This week I did:
When different becomes usual
I spent a couple of days at our staff summit. We work remotely most of the time but all get together four times a year. This is my third summit, and they are starting feel like less of “different” thing and more like “just something we do”. When something starts to feel normal, maybe it becomes a Chesterton’s fence, something that is always there and doesn’t need constant reinforcement about why. It’s interesting to think about change in this way. Measuring the number of people who go to the summit might be a useful acquisition metric but adoption, actually feeling like it’s a normal part of how we work, that’s a very different thing.
The Technology Charity
I started collecting my thoughts together to write something more in-depth about the idea of a technology charity (like we have technology companies). I believe technology is the third big way of creating change (after individuals and organisations), so it might make an interesting topic for a book.
Interesting post about the enabling factors for different methodologies and ways of working. This is something I’m hundred percent about. It’s too easy to make changes to the ways work is done without understanding the environment they exist in, which has such an impact on how well those changes work.
How to work hard
This paper maps conscientiousness, from the big five personality test, to intentional goal setting. It’s really interesting to look at some of the academic thinking behind goal setting. Basically, what it’s saying is that people who work hard are more likely to achieve their goals.
Digital for charities
Exploring some of the key areas that charity leaders and teams need to think about in harnessing technology for social impact, the Charity Impact podcast talks to Ross McCulloch.
I thought about:
Had a couple of discussions about designing/decision-making for now and for the future, for things like skills, capacity and roles. What’s needed now seems obvious, and uses inductive reason to figure out all those things that are true now. But what might be needed in the future is really hard to predict as it has to use deductive reasoning that starts with the big picture that no one can see.
GPTs on the hype cycle
GPTs are only one part of LLMs, which are only one type of AI, but they are getting all the attention at the moment. As with all tech (and everything else in existence), there are pluses and minuses, but it’s interesting to see people’s reaction. Much like NFTs were/are one small aspect of crypto, which is only one part of distributed ledger technologies, there was a peak to the hype, and then a descent into the trough of disillusionment. Perhaps all emerging consumer tech has to go through these moments before more reliable, long-term applications can be created.