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Besides Kahnemann’s Fast & Slow book, I’ve also talked about fast and slow innovation. Fast is where you have a specific problem to solve, or product to design, or thing to research, and you do so. Slow is the innovation that happens because you create opportunities for new ideas to flourish: making it safe, keeping the ‘adjacent possible’ open, facilitating creative friction, etc. Similarly, in my writing, I use both marathons and sprints. What do I mean?

So, I tend to have reasonably long time-frames for writing. I now blog once a week, and I tend to queue these up a week or two in advance. My books, of course, when I’m working on them, have deadlines months ahead. Presentations, too, are a form of communication. Overall, I tend to have months between proposals and when I have to deliver them. Occasionally, I’m asked for something on a short time frame, but even that’s several days.

And, in my life, I tend to have time (typically, in the morning) to respond to short term requirements, and also time to nick away at the longer term requirements. I’ve become relatively good at leaving projects open to contribute to them as I can. So, largely, this is the ‘marathon’ life. That is, I take care of details, and then take time to polish off the bigger projects. Which, I acknowledge, is a luxury. The tradeoff is that I haven’t had a secure income for most of the past 2.5 decades ;).

What also happens is that, at some point in my nicking away at a project, it comes together. The picture that’s been gestating finally emerges. Then, I tend to suddenly find myself grinding it out. It could be a chapter, a book, a presentation, or just an article, but ultimately it takes shape. That said, for my most recent tome, an iterative process emerged. I kept sending out the latest version to someone else, and rearranging it based upon their feedback. That is, until I realized that the latest rearrangement felt truly right, and I was done!

This varies, of course. Sometimes I’m asked for something short term, and then I tend to fall back on things I’ve already thought through. This blog, as I’ve mentioned in many ways, forces me to think through things (looking to keep it fed and not repeat myself too much). I don’t mind this, as it still forces me to rearticulate, which often forces me to rethink, which is a good thing! In my reprocessing, I’m not only cementing my understanding, but frequently deepening it!

Overall, however, this cycle of marathons and sprints works. The longer term processing provides the basis for the short-term sprints. As it is, I’m usually as productive as anyone else (possibly more), yet it seems like there’s a lot of time of me just musing. Percolation (fermentation, incubation, pick your metaphor) is a good thing! As a reflection, this strikes me as right. It also strikes me as a prescription: break things up, ensure you have enough time for the big things, and take time to reflect. It works for me! And, I realize, it’s contrary to much of organizational life, which to me says more about organizational life than how you (should) think.

(BTW, in real life, I was always better the longer I had to run; I was usually the slowest person in my phys ed classes in sprints! At least on land…) 

Emotion matters. Yes, largely it’s a cultural construct, as Lisa Feldman Barrett tells us. Still, they can help or hinder learning. When designing games or creating meaningful learning, they matter. But they also affect us in our daily activities.

So, my previous post, on misinformation, is personal. I’ve frustration that family members are buying into some of it. I try to maintain a calm demeanor, but it’s challenging. Still, it’s a battle I’ve not yet given up on. Yet, I’m also not immune to the larger effects of emotion.

What we know, from the Yerkes-Dodson Curve, is that a little bit of arousal (read: emotion) can help, but too much can hurt. What isn’t clear from my conceptual rendering is what amount is the ‘right’ amount of arousal for optimal performance. I’ll suggest that for learning, it’s pretty low, as learning is stressful (another synonym for arousal). And I do suggest we manipulate emotions (which I admit is shorthand for motivation, anxiety, and confidence, which aren’t the regular definition) to successfully achieve learning outcomes.

However, even general functioning gets difficult when things are stressful. When I look at the design of casinos, for instance, (a way to cope with the too many times I have to go to Vegas for conferences), I note that they deliberately have low information, lights, no clocks, as an information-sparse environment. It is deliberate, so that you’re more focused on the enticements. They want you confused because you’re then more vulnerable to predations.

I fear that there’s a bit of this in our culture. For instance, fear sells: more alarmist headlines lead to more engagement. Which is good for the news business, but perhaps bad for us in several ways. For one, there’s a vested interest in focus on the alarming, not the bigger picture. Similarly, twisting stories to get emotional engagement isn’t unknown. That can be entertaining, but when it’s the information we depend on is manipulated, it’s problematic. Reducing support for education similarly reduces the intelligence people can apply to analysis.

I struggled to focus to find a topic this week, and I realize it’s because of the informational turmoil that’s currently in play. So, I thought I’d write about it (for better or worse ;).  Exaggeration of issues for the sake of clicks and sales, I’ll suggest isn’t a good thing. I’m willing to be wrong, but I worry that we’re over-excited. Our emotions are being played on, for purposes that are not completely benign. That’s a worry. That’s what’s worrying me, what about you?

One of the banes of our corporate existence is the existence of myths. (We seem to be immune to conspiracy theories, at least.) I’ve been fighting them in myriad ways, over the years. Approaches include a book, talks, and more. We also need ways to vet new information for veracity. Here are a few steps taken recently for misinformation and the fighting thereof.

First, at the Learning Development Accelerator (LDA), we created a research checklist (warning: members only, but at the free level). This was supposed to be a way to vet claims, starting with the practical, but eventually getting into actually evaluating the research. We don’t necessarily recommend this, by the way. It’s probably better to trust research translators unless you’re really willing to dive into the details. (Translators: folks who’ve demonstrated a reliable ability to both take research and extract the meaningful principles and cut through hype).

Then, Matt Richter, my colleague in the LDA, recommended Alex Edman’s book May Contain Lies. I’ve read it and found it an accessible and thoughtful treatment of analyzing claims and data (recommended). Matt even prompted the LDA to host a ‘meet the author’ with Alex. That’s available to view (may also require free membership).

In it, he reiterated something in the book that I found valuable. He talked about a ‘ladder’ of investigation. Telegraphically, it’s this:

1. Statement is not fact (the statement must be accurate)
2. Fact is not data (the fact must be representative)
3. Data is not evidence (the data must be conclusive)
4. Evidence is not proof (the evidence must be universal)

What is being said here is that there are several steps to evaluate what folks want to tell (sell) you. If someone just quotes a statement, it’s not necessarily valid unless it’s accurate. Someone could make a claim that’s not actually true (as happens). Then, that statement alone is not data, unless the statement is representative of the general tenor of thought. For instance, a few positive anecdotes aren’t necessarily indicative of everyone’s experience. Then, representative quotes actually have to be sufficient against any other explanations for the same outcome. For instance, finding out that people like something may not be indicative of its actual efficacy. Finally, the evidence has to apply in your situation, not just theirs.

He used some examples, for instance books where they draw inferences from a few successful companies, without determining that other companies with the inferred characteristics also succeed. What’s nice is he has boiled down what can be an overwhelming set of rules into a simple framework. Misinformation isn’t diminishing, it even seems to be increasing. There’s increasing needs to separate out bogus claims for legitimate. We need to be rallying around misinformation and the fighting thereof. Here’re some tools. Good luck!