Sarah MeiVerified account

To be totally honest, the project itself was tedious. Digitizing slides and attaching their metadata, especially in the days before good open source relational databases existed, was a sloooow process.

The page itself was an image map (remember those?) that was a world map. Clicking on it triggered a cgi-bin program written in C (pointers are terrible, thank you for coming to my ted talk) that translated where you clicked into an approximate lat/long & looked for nearby photos.

This was before automated testing was really a thing, and it was written by students, so...you can perhaps imagine how high-quality it was. But nobody really noticed. It was such new tech that everyone was just REALLY impressed that it actually (occasionally) worked.

So that was pretty neat, but also fiddly & irritating because there were no docs on anything. Summer ended & I went back to my structural engineering classes. Then a few months later the professor who ran the lab forwarded me an email she’d gotten from a colleague in Brazil.

This was the mid-90s, & environmental scientists in Brazil were battling with their government over rainforest deforestation. Loggers were clear-cutting immense columns of rainforest, but in locations so remote that the government was able to deny it was happening at all.

This scientist who wrote to us had used our web page (despite the bugs) to find two photos of the same location in the remote Brazilian rainforest, taken 10 years apart.

The earlier photo was pretty, but unremarkable. The later one, though, showed clear, long scars, like claw marks through the forest, where loggers had clear-cut. So big that they were visible from space.

This scientist had used these two photos - official US government photos, so difficult to dismiss as fakes - to help convince some of the ministers in the government that clear-cutting was actually happening - despite the logging industry’s assurances to the contrary.

That was what hooked me on software - this idea that surfacing information to a wider audience could change the world. I switched majors to computer science and haven’t looked back.

There’s that phrase - “change the world.” That’s how I thought about it at the time.

You might reasonably ask, what’s the real difference between “changing the world” and “making the world better”? Isn’t this just arguing syntax? They can mean the same thing. And yes - they CAN. But they don’t, always.

Ever read one of those new-agey self help books that’s all like, “tell the universe what you want & THE UNIVERSE will manifest it for you”? I read a few at various points in my life & always sorta rolled my eyes at the idea that anything in the universe was looking out for me.

But it turns out that the new agers were largely correct. One significant proponent of manifesting what you want was Dwight D. Eisenhower, who put it this way: “Plans are worthless, but planning is everything.”

In other words - to be successful, you must be very intentional about what you want. Just don’t expect it to actually, uh, manifest the way you expect.

There’s some really cool research backing this up. The most interesting one, for me, dealt with the concept of luck. As it turns out, people are about as lucky as they think they are. And increasing how lucky they think they are ACTUALLY makes them luckier.

The reason for this? Only a small fraction of our motivation for doing things comes from our conscious minds. The rest comes from our subconscious mind - which you can sorta think of as all the things we know, but we aren’t consciously thinking about right now.

Your ideas about ‘who you are’ & ‘what you are here for’ guide hundreds of thousands of microdecisions, even when you aren’t consciously thinking about anything so philosophical. Collectively, the outcome of those microdecisions changes - when your ideas about yourself change.

What all this adds up to is that you need to set the right intentions in order to make the right decisions. And like a djinni who grants you a wish - the more specific you can be, the higher the chance that your microdecisions will add up to what you wanted.