Fifteen years ago, when Julia and I were living in a studio apartment, she got me a keyboard. It was a used Yamaha P85, and a significant expense for us at the time. I loved it, and unlike the penny whistles, accordion, and stroh violin I was exploring, it had a volume control. Almost immediately our cat knocked a potted plant onto it, and I needed to take it apart to carefully clean it.

Since then, however, I've had no issues, save one: clacky keys. Over time the keys were getting louder, especially the "A" below middle "C". Something had clearly worn out inside. It was an acoustic noise on an electronic instrument—playing live the audience couldn't hear the clacks over the amplified sound—but having odd percussion on "A" wasn't ideal. Still, I applied my normal approach of trying not to care, which saves me lots of time and money, and didn't let it bother me.

Lily has been increasingly fooling around with the piano, which I'm happy to see: this is also how I learned to play. She asked me about the clacks, and when I explained what I thought had gone wrong she asked if we could fix it. I said I was happy to try, and we got to work:

In 2017, after getting laid off from a startup, I spent a while looking into AI risk:

Many people I respect have started to think that AI risk is the most valuable place to focus EA efforts. For example, 80000 Hours ranks it first on their "list of global issues", taking into account "scale, neglectedness, and solvability". On the other hand, I have a lot of friends working in machine learning, and none of them think AI risk is worth working on now. This level of disagreement is very strange, and kind of worrying.

After playing for a dance weekend in South Carolina where casual conversation among non-tech people included earnest speculation over the likelihood that AI gets us all killed, I thought it might be a good time to look back at when this was really speculative.

Summary: I talked to the right people, heard some incredibly prescient ideas, and got the bottom line wrong.

Walking to kindergarten with Nora this morning, I asked if she wanted to practice crossing the street: once she got good enough, she could walk to school on her own. She didn't want to practice today, but she asked if she could walk the final block herself since there were no more crossings. I said sure, hugged her goodbye, and she set off:

In 2005 I bought an accordion on eBay for $38 (plus $42 shipping). It arrived surprisingly in tune, but I made up for that by playing it badly. It sat next to my bed in the Fishbowl, a large triple I shared with David and Lucas sophmore year:

Now that LLMs have made many kinds of coding a matter of saying what you're looking for, many more programs make sense. This weekend it was audio mixing software, customized for my use case (live sound for contra dancing) and hardware (a specific obsolete audio interface).

In 2011 PreSonus released the 1818VSL, an 8-channel audio interface, with low-latency mixing software. I wrote:

All I really need is a box with some amplifying inputs that send tracks from the mic to the laptop and some outputs that let me send mixes back out again. Then any sort of complex eq, compression, or other effects can happen in software on the laptop. So I got one: it's a Presonus AudioBox VSL1818, with eight usable inputs and eight usable outputs.

At the time I did worry about how long I could expect it to be supported:

AI keeps getting more capable. At some point, likely in the next 1-3 years unless we do something to stop it, we get to where AI systems are able to do everything almost anyone can do. This is often described as leading to a world with "no jobs", but I think this tends to confuse more than help.

One sense in which there might be no jobs is that there might be no people. This is a very real concern, [1] and is the primary reason I think we need to slow down or pause AI development, but isn't what I'm trying to talk about here.

Instead, when people say "no jobs", they're usually talking about a future where there are still people but humans are basically never the best way to go from "I have money" to "my problem is solved". The history of automation has had many rounds of taking some kinds of problem and moving it to machines or human-directed machines: almost all ketchup bottles are filled by machines, almost all dirt is moved by human-controlled machines. As long as there were other things that needed doing which humans could do better than machines, though, humans have moved into other lines of work, and the futures envisioned by a 1930 Keynes in Economic Possibilities for our Grandchildren haven't come about. But this is changing fast, as the list of things we can do better than machines rapidly shrinks.