Category: Uncategorized

Climate change. Obesity. Stress. Misinformation. What do they have in common?

The classic metaphor of a frog sitting in slowly-heating water is unfortunate in that we can’t really relate. “What a dumb frog! He can’t even tell the water is getting hot! Fortunately, I would notice.”

We’ve made a lot of progress with faster-acting problems. Hunger. War. You notice those pretty quick.

The problems we can’t seem to get a grip on are caused by factors that act so slowly, we don’t feel them. It’s very hard to prove that any of the thousands of chemicals widely used in consumer products are the root cause of anyone’s particular disease. Sure, many of these chemicals were shown to kill laboratory rabbits in high enough doses. But those are rabbits. And high doses. It doesn’t prove anything!

How long did it take to definitively prove that smoking causes cancer? Smoking literally involves filling the lungs with visible, foul smelling smoke! So how are we supposed to make any headway with rose-scented soap additives?

One sugary snack doesn’t give you diabetes. You can’t see the ocean rising as you drive your gasoline car or your coal-sourced electric car. You can’t feel yourself becoming radicalized as you read one more eye-catching social media post.

The best hope for progress on climate change seems to be the fires, floods, and hurricanes that we can see. Finally, some symptom that acts on a timescale we can process!

Even the Covid pandemic — which was very fast moving — can be seen as a win for science. Innovative vaccines developed and distributed in record time despite political morass. And notice — all those people with underlying medical conditions (caused by who knows what? a million bags of chips? a million applications of body lotion? a million hours sitting in traffic? just genetics?) — the cause of death is still: Covid-19. That’s the part we can see. It’s the part we can measure.

If all of this is true, then the challenge of our times is finding ways to see the slow. Juxtaposing the past and the present. Compressing big data into something comprehensible. Making statistics trustworthy. Connecting the low doses and the small moments to something larger. Seeing the big picture. Feeling the big picture.

Finding ways to make the gradual, visible.

“If I don’t have a plan B, I am by definition powerless. By definition, I will not take big risks. I will play it safe. But if I have a plan B, suddenly I become powerful. Suddenly I’m free to do something that I’m really excited about.”

-Frederic Laloux (via Leadermorphosis)

“I always say: when there are two sides to an argument, both are wrong. So there isn’t much of a value to debate in my opinion — no one’s going to get persuaded, and both sides are wrong anyway, so your premise is wrong that one side is wrong and one side is right.”

-Horace Dediu (podcast)

From the Wall Street Journal (via John Gruber), “Facebook Executives Shut Down Efforts to Make the Site Less Divisive”:

A 2016 presentation that names as author a Facebook researcher and sociologist, Monica Lee, found [that] “64% of all extremist group joins are due to our recommendation tools” and that most of the activity came from the platform’s “Groups You Should Join” and “Discover” algorithms.

Gruber noted:

In the old days, on, say, Usenet, there were plenty of groups for extremists. There were private email lists for extremists. But there was no recommendation algorithm promoting those groups.

This crystalized in my mind the extent to which recommendation algorithms are central to both the successes and failures of social media. “Success” in terms of reach: the algorithms pick the most addictive posts to keep people hooked on the site, leading to massive engagement; “failure” in terms of the human cost: the most addictive posts are not only addictive but also often divisive, distressing, and untrue. The algorithms are widely and directly boosting extremely problematic content!

And this isn’t new to social media — human editors at tabloids and cable news have been using similar “recommendation algorithms” in their heads as they pick stories and headlines to keep people watching.

How do we make alternate recommendation algorithms available that optimize for other qualities, such as well-being, empathy, and trust?

“Historically, the heartbeat of racism has been denial — to deny that one’s ideas are racist, one’s policies are racist, and certainly that oneself, and one’s nation, is racist. By contrast, the heartbeat of anti-racism is confession, admission, acknowledgement, the willingness to be vulnerable, the willingness to identify the times in which we are being racist, being willing to diagnose ourselves and our country and our ideas and our policies. …

“To grow up in America is to grow up with racist ideas constantly raining down on your head — and you have no umbrella, and you don’t even know that you’re wet with those racist ideas, because those racist ideas themselves cause you to imagine that you’re dry. And then someone comes along and says, you’re wet, and these ideas are still raining on your head — here’s an umbrella. You can be like, thank you! I didn’t even realize I was drenched!

“[So] essentially, to be anti-racist is to admit when we’re being racist. [In my book] I had to basically admit and chronicle some of the most shameful moments of my life. … It took me almost a year to write the first few chapters.”

-Ibram X. Kendi, via Unlocking Us (Brené Brown)

“If you’re a white American who has racist ideas, and you’ve perpetuated those ideas… you were simultaneously a victim and a victimizer.

“[Throughout history] you had so many powerful Americans trying to convince [everyone] that black people were inferior, [because this belief served] their own self-interest. … Poor whites whose poverty was directly the result of the riches of white slave-holders became [convinced that] it should be this way! And so then those people [in power] were able to get richer and richer.

“People have been tricked, they’ve been manipulated, they’ve been hoodwinked, and that’s what I want people to realize.”

-Ibram X. Kendi, via Unlocking Us (Brené Brown)

I recently read Loonshots by Safi Bahcall, a physicist turned biotech entrepreneur. The book included some interesting stories and ideas, but I didn’t find his terminology or physics analogies very useful. His word “loonshot” just means an innovative project with uncertain chances of success — trying to capture a notion I usually phrase as “you can’t get innovation without risk”.

The book’s thesis (as I see it) is that any organization that wants to be innovative should study and copy the DARPA model. Specifically, the US military is split into two branches that are organized very differently to optimize for very different levels of risk tolerance. The rigid hierarchy of the regular military is designed to carry out orders with no surprises. In contrast, the loose DARPA organization is composed of independent research labs working on innovative projects, most of which fail but some of which eventually transform the military’s capability (and beyond — we have DARPA to thank for the internet, GPS, voice recognition, and many other technologies). Other notable success stories have been organized in a similar way — from AT&T Bell Labs to the startups and tech giants of Silicon Valley — with separate yet interconnected groups focusing on predictable business vs. new research.

The part of the book I found interesting was the discussion of how critical it is to manage the interface between the two types of organization. If researchers don’t stay grounded in pragmatic operational needs, their research becomes less useful. And if operations teams don’t understand the research results or aren’t willing to try them out, then the innovations never make it out of the lab. The challenge is finding intermediaries who can talk to both sides — to convince academics that they need to pay attention to seemingly mundane details, and to convince bureaucrats that it’s ok to make measured changes and take risks on promising innovations.

I saw this challenge first-hand at Tableau. As a researcher, I didn’t fully understand the practical limitations of the business and I was frustrated when engineering teams showed little interest in adopting my prototypes. Meanwhile, engineers didn’t fully understand the promise of my research and were frustrated when I distracted them with ideas that seemed to put their operational goals at risk. In retrospect, it would have been helpful to have liaisons whose sole job was to bridge this gap, providing the necessary context to both sides and keeping the lines of communication open. I agree with Bahcall that such work is a difficult and under-appreciated specialty.

“There is no courage without vulnerability. But we’re all taught to be brave, and then we’re all warned, growing up, to not be vulnerable. And so that’s the rub. When you have bravery without vulnerability, that’s when you get what we’re looking at today: all bluster, all posturing, no real courage.”

-Brené Brown (via On Being)

“Sometimes it’s not the forecast that matters — it’s whether that forecast helps you think harder or encourages you to stop thinking.”

-Tim Harford (Cautionary Tales ep. 9)

“We don’t have to understand everything about each other in order to be present with one another. I think that we have mistaken empathy as walking in someone else’s shoes. Let us be clear, you can’t, because that person lived a lifetime in their shoes. But what we can do is witness and accompany.”

-Lennon Flowers (via On Being)