A week in review, 2018-W41





Evercrisp apples at Eckert's


Notes from Data for Good 2018

Last Friday, I went to an event called Data for Good, hosted by Washington University's Olin Business School. Here are a few notes from the event...

The most interesting new thing I heard was about the St. Louis Vacancy Collaborative. In short: a group of people started working on a web portal at OpenSTL's 2017 hackathon to use data posted publicly by the city of St. Louis. They did this without permission—my kind of people—using data that was there, then provided the useful results to the city. There's a better description here from STLPR: Vacancy Portal opens door to data on abandoned parcels in St. Louis. Of course, the thing itself is interesting, but even more interesting is the thought that comes with it: there are opportunities to do useful work just laying around out there waiting to be discovered, and you don't have to be picked to do the work—you just decide to do the work. (See also: Seth Godin's latest Akimbo podcast: You're It.)

(More: OpenSTL has a Meetup group. They're still working on the project. Even tomorrow (2018-10-13).)

In the next panel, someone—I think it was Philip Bane of the Smart Cities Council—referred to wicked problems in designing solutions to social problems. Wicked problems are one of those terms that get thrown about without much thought. The term originates here, in a paper you should read if you care at all about solving difficult, intertwined, impossible-to-optimize-for-everything problems: Rittel, Horst W. J.; Webber, Melvin M. (1973). "Dilemmas in a General Theory of Planning". Policy Sciences. 4: 155–169. (doi: 10.1007/bf01405730, pdf). The thing deserves its own post. In the meantime, here are some notes about it.

At the end of the day, Jake Porway of DataKind gave the keynote presentation. Here are a few recommended resources from his talk:

Notes from Planning for the Human-Digital Workforce

I listened into an MIT Sloan Management Review webinar this morning, Planning for the Human-Digital Workforce, with Mary Lacity. I like to learn more about automation or augmentation or the general idea of What Happens Next when it comes to humans and computers, or humans vs. computers, or however you want to look at it. It's going to happen. It has happened. I do it myself, although in a really unsophisticated way. It's an interesting and anxious time.

Anyway. Here are a few notes from the presentation:

Characteristics of...

  • Robotic Process Automation: structured data; rules-based processes; deterministic outcomes
  • Cognitive Automation: structured and unstructured data; inference-based processes; probabilistic outcomes

Some references:

Some work by Mary Lacity:

Drawing competition

So my wife challenged me to a drawing competition.

I don't know why. Maybe she was concerned that I had developed too much self esteem recently. There's a cure for everything these days.

She had already challenged her parents on WeChat (and won), so I really had to grounds for holding out.

Judge not lest ye be &c.

See, I was trying to go for the I-can't-compete-on-skill-so-maybe-I-can-do-something-interesting-with-minimal-effort angle. Make the lines quick. Decisive. Get at the essence of the bird. The inner bird.

Kind of ended up with the angry chicken look in the end. As my mother-in-law put it: 不是个好鸟 (not a good bird).

A week in review, 2018-W40





Maria Bamford, Psych Ward, This is Not Happening


Lemur at the STL Zoo



Last week I signed up for two blockchain related courses on edX, developed by UC Berkeley: Bitcoin and Cryptocurrencies; and Blockchain Technology. Together they add up to a certificate: Blockchain Fundamentals.

Superficially, I'm against collecting certificates because they are, like this one, just tokens without much obvious value. But maybe those tokens can be redeemed by someone willing to pay for the knowledge or potential utility they represent. I don't know.

That's not the driving reason anyway. Mostly I was annoyed at missing out on a Hot Topic™ that I didn't understand. (Although it seems to have peaked.) I think very few people understand it, or even care outside of curiosity about what Bitcoin is. It's not an intuitive concept. And it's fraught with fervent True Believers. But it was driving me crazy to hear about it and not understand anything—had to fix that.

I'm collecting some notes here—Blockchain— and might post some interesting things here from time to time.

Sunk costs

Here's an episode of Seth Godin's Akimbo podcast that has been banging around my head since I heard it a few weeks ago: Ignore Sunk Costs.

The basic idea—although you should listen to the whole thing—is that the time and effort you've spent in the past working on something or becoming something is like a gift from your past self. And you don't have to accept the gift. You can say "no, thank you".

I suppose that's a natural concern for a middle-age human with basic needs taken care of. Am I on the right path? Who knows, anyway, right? Keep on straight ahead, or head left or right at the next fork. It's how I feel about my two diplomas in aerospace engineering. (I haven't seen those in a while... I wonder if they're still in the closet...) It's how I feel about the arc of my career so far. It's how I feel about some organizations and relationships and investments and clothes and habits and so on which just hang on in some niche of my life, and it's not clear always if they're serving me or the other way around.

But thinking about these things as a gift from a past self that I can refuse helps to relieve the pressure. No, thank you; or, still, yes. It can be a new decision. It doesn't have to be an old decision that got locked in forever.

Here's another version to listen to by David McRaney on You Are Not So Smart: The Sunk Cost Fallacy.

Tools as abstract excuses to create and understand

I saw this interesting post on Twitter from Chris Krycho the other day:

One of the frustrating side-effects of being 100% self-taught in software and computer science is having massive, *massive* gaps in my knowledge and experience, and accordingly being actually intimidated by entire classes of problems. [...]

I replied to it at the time, but I couldn't quite shake the idea out of my head. I recognize that feeling. Self-taught leaves out quite a lot. Some of the things you know aren't necessarily right, and some of the things you don't know you don't know you don't know.

It also fits in with a recent pair of episodes from Talk Python To Me: Coming into Python from another Industry (part 1) and Coming into Python from another Industry (part 2). These two episodes are talks with panels of people who turned some side work they did in Python at their old jobs into new jobs that required Python (sometimes at the same organization). Most of them told the same story: they learned Python on a lark or to solve a problem, then it turned into a superpower, then they used their superpower to solve more difficult problems and change their lives. They didn't set out with a goal in mind—they created, learned, kept at it, and drip-by-drip became someone new.

So. Two things:

One. That initial post and the podcasts turned into a solid creative week of writing some tools at work. I had lost the confidence to do that for a while, and now it's back. All the old patterns were there I could manipulate them into place like Legos, often in new configurations.

Two. I don't make tools for tools' sake. Sometimes I'll write a bit of software that saves time or produces a better looking output, and there's some joker that will ask if making tools is something I want to do. No. I do it because it helps me get the work done, but also because I get to think about the problem in a deeper, more thorough way than I otherwise would. You have to understand the interfaces of the problem, as well as what it's supposed to do and why, in order to get a tool to work with it. You have to think more abstractly when you're designing the software to solve the problem—you can't reach inside it and fix things that don't line up, you have to train the software (or the inputs to the software) to identify aspects of the problem and deal with it.

And maybe also Three: it's fun to make things.

A week in review, 2018-W34





我不是药神 (2018)



Believe in the other side

James Altucher: How To Succeed in Life

There was a passage in this post that caught my eye—

I’ve asked 400 of the most successful people in the world what they did when they were at their worst.

How did you survive?

Almost always the answer is: WAIT.


When you thrash, you crash.

Just be quiet. Don’t move too much. Be calm. Be patient.

What can I say? Look at my history and it's seems pretty clear that I don't do what the man says. I've dumped jobs and volunteer gigs far, far too soon. But I believe the advice. Even if it's just because I know the opposite doesn't work.

I know a venue where waiting and patience did work for me: running. In endurance running I routinely started in the back of the pack. Sometimes I would show up at races late and start a few minutes after everyone else. It was a good tactic for me. Let the others take off with their adrenaline surges. It's a long day. They'd be back. 50 km, 50 miles, 100 miles—after a long day I would reel all those early streakers in eventually (but for the fastest, of course). It was just a matter of time if you believed in it.

There was one other aspect of running that rewarded patience: hills. In endurance running the conventional wisdom is to walk the hills. Save your legs for the rest of the race. It's a long day. But that was my secret weapon: run the hills. If you were patient and believed that you were going to be fine later after suffering for some time now, you'd be OK. More than that, I didn't just feel OK rolling over the top, I felt strong for having waited it out.

One more thing: in the long runs, when things felt bad you had to believe that they would eventually not feel so bad. It's a long day. There was one race I remember falling apart around mile 40 in a 50-miler. I clawed out of it by clinging to a simple rule: run a minute, walk a minute; run a minute, walk a minute. Eventually: run two minutes, walk a minute; run three minutes, walk a minute. I don't know when, but eventually I didn't need the walk-a-minute part. There's no magic to it. No superhuman feats. You just have to believe that there's an Other Side to whatever difficult thing you're dealing with.

I don't know how to bring that to work yet. It seems like an easy enough lesson. But work feels like it has a different kind of pressure associated with it. A long race ends, and you know where it ends. If you walk, if you run, if you crawl, the finish line is at a fixed spot. Work? It's different. Here's a good post from Seth Godin: Evanescent boundaries

Instead, real life has changing rules, hidden rules, rules that aren't fair. Real life often doesn't reveal itself to us all at once, the way the rules of baseball are clearly written down.

And so, the first challenge of real life is: find some goals. And the second: figure out some boundaries.

It doesn't pay to get stressed out that these goals and these boundaries aren't the same as everyone else's. It doesn't pay to mourn the loss of the rigid structures that worked in the world you used to be in.