He pointed out that humans are great at pattern recognition (“intuition is compressed experience”) and are great satisficers (computers are great at optimising), and that humans never read or remember the same word in quite the same way (has anyone told Autonomy this?). I suppose this is the accretion of personal context and experience affecting your own understanding of the word. I remember as a child forming very strong associations with names of people I liked or disliked – if I disliked the person, I thought the name itself was horrible. This is clearly a dangerous process (and one I hope I have grown out of!) but presumably is part of the way people end up with all sorts of irrational prejudices and also explains why “reclaiming” words like “queer” eventually works. If you keep imposing new contexts on a word, those contexts will come to dominate. This factors into taxonomy work, as it explains the intensity people feel about how things should be named, but they won’t all agree. It must also be connected to why language evolves (and how outdated taxonomies start to cause rather than solve problems – like Wittgenstein’s gods becoming devils).
Snowden also talked about the importance of recognising the weak signal, and has developed a research method based on analysing narratives, using a “light touch” categorisation (to preserve fuzzy boundaries) and allowing people to categorise their own stories. He then plots the points collected from the stories to show the “cultural landscape”. If this is done repeatedly, the “landscapes” can be compared to see if anything is changing. He stressed that his methodology required the selection of the right level of detail in the narratives collected, disintermediation (letting people speak in their own words and categorise in their own way within the constraints), and distributed cognition.
I particularly liked his point that when people self-index and self-title they tend to use words that don’t occur in the text, which is a serious problem for semantic analysis algorithms (although I would comment that third party human indexers/editors will use words not in the text too – “aboutness” is a big problem!). He was also very concerned that computer scientists are not taught to see computers as tools for supporting symbiosis with humans, but as black box systems that should operate autonomously. I completely agree – as is probably quite obvious from many of my previous blog posts – get the computers to do the heavy lifting to free up the humans to sort out the anomalies, make the intuitive leaps, and be creative.
UPDATE: Here’s an excellent post on this talk from Open Intelligence.