It’s tough working on a project you can’t share in detail with the people around you. For the DEM project at Elenta, the domain knowledge needed to bring someone up to speed can be (apparently) boring to them (and I, of course, fail to see how this is possible). It also doesn’t make strategic sense to openly discuss the details of everything we’re building at such an early stage of development.
But it’s tough personally. It’s technical and mysterious and consumes a hell of a lot of time, and friends and family are curious about what we’re up to.
It’s also tough for the development itself. When you’re working on something new and untested, soliciting feedback from potential users – especially friends and family whose opinions you trust – is invaluable.
So ultimately, it’s in my best interests to find a way to articulate what we’re doing. It’s a subject I’m sure I’ll return to periodically (hey, sometimes we have problems describing it to ourselves). So far, I’ve realized a few general things about the public relations of this stuff – giving machines a semantic understanding in a way that creates a general :
- People will immediately draw analogies to science fiction. This is, after all, where people have interacted with general AI the most, because
- The analogies drawn are more often to dystopian man-vs.-machine scenarios, rather than instances of benevolent AI. Stuff like Terminator and The Matrix, titles that even the pop-culture-challenged know enough about.
- Limiting how much we anthropomorphize the platform helps. Talking about a system that passes the Turing-test is significantly scarier. Talking about it like a commercial product is better.
- The idea of the system “learning” from multiple sources seems to put people off. They’re less affected if you just call the system “smart” instead. (something about controlled environment)
- People are typically unaware of where “AI” ideas and algorithms are in use around them.
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