Where do you keep the (informatics) pixie dust? (borrowed from NYTimes)

This is hilarious: angsty flowcharts to help guide readers. Must-read article.

Fawzy Taylor, social media and marketing manager of the bookstore: A Room of One’s Own, Madison, WI, via NYtimes “These Memes Make Books More Fun”

Thank you to Fawzy Taylor, whose brainchild this is. Fantastic in so many ways.

Why can’t we build our informatics and our internal education this way? For example, for newbie informaticists, how about my book-recs graphic above, based on the same idea?

CMIO’s take? What do you think of the graphic? of the style? of the content? Guess what? It doesn’t matter, if it gets us talking!

Steven Pinker Thinks Your Sense of Imminent Doom Is Wrong – The New York Times

Steven Pinker image from wired.com

“It is irrational to interpret a number of crises occurring at the same time as signs that we’re doomed.”
— Read on www.nytimes.com/interactive/2021/09/06/magazine/steven-pinker-interview.html

The Xenobot Future Is Coming—Start Planning Now (wired.com)

“…the ability to recode cells, de-extinct species, and create new life forms will come with ethical, philosophical, and political challenges”


With CRISPR, the molecular scissors technology ,we are gaining not only read, but WRITE access to our genetic data. Writing code will no longer be limited to computers (and electronic health records), but into living organisms. Are we ready? The technology is racing ahead of our ability to think about and deploy it for the good of all.

Can Learning Machines Unlearn? (wired.com)


How much data?

I’ve been thinking about this a lot. In our recent work designing predictive algorithms using linear regressions and neural networks, and similar approaches, we’ve discussed the use of EHR (electronic health record) data, and have had some success using such algorithms to reduce deaths from sepsis (blog post from 10/6/2021).

One of many problems, is “how much data?” And it has been interesting to work with our data science colleagues on creating a model, and then carefully slimming it down so that our models can run on smaller data sets, more efficiently, more quickly, with less computing power.


A related problem is “when do we need to forget?” EHR data ages, the way clinicians record findings can change. Our understanding of diseases change. The diseases themselves change. (Delta variant, anyone?)

Will our models perform worse if we use data that is too old? Will they perform better because we gave them more history? Do our models have an “expiration date?”

The Wired.com article above talks about having to remove data that was perhaps illegally acquired, or perhaps after a lawsuit, MUST be removed from a database that powers an algorithm.

Humans need to forget. What about algorithms?

Isn’t human memory about selective attention, selective use of memory? Wouldn’t a human’s perfect memory be the enemy of efficient and effective thinking? I’ve read that recalling a memory slightly changes the memory. Why do we work this way? Is that better for us?

Is there a lesson here for what we are building in silico?

CMIO’s take? As we build predictive analytics, working toward a “thinking machine”, consider: what DON’T we know about memory and forgetting? Are we missing something fundamental in how our minds work as we build silicon images of ourselves? What are you doing in this area? Let me know.

A picture of change (and inspiration for informatics. NYTimes)

From the Metropolitan Museum of Art via NYTimes: a Japanese Print to teach us about the modern world

The artistry in our journalism can be remarkable. Spend a few minutes zooming in and out of this Japanese print with Mr. Farago. It is inspiring and completely engrossing.

From an informatics perspective, can we take an EHR screenshot, and zoom in and out as entertainingly? Could we =gasp= make learning about EHR’s as engaging as an art exhibit?

James Webb telescope: astounding science and engineering (wired)

Zero Kelvin! Lagrange Points! Infrared parabolas! Light years and Time Travel! wtf?! We are living in the future.


If you have not been following the journey of the James Webb telescope, here is your chance to catch up. TL;DR: it is going well and in a few months we can look forward to astounding images from further away than ever before, and from further back in time than ever before. I can’t wait. Read the nice summary article from Wired.com, above.

Why to-do lists don’t work (Wired.com)

from wired.com


Ah, yes, the eternal search for more productivity by downloading apps and other tools that “promise to boost your productivity!” How could you not? These (mostly) free apps and click-bait make it sound super-easy!


Use our checklist app! This is just like “Getting things done, but modern!” Try our technique; just $14.99 for the book that explains our system! Never be unproductive again!


Read the article. Yes, it is on the longer side, and it will be 10 minutes you won’t be getting something done.

But, you’re already here wasting time reading my blog. Whatever you were trying to get done, you were already unproductive. Sorry.

Here’s the crux of the article…

Clive Thompson says it much better than I will, so go read his article above in Wired.com. I’ll just say: apps won’t create more time, and our present selves overpromise what our future selves might be willing to do. You are your own worst enemy.

Every to-do list is a midlife crisis of unfulfilled promise. Winnowing away things you’ll never do in a weekly review is crucial, yet we dread it for what it says about the boundaries of existence. Our fragile psyches find it easier to build up a list of shame, freak out, and flee.

Clive Thompson in wired.com


Here’s my take: pomodoro or nothing

My take on the whole productivity thing? Pomodoro technique. I wrote about it in a this blog in 2017 and I still use it as my primary productivity tool. Any time I have protected time in my schedule, as little as 30 minutes, but better if it is a 2 hours or longer, I break out my Focus Keeper app, a pencil and yellow pad to park distracting ideas, and get down to serious business.

CMIO’s take? Here! Try my app! Here’s my idea, behind my paywall! Kidding. Pomodoro technique guys. Let’s get to work. (ironic – see what I just did there?)

What do sharks have to do with Tesla (valves)?

from wired.com


I only know Nikola Tesla from his competition with Edison over electrification. However, Tesla, like Edison was an inveterate inventor. In this article, scientists recently deconstructed the gastrointestinal system of sharks, and found that they resemble Tesla valves.

What is that, you say? It has nothing to do with anything you think you know about Tesla. And it is a fascinating read. Here is a taste (video) of a Tesla valve system, illustrated with flames.

CMIO’s take? Super cool! But, what does this have to do with informatics, you say? I leave that for you to puzzle out. 🙂