The reason for putting artificial intelligence (AI) and governance together in the first place is due to an intuition I had very early on in 2011 as a student of robotics: that there was no mathematical eureka that would “solve” intelligence, that the problem was simply too big, and that this meant that AI had to be assembled piece-by-painstaking-piece [1] But neither was AI a monolithic engineering project, directed by a technical pharaoh. There were too many people with different ideas, too many scientific and technical unknowns, and too many simultaneous research projects and paradigms. It was not even clear to me that a centralized research program was preferable even if one were possible. I believed that building and training an AI was a coordination problem involving millions of people, and I wanted an architecture to solve—or even to define—that coordination problem [2].
To build that architecture, I needed to go beyond AI (at least, as it is practiced today). In the field of AI, the usual meaning of “architecture” refers to technical architectures—software architectures and languages like Prolog, SOAR, subsumption, and ROS, but also hardware architectures like PCs, mobile phones, GPUs, the Raspberry Pi, and the iRobot Baxter—all of which reduce the cost of building and running interesting programs and robots. These mechanisms provide convenient design and programming abstractions to engineers, and they organize the AI’s task by enacting certain knowledge representations (KR). Neural networks are an architecture in this sense, one with particularly nice properties (e.g. modularity, scalability). Technical architectures also often have the effect of making it easier for one programmer to build on the work of another programmer, e.g. by reducing communication and transaction costs, though that was rarely their explicit purpose. In practice, technical architectures (even so-called hybrid architectures) often siloed researchers within competing languages, platforms, and KRs, making it more difficult for people to work across their separate domains.
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