Automation is penetrating every industry, but still heavily reliant on human behavior and feedback to make it effective. In this piece, Benedict Evans talks about identifying the point in a workflow where the optimum point of leverage sits for human interaction:
This means that a lot of the system design is around finding the right points of leverage to apply people to an automated system. Do you capture activity thatās already happening? Google began by using the links that already existed. Do you have to stimulate activity in order to capture the value within it? Facebook had to create behaviors before it could use them. Can you apply your own people to some point of extreme leverage? This is Apple Musicās approach, with manually curated playlists matched automatically to tens of millions of users. Or do you have to pay people to do āallā of it?
This is a great account of an extended conversation with computer scientist Alan Kay. Itās amazing how certain brains can be on such a higher level than the rest of us.
For the few computer idealists among us, we are so lucky to have the legacy left to us by Vannevar Bush, J.C.R. Licklider, Douglas Engelbart, Alan Perlis, John McCarthy, Edsger Dijkstra, John Backus, Ivan Sutherland, and Alan Kay. And those are just some of the names I personally know ā I am now ashamed I donāt know more of our history. Itās hard to imagine now because they were so effective, but so much of our worldās computing prosperity today is due to these people. They imagined the computer as a personal device, a communications device, a device to lift off the burden of tedious mental tabulations. Douglas Engelbart imagined a tool that would aid humanity in dealing with the increasingly-complex problems it faces around the world. Weāve only seem a glimpse of that vision, but we need it now more than ever.
So practically, what does this mean for me? Alan also said at lunch that one problem young people make is āhaving goals.ā Itās too early to have goals that āconsume oneās horizons,ā because young people donāt even know what they donāt know. I think this kind of epistemic modesty is a great idea. I can probably benefit from shifting the focus from my overly-specific goals to āmore metaā goals, such as becoming āeducatedā in a broader sense than I previously thought was possible. The more perspectives I can acquire, the better Iāll be at not fooling myself, and the more Iāll be able to appreciate the richness of the world.
Kirk Goldsberryās new book Sprawlball looks fascinating, covering his work on basketball analytics and his famous hexbinned shot charts showing how the game has changed in recent years. But most folks that have followed his ESPN career probably donāt know about his background in geography and mapmaking:
At its heart, āSprawlBallā is a book of maps. Itās a geography book.
During his junior year at Penn State, Goldsberry took an introduction to cartography class on little more than a whim. āI remember the census data and this software [Graphic Information Systems] that basically links databases to maps,ā he said. It was this perfect balance of art and science, and I devoted the next 15 years of my life to it.ā
He switched his major, got a cartography degree and then moved to Washington to make flood maps for the Federal Emergency Management Agency. After a stint working for a software mapping company in Maine, Goldsberry got his masterās and PhD at UC Santa Barbara, focused on the intersection of computer graphics data visualization and cartography.