We talk a lot about Human-Computer Symbiosis on this blog – it’s a systems design approach that guides us in our construction of our technology stacks. Given that, we’re always on the lookout for example of HCS systems built by other people.
Here’s an unlikely example: the layout of names in the memorial was made according to ‘meaningful adjacencies’ (as described by Jer Thorp in his blog post, All The Names: Algorithmic Design and the 9/11 Memorial):
The project was to design an algorithm for placement of names on the 9/11 memorial in New York City. In architect Michael Arad‘s vision for the memorial, the names were to be laid according to where people were and who they were with when they died – not alphabetical, nor placed in a grid. Inscribed in bronze parapets, almost three thousand names would stream seamlessly around the memorial pools. Underneath this river of names, though, an arrangement would provide a meaningful framework; one which allows the names of family and friends to exist together. Victims would be linked through what Arad terms ‘meaningful adjacencies’ – connections that would reflect friendships, family bonds, and acts of heroism. through these connections, the memorial becomes a permanent embodiment of not only the many individual victims, but also of the relationships that were part of their lives before those tragic events.
Read on for details on the approach they used and how it embodies HCS architecture (not to mention, a video of their tool in action).
The post goes deep into detail on how they built the information system to model and prototype the layout of the names. In end, they let the computers track the adjacency issues while the humans handled the overall aesthetics of not just the overall memorial, but the details of how the names were laid out:
It would be misleading to say that the layout for the final memorial was produced by an algorithm. Rather, the underlying framework of the arrangement was solved by the algorithm, and humans used that framework to design the final result. This is, I think, a perfect example of something that I’ve believed in for a long time: we should let computers do what computers do best, and let humans do what humans do best. In this case, the computer was able to evaluate millions of possible solutions for the layout, manage a complex relational system, and track a large set of important variables and measurements. Humans, on the other hand, could focus on aesthetic and compositional choices. It would have been very hard (or impossible) for humans to do what the computer did. At the same time, it would have been very difficult to program the computer to handle the tasks that were completed with such dedication and precision by the architects and the memorial team.
Men will set the goals and supply the motivations, of course, at least in the early years. They will formulate hypotheses. They will ask questions. They will think of mechanisms, procedures, and models. They will remember that such-and-such a person did some possibly relevant work on a topic of interest back in 1947, or at any rate shortly after World War II, and they will have an idea in what journals it might have been published. In general, they will make approximate and fallible, but leading, contributions, and they will define criteria and serve as evaluators, judging the contributions of the equipment and guiding the general line of thought.
In addition, men will handle the very-low-probability situations when such situations do actually arise. (In current man-machine systems, that is one of the human operator’s most important functions. The sum of the probabilities of very-low-probability alternatives is often much too large to neglect. ) Men will fill in the gaps, either in the problem solution or in the computer program, when the computer has no mode or routine that is applicable in a particular circumstance.
The information-processing equipment, for its part, will convert hypotheses into testable models and then test the models against data (which the human operator may designate roughly and identify as relevant when the computer presents them for his approval). The equipment will answer questions. It will simulate the mechanisms and models, carry out the procedures, and display the results to the operator. It will transform data, plot graphs (“cutting the cake” in whatever way the human operator specifies, or in several alternative ways if the human operator is not sure what he wants). The equipment will interpolate, extrapolate, and transform. It will convert static equations or logical statements into dynamic models so the human operator can examine their behavior. In general, it will carry out the routinizable, clerical operations that fill the intervals between decisions.