should have in what they say.

So here’s the bad news: You shouldn’t trust yourself to figure out who you should trust.

At least that’s the case if I understand Blindspot: Hidden Biases of Good People, a very interesting book by social psychologists Mahzarin Banaji and Anthony Greenwald, correctly. Blindspot is a good book (although Mahzarin is an even better lecturer; she recently gave a great talk to a number of Thomson Reuters folks) that focuses on the biases and prejudices – “mindbugs,” she calls them – that we have, but that we don’t know we have.

Don’t believe me (or rather, her)? Check out the Harvard Implicit Association Test, which tracks, via the length of time it takes for you to run through a series of matching tests, how strongly you associate one group with a set of traits – for example, female names with domestic terms, as opposed to men and work issues, or white faces with Americaness vs. non-whites. Try the test(s):  They’re both scary and enlightening. And if you’re like me, you’ll take them a couple of times because you don’t like how the results turned out.

Alas, the results don’t change.  At least not very much, and not without a fair amount of intervention.

Which is another way of saying that we all have biases, many of which we’re unaware of, and that we act on them unconsciously.  That’s not to say we’re racist or sexist, or that we knowingly discriminate against groups we don’t like.  But it does mean

So what ails the internet, you ask?

Excellent question.

Luckily for you, Maciej Cegłowski and Ethan Zuckerman recently wrote two great pieces expounding on that very topic. Maciej’s text of a speech he gave at Beyond Tellerrand in Germany offers a broad survey of the built-in problems of the digital world; Ethan’s article focuses on the impact of making advertising the default business model of the internet.

Both pieces are smart, funny, depressing, insightful and well worth reading. You’ll laugh, you’ll cry.  Or you should.

But beyond encouraging you to slit your wrists while smiling, they’re also great reminders of the importance of taking a breather from chasing the latest trend – mobile! internet of things! social! big data! – to step back and survey how the basic architecture of the web, from the way it’s built to how it’s regulated to where its funding comes from, affects our lives, our industry and our journalism. It’s also a great reminder of how relatively new, unformed and plastic the landscape is; and how every time it evolves – which is to say, pretty much every year – the ground potentially shifts again.

The clearest example is in how the media business responded to the chase for advertising dollars, a consequence of what Ethan calls “the original sin of the web.”

Through successive rounds of innovation and investor storytime, we’ve trained Internet users to expect that everything they say and do online will be aggregated into profiles (which they cannot review, challenge, or change) that shape both what ads and what content they see.

(We’ll get to “investor storytime” in a sec.)

It’s true that we’ve all bought into a notion of data profiling as the price of a myriad of online services, and Ethan is right to focus his outrage and attention on that, but I’m just as unhappy about what it’s done to journalism, as Ethan also notes:

Second, not only does advertising lead to surveillance through the “investor storytime” mechanism, it creates incentives to produce and share content that generates pageviews and mouse clicks, but little thoughtful engagement.

And it’s true:  Much of the way ads are structured online encourages the disaggregation of content into pageview-friendly chunks.  There’s much less incentive to create more engaging and immersive experiences – beyond their ability, of course, to generate more clicks and pageviews.  It’s not a world particularly friendly to a Connected China or Theyrule, for example.

Not that they – and other structured journalism-type sites such as Politifact and Homicide Watch – couldn’t exist in an ad-driven world. 

If you can’t say something nice, don’t say nothing at all – Thumper, in Bambi (1942)

So I’m definitely misusing Thumper‘s aw-shucks-adorably-cute line from Bambi, but that’s one of the takeaways I took away from a recent post at Poynter about the survival of sports match reports, even in a world where major games are available online and results can be found everywhere.

The post, by Roy Peter Clark, makes the case that there’s still room for great match reports when they bring more to the table than just who-won-and-how, and points to a great piece by the Washington Post’s Steven Goff on Brazil’s humilating 7-1 defeat by Germany in the World Cup semi-final – a game watched live by millions, and probably tens if not hundreds of millions. (Even me, for all of 10 minutes.  But there were four goals in that time.)  It starts:

BELO HORIZONTE, Brazil — It’s been said Brazil has never fully recovered from its greatest sporting tragedy, the 1950 home loss to Uruguay in the World Cup final. Despite proceeding to win a record five global crowns and injecting beauty into the beautiful game, for blessing the sport with legendary players such as Pele, Romario and Ronaldo, Brazil remains haunted by the ghosts of “Maracanazo” — a term capturing the heartbreak of that day before 173,000 spectators at Rio’s Maracana stadium.

After what unfolded Tuesday, a 7-1 loss to Germany in the Cup semifinals, Brazil will have to coin a new idiom to pass through the generations, an expression to capture what it looked and felt like at Estadio Mineirao, what it meant to concede four goals in six minutes of the first half, to suffer one of the most humbling setbacks in World Cup annals, to lose at home for the first time in 12 years and to equal the largest margin of defeat in its eminent history.

There’s a lot more sociology than sport in that piece, and that makes sense.  If you’re going to have to write a second-day story about an event most people have already seen, you need to bring something else to the table than just-the-facts.  Not just because lots of people might have already watched the game, but because even for those who haven’t, machines will likely do as good a job of covering the basics, and will do it faster and cheaper than humans can.

Chicago-based Narrative Science started out

Ken Doctor, as always, has a smart post about the renewed focus on “explanatory journalism” with the rise of such sites/verticals as Vox, the Upshot, Storyline and FiveThirtyEight, and asking a critical question:  What’s the bottom line?

If, in fact, in a world awash in Who/What/When/Where, readers value the connecting of dots, they’re more likely to pay for it — and to pay more for it.

Is that true?  Ken makes a strong case for the higher value of Why over Who/What/When/Where, and it’s certainly true that the world is flooded with commoditized “news” – what-just-happened stories – that drive their value and price down.  And so the relative value of contextual, explanatory news makes lots of sense to me; and what I’d argue is that we can and should do more to turn out more Why? content more regularly and more efficiently to really drive value.

But to do that we’ll need both to focus much more and – you guessed it – structure our content more.

First, back to Ken’s post, which lays out the case for explanatory journalism clearly and succinctly.  As he notes, it isn’t something new or something confined to the FiveThiryEights of this world, but a core part of daily journalism at the best news organizations in the world.

The Wall Street Journal, the FT,  The Economist, and The New Yorker are just a few of the news outfits that have long based their products on making the world a little more understandable for their readers. More recently, sites as far-flung as Quartz and the Netherlands’ De Correspondent have joined that group. What they have in common: the ability to price up for readers, or charge premium rates to advertisers, or both. Might they be on to something?

But that kind of great journalism is expensive – not to mention inherently inefficient – and as revenues at news organizations have suffered and news cycles have shortened, there’s been a temptation in many newsrooms to get on the “hamster wheel” of content generation – focusing on giving readers more and faster in an effort to keep up with competitors and drive page views.

To be sure, there’s also been a trend back to deeper investigative reporting in some newsrooms, based on the theory that it’s precisely that kind of differentiated content that will bring more dedicated and loyal readers/subscribers – an argument very similar to the one Ken makes.

The main issue – and Ken flags it well when he discusses the challenges local papers face in trying to follow this model – is that good content, whether investigative or explanatory, is more expensive and slower to produce.  Even if it does generate more revenue, will it cover its higher costs?

Just a quick post to riff off a piece at Poynter today about the potential value embedded in news organizations’ archives – and how little of it is being tapped.

And more importantly (at least for me), a chance to reiterate that we can and should go far beyond just surfacing our timeless prose to rethinking how and what we write in the first place.

The Poynter piece, which draws on a post by media data analytics company Parse.ly, notes that for most publishers surveyed, less than 10 percent of traffic came from stories more than three days old. That’s not surprising, given how little is done to promote older content, but as the Parse.ly post notes:

Integrating evergreen posts into your distribution strategies can attract and grow readership without having to increase editorial costs.

And it’s certainly true that one of the goals of structured journalism is to extend the shelf-life of journalists’ work, in effect amortizing the costs of all that effort over time and page views.  But that should involve more than simply writing evergreen posts that will continue to be relevant for weeks; and it’s certainly also more than working up ways to flag old content to new audiences.

Sam Kirkland, who wrote the Poynter piece, focuses on the issues around pushing old stories, noting that:

My instincts say it’s weird to dig up old content without a specific reason, but it’s worth asking if our hyper-sensitivity to timeliness can get in the way of serving readers who might not care as much about news hooks or newness as we do.

Which really points the finger at where the issue is: Our hyper-sensitivity to, well, what we do, and less to what our readers might want. Sure, we care hugely about news – and it is the name of the business we’re in, although perhaps it shouldn’t be – but there are many more reader needs than are captured by a focus on what-happened-this-minute.  More importantly, by focusing on what we do (write stories) than on what readers/users want (information, context, insight – and news), we’re missing an opportunity to create stories and information the first time around that have extended shelf lives, whether as individual stories or as elements of information that can be recombined into new stories.

That’s how Politifact, Homicide Watch and Connected China were built, and it’s a structure that allows them to keep building new content on top of older content, often creating it in response to a query by a reader rather than as a one-size-fits-many story. And that, in turn, means they can lower the long-term cost of creating while letting users find more useful information when they want it.

That’s the real potential value embedded in older content for news organizations, and we need to find more ways to free it.

“Robot” journalists can’t compete with humans at the things humans do best – Slate Magazine

Slate had an interesting piece the other day about “robot” journalism, doubtless prompted by the AP’s recent announcement that it would be turning to software from Automated Insights to produce thousands of corporate earnings stories. (Business news organizations like Reuters, Forbes, and probably Bloomberg have been automating stories as well, but this underscores how mainstream the technology and practice is becoming.)

The Slate piece was a smart look at the advantages and disadvantages that humans and machines bring to the exercise of producing stories, and it summarizes the state of play well.  Machines are faster, more reliable, better at crunching reams of data, and all that.  Humans are better at bringing in broader context, understanding what might be interesting to other humans, and so on.  Machines are critically handicapped by the quality of the data available to them.  Machines are cheaper than humans.  All of which is true – or mostly true, anyway.  (Machines can be very expensive to run.)

Slate’s conclusion?  Humans are better at producing journalism, as the quote above notes.

Well, sure – but is that the right question?

Horses are more empathetic than cars.  They won’t – by and large – go off a cliff by themselves if you take your eye off the road or doze off.  They’re superior at jumping over obstacles.  They don’t need messy fossil fuels to run.  In short, horses are better than cars at providing horse-type locomotion.  But as a method of mass transportation, they suck.

So – yes, humans are better at producing human-type journalism, and God knows, we need much more of that.  But is it the only thing we need, and what are machines better at producing that the world needs?

I don’t mean to suggest