Humans vs. Machines
At first glance, “The Cultural Functions of Computation” incited feelings of panic as Golumbia threw out Derrida, Kant and Descartes. It reminded me of my freshman philosphy course with a nervous TA and all-nighters before terrifying exams.
Panic subsided, however, when Golumbia began discussing the inherent disconnect between human thought and language, and that of computers. Golumbia argues that computers will never have the depth of language that humans have as “we are material beings embedded in the physical and historical contexts of our experience.” Computers learn their languages from handed down programs, with rigid rules and regulations, whereas humans are messy and able to break from rules and commands.
Golumbia adds, “Human nature is highly malleable…analog in nature. They are gradable and fuzzy; they are rarely if ever exact, even if they can achieve exactness.” This strikes me as a comfort. As computers and other computing machines become sleeker, smarter, sexier, the attempts to improve all seem to adapt to work with human intuition. Google tailers its results to fit your needs because Google knows you. Siri knows you, and probably loves you. It’s unsettling.
This idea is mirrored by “No, big data will not mirror the human brain — no matter how advanced our tech gets” by Christian Madsbjerg & Mikkel Krenchel on VentureBeat.
Madsbjerg and Krenchel argue that computers and big data will never perfectly mimic human thought because it limits technology, and it limits the complexity of the human brain. They argue against the idea that soon computers will overpower the human brain, erasing all need for theory and human strategists. Golumbia’s idea that computers will never be able to have the same depth of thought or character as humans is once again brought to the forefont, “while computers excel at following rules, we as humans are at our best exactly when we break the rules. We have the unique ability to empathize and inhabit the experience of other minds, and can reinterpret, reframe, and redefine what was to create amazing things.”
In terms of big data, Madsbjerg and Krenchel point out, “big data allows us to sort, categorize, and compute quantities of static or dynamic data much greater than any person would ever be able to comprehend. But when it comes to making sense of that analysis and figuring out what organizations or people should actually do, only a human mind will suffice.”
Computers are able to compute far more efficiently than the human mind could, but it is important to acknowledge that computing is not all that needs to be done and for complex thought and questioning, humans will always have their brains.
Furthermore, all of these interesting arguments about our future with computers reminds me of my favorite Radiolab episode, Talking to Machines.