A very short post, sparked by a single paragraph.

It was in a NYT story about the debate over language on the left (BIPOC/Latinx/ Microagression/AAPI/LGBTQIA+ and more); the story overall was smart and interesting, but this paragraph was particularly insightful.

Saying something like, ‘Black people are less likely to get a loan from the bank,’ instead of saying, ‘Banks are less likely to give loans to Black people,’ might feel like it’s just me wording it differently,” Rashad Robinson, president of the racial justice organization Color of Change, said. “But ‘Black people are less likely to get a loan from the bank’ makes people ask themselves, ‘What’s wrong with Black people? Let’s get them financial literacy programs.’ The other way is saying, ‘What’s wrong with the banks?’”

And Mr. Robinson is absolutely right: Words matter, and how we use them matter. Beyond news judgment – itself a whole area we can and should explore – and the framing of stories (ditto), even simple, declarative, uncontroversial factual statements can affect how readers look at a subject.

You might be thinking: Perhaps he’s overstating the importance of this. And it’s true that probably a single use of a phrase or a framing doesn’t have much impact. But cumulatively, small things do build and can change our perceptions of the world. We all have biases, based on how we see categories of things and how experience and culture of them filter into our brains. (This all from The End of Bias, a book I’m deep into now and plan to write about soon.) And words in stories are part of that experience and culture.

This won’t be easy to address. Undoing decades of writing habits is hard.

It would be easier if it wasn’t words. Certainly the graphics and data visualization community has always been sensitive to how information is designed – and writing is a form of information design – and that’s perhaps because that visual grammar is in many ways still evolving; and as a result, everything is up for discovery and debate. Writing, on the other hand, is a much older technology, and so much of it is embedded in us that we often don’t think as much as we should about how the words go on the page (or screen), and certainly not when we’re on deadline. I confess I haven’t thought about what I write the way Mr. Robinson has, and that’s my bad.

So how can we address this? I’m not sure, other than more scrutiny and awareness. But I’m sure that’s not enough.

The NYT recently ran a great opinion piece, by Jessica Nordell and Yarnaa Serkez, about the long-term impact of bias on women in the workplace. The magic was in the math.

It wasn’t that the piece called out egregious examples of discrimination, or identified companies or people that were really bad actors (although there was some of that); it was that it called attention, via a simple simulation, about how even small levels of bias – whether conscious or unconscious – can accumulate over time and lead to very large effects. In other words, it wasn’t trying to pin issues on particular bad actors or motives, but flagging systemic issues we might be otherwise blind to.

And that’s something we should think about too, as we write about complex systems – to resist the temptation to just look for for bad guys but instead to help readers really understand how the world works, even if terrible outcomes are the result of small flaws or human frailty.

The piece features a simulation of a company, NormCorp, where employees are promoted based on their performance reviews. You know, more or less like a regular company.

NormCorp is a simple company. Employees do projects, either alone or in pairs. These succeed or fail, which affects a score we call “promotability.” Twice a year, employees go through performance reviews, and the top scorers at each level are promoted to the next level.

So if all things are fair, men and women progress at the same rate through the company. But what if there’s some in-built bias in the system that regularly rates women slightly lower then men? It doesn’t have to be intentional, or the result of bad motives, or even conscious. It just has to exist – and it doesn’t even have to be against women. It simply has to be systemic. Maybe managers have a (unconscious) preference for people that look or sound a certain way, or who have gone to a certain university, or come to work early, or socialize after hours. Whatever.

When we dig into the trajectory of individual people in our simulation, stories begin to emerge. With just 3 percent bias, one employee — let’s call her Jenelle — starts in an entry-level position, and makes it to the executive level, but it takes her 17 performance review cycles (eight and a half years) to get there, and she needs 208 successful projects to make it. “William” starts at the same level but he gets to executive level much faster — after only eight performance reviews and half Jenelle’s successes at the time she becomes an executive.

Shameless self-promotion post:

Incredibly moved and honored to have been named the inaugural recipient of the Online News Association‘s Impact Award, for a “trailblazing individual whose work in digital journalism and dedication to innovation exhibits a substantial impact on the industry. “

I’m not sure I would have chosen myself to get this award, so I’m very glad the ONA board was making that decision and not me. It was nice to see shoutouts in the citation to things I’m really proud to have been involved with, from Connected China to WhoRunsHK to CitizenMap, as well as Reuters’ award-winning graphics and data teams. I’m even happier to have it also call out this blog and the Tiny News Collective, a really smart and innovative project that sprung from the fertile mind of Aron Pilhofer, that I’m currently privileged to be a part out (and I’ll have to write it about soon.)

And especially happy to have a chance to talk, in short remarks when accepting the award, about how we need to not only work to make sure our newsrooms reflect the communities they serve, but also to ensure that our coverage more accurately reflects the world we live in.

This is an excerpt.

So that was a very nice evening. And now back to the salt mines.

Pauli Murray. Charcoal on paper, Gina Chua 2020

It’s been a while since I posted, I know. Events got in the way, notably trying to get people out of Afghanistan. But here I am again.

I’m in the middle of reading the autobiography of a remarkable person, Pauli Murray – a pivotal figure in legal and civil rights circles of the 20th century, and yet someone most people haven’t heard about. Why is that? What gets in the way of our ability to see stories that matter, and what stories are we now missing – what events aren’t considered “newsworthy” – because of the blind spots we have?

But first, a plug: I came to know about Pauli Murray via a great documentary about their life, My Name Is Pauli Murray, by Betsy West and Julie Cohen, who also directed RBG. It’s well-worth watching. Pauli was a feminist, civil rights pioneer, legal scholar and the architect of the winning arguments behind some critical U.S. Supreme Court rulings. The first African-American woman to be ordained an Episcopal minister. Also, queer, non-binary and possibly transgender. How did someone pack so much into a life that began as a young Black orphan in North Carolina? Watch the documentary, read the book; Pauli is well-worth getting to know.

But that’s not what this post is about. It’s a long one, so apologies in advance.

Early in the documentary, you learn that Pauli was arrested and jailed in 1940 for refusing to move back to the rear of a bus, as was required in then-segregated Virginia. That was 15 years before Rosa Park’s similar, but much more celebrated, act of civil disobedience. During a panel discussion with the filmmakers at Reuters, the question was asked: Why wasn’t there more coverage at the time of Pauli’s action?

The answer: There was. Just not in the mainstream press. Black newspapers covered it, as they did issues like lynchings and everyday discrimination. But this was rarely deemed “newsworthy” by the mainstream – white – press.

And that raises bigger questions about what we deem to be worthy of coverage, what constitutes “news”, whose voices we hear, and who gets to make those decisions.

This aren’t new questions, but they are important ones, not least in the wake of the racial justice protests around the world in the summer of 2020; and while it’s heartening to see that those events have raised newsrooms’ sensitivities to those kinds of stories, it also raises the question about what other stories we might be missing, what other as-yet-undiscovered blind spots we might have.

Sometimes we miss stories because we don’t have connections into communities where things are happening; that’s a problem of a lack of diversity in newsrooms (and not just of gender and ethnicity, but also of class and background). Sometimes editors dismiss ideas because they don’t jive with their view of what’s important; that’s a problem of mistaking one’s viewpoint for being the most valid viewpoint. And Gary Younge, a journalist and academic, notes in an incredibly insightful piece that sometimes we don’t pursue important stories because they are – regrettably – just not out of the ordinary.

Just riffing off my recent riffing off on Noise, the new book by Daniel Kahneman, Olivier Sibony and Cass Sunstein: OK, so people are flawed, illogical and inconsistent, and that leads to injustice – even when the people making the decisions aren’t biased.

(Of course it’s worse when they are.)

And we as journalists should expose injustice in systems whenever we find it – no matter whether the cause is.

But more importantly, we also can and should delve into how those systems could be better. As well as think about how these ideas could apply to our own decision making and our own organizations – such as when we hire or promote, since that’s a place of intersection with systems, journalism and diversity.

So how does one reduce “noise” and inconsistency in decision making?

The book lists a series of practices that help, mostly involving slowing us down from our very human habits of jumping to conclusions, relying on intuition, or building a narrative to support a decision we’re predisposed to make, regardless of the facts. And – more controversially – turning more to algorithms to help us drive more consistency.

These aren’t hard things to do – they’re just a pain, and they take away some of what we think of as our essential humanity: Our ability to make exceptions, look beyond the facts, go with our gut. And sometimes those are good instincts – and many times they’re not.

Among the suggestions: Break judgments up into individual tasks, so we’re less inclined to make holistic decisions, overriding inconvenient facts. Get multiple, independent opinions, and aggregate them into a wisdom-of-crowds judgment. Think statistically, not in terms of narrative or neat causal stories. Resist premature intuitions. Try to make judgments on just the issues that are relevant.

Take hiring: We often based those decisions on interviews and discussions with a hiring panel – possibly one of the worst ways we can find the best candidate. Instead, where there are specific skills we’re looking for that can be quasi-objectively judged, let’s make applicants take tests that measure those skills. And anonymize the entries, so we’re not swayed but who someone is, or how the look, or what school they went to.

If you’re trying to hire a copy editor, have candidates take a copy-editing test. And scrub their names from the submissions. Have the hiring panel grade the results – independently. Then compare notes. If you’re looking for a reporter, get anonymized reporting memos from the applicants.

That’s not to say that you shouldn’t also interview the candidates. But the test may throw up results you weren’t expecting.

Look at the experience of US orchestras, which I wrote about some time ago:

Consider that in 1970 women comprised less than less than 10% of major orchestras in the US and fewer than 20% of new hires.  As Mahzarin (Banaji) recounts in her book, back then auditions for new members were conducted in front of a team of seasoned musicians, often from that orchestra.  You’d expect that they had well-trained ears, able to select the best candidates.  And they largely picked men.

But then an interesting thing happened when they started auditioning candidates behind a curtain, and taking pains not to let the panel know if it was a man or a woman was playing.  More women won spots.

Whose fault is it when something bad happens? Who do we hold to account when we find injustice?

It’s a natural – and good – impulse journalists have, to look for wrongdoers when we see wrongdoing, to identify bad actors and uncover bad motives. And long may that continue.

But what happens when injustice isn’t anyone’s fault; if it’s – essentially – everyone’s fault?

That’s at least one of the takeaways from Daniel Kahneman’s interesting new book, Noise, written with Olivier Sibony and Cass Sustein. It’s about how, beyond bias, discrimination and prejudice, simple randomness – caused by human frailty (“A flaw in human judgment”) – can also lead to injustice and inequality. And it offers a lesson for journalists: We should look for and expose systems that are failing, regardless of whether there’s systemic bias in them.

The book offers example after example of how what should be consistent judgements made on the merits of an argument often aren’t, even when the people making those calls are trying hard to be impartial and fair.

A study of thousands of juvenile court decisions found that when the local football teams loses a game on the weekend, the judges make harsher decisions on Monday (and, to a lesser extent, for the rest of the week.) Black defendants disproportionately bear the brunt of the increased harshness. A different study looked at 1.5 million judicial decisions over three decades and similarly found that judges are more severe on days that follow the local city’s football team than they are on days that follow a win.

Or this:

A review of 207,000 immigration court decisions over four years found a significant effect of daily temperature variations; when it is hot outside, people are less likely to get asylum.

The fundamental thesis of the book – which, admittedly, can be a little hard to get through – is that we don’t spend enough time looking at “noise” in our systems: the factors that produce wide variations in what should be much more standardized decisions. That’s not to say that bias and systemic bias isn’t an issue, and certainly journalists expend a huge amount of effort to find cases of discrimination, both blatant and subtle. But we don’t focus as much on the noise that can cause as much injustice in outcomes. If immigration cases aren’t judged purely on the merits, if the results are somewhat random, that’s just as bad an outcome as if cases are regularly stacked against a type of applicant or group.

Just the facts, ma’am – Sgt. Joe Friday, Dragnet

Not really. All stories need framing and narrative for the facts to speak, for audiences to engage, and for insight to emerge. We call that editing. But in an age of visual, interactive and multimedia journalism, maybe we should call it designing.

There’s a nice piece in the New Yorker (largely a review of a book, A History of Data Visualization & Graphic Communication) that makes a point that I love to make: That how information is presented – designed, for want of a better word – isn’t just an add-on to other forms of journalism that can make a story better; it’s as much an independent form of narrative that, properly used, can bring completely different insights to users.

It can even literally make the difference between life and death.

The piece starts with the now-famous chart of the space shuttle’s O-ring failures in frigid temperatures, and how poor presentation of that data may have misled engineers to believe the components were robust enough to hold up in cold conditions, and hence green-light the tragic launch. They had all the data; they just didn’t see it clearly. And that’s because it wasn’t presented correctly. As the story notes:

A decade later, Edward Tufte, the great maven of data visualization, used the Challenger teleconference as a potent example of the wrong way to display quantitative evidence. The right graph, he pointed out, would have shown the truth at a glance.

The flip side of that, as I wrote some time ago, was how information presented correctly can bring instant insight:

Probably the best-known example of the value of mapping is John Snow’s famous map (above) tracking cholera outbreaks in London, showing that an outbreak in the mid-1800s could be traced to a contaminated pump.   Without the map, you’re faced with a long list of addresses where outbreaks occurred; with the map, you can immediately see where there’s a real concentration of cases and hence where to investigate.

To be sure, those are examples of single information graphics rather than the all-bells-and-whistles multimedia interactive extravaganzas that we’ve come to expect from any major journalism project. But the core point remains the same: It isn’t simply how words are edited, pictures cropped, or charts plotted; it’s also how they are integrated, how the narrative flows, and how the audience experiences them that brings the understanding, engagement and insight to the fore. It’s how the information is designed.

So it’s been a while. OK, a very long while. OK, a very very long while.

But since this post is about the value of old stuff, perhaps it’s appropriate it’s been three years or so since I wrote a real new post. (Although the real reason for not writing for a while is, as I’ve noted here, that I’ve been kinda preoccupied.)

In any case, I was struck by this interesting article at Digital Content Next that asks the thought-provoking question: What if the value of news isn’t what’s new? It cites the example of the Daily Nation, Kenya’s largest national paper, which is starting a subscription service – not for current news, but for anything older than seven days old. In other words, the “new news” is free; it’s the “old news” you have to pay for. As the piece notes:

So, can an approach like this work? Can you effectively sell a “news” subscription where the content you’re charging for isn’t, well, new?

Spoiler alert: Yes.

Or: Probably yes. Or: Possibly yes, if… And we’ll get into what those ifs are, and some reasons more people aren’t trying this strategy. And why, perhaps, they should.

But back to the article, which goes on to cite examples like National Geographic, Esquire and others that have managed to monetize their archives. The Daily Nation may well be the first – I admit, I haven’t done exhaustive research on this – to bank its entire subscription strategy on selling, well, old news.

It’s not as crazy as it sounds. True, some readers/users really value getting information first – and certainly I work at a news organization which is largely built around speed, sometimes to the tune of milliseconds. But let’s set Reuters and the like apart for a moment, and focus on the vast majority of other newsrooms. A lot of news is widely reported, and if the information is behind a paywall at one site, I can probably get the gist of what I need to know from another site. True, I may really like one news organization’s take on a particular event, but in many cases there’s not necessarily enough differentiation to make me take out my credit card.

Sure, there are exclusive stories, features and deep investigative work, but most news sites pin their value on news.

But speed is only one metric that readers value. As I noted a decade ago:

All those events mattered in some way or another, but knowing about them minutes – or even hours – ahead of others isn’t critical to most of us. What often matters more is the thoughtful, considered analysis of events, or perhaps the exploratory database/interactive that lets us understand the information on our own terms, or the insightful commentary piece a couple of days later.

And that’s where archives – or previous reporting, or well-structured data – can really bring new, and sometimes instant additional value to an audience. Very few events happen in a vacuum; if there’s a plane crash, how many others happened at that location, or with that airline, or with that type of aircraft? If a politician makes a claim, who else has made the same assertion, who has debunked it, what other claims has he or she made? And so on.

Yes, a good journalist can dig that all up in the heat of coverage, and get it into a well-written and nuanced story. But it’s tough to do on deadline. More importantly, much that information probably already exists in the site’s old stories; why not just let readers find it – or better yet, let it find readers?

So it’s been a while (a long while!) since I’ve written here – not because there isn’t much to say about changes and developments in technology, journalism and news products; there’s in fact probably too much to dive into, analyze and brainstorm around.  I just haven’t had much time. 

One reason is this: 

I’ve been busy with a different type of change and development.  Specifically, about me.

I’m transgender, and have as of today, transitioned into what I know to be my true identity.  There’s not much else to say, although there’s a bit on the About section.

Thanks for visiting, and I hope one of these days to get back to writing about how journalism is or should be evolving.

It takes courage to grow up and become who you really are – e. e. cummings

Just a riff on a recent NYT magazine piece about the debate around “autonomous weapons,” or machines that can make decisions about who and when to kill.  Spoiler alert: There’s no consensus about them.  Actually, not even close to being a consensus. Which is probably a good thing.

That said, it’s a good entryway to revisit the notion that we as an industry/profession could be doing a better job covering the multiple algorithms that now govern our lives, even if they aren’t literally designed to kill us.

Algorithms influence what news and information we see, how financial markets behave, where police put their resources, whether we can get loans and at what price, and much more.  And beyond that, they have to power – as do other automations – to reshape how we build and structure our world, beyond replacing humans.

As the NYT piece notes about the debates about autonomous weapons:

This argument parallels the controversial case for self-driving cars. In both instances, sensor-rich machines navigate a complex environment without the fatigue, distractions and other human fallibilities that can lead to fatal mistakes. Yet both arguments discount the emergent behaviors that can come from increasingly intelligent machines interpreting the world differently from humans.

Precisely.  Autonomous machines can and will go beyond replacing humans and potentially fundamentally change our world – not necessarily for better or worse,