Filter bubbles

In an earlier post I wrote about the importance of understanding the legibility, agency and negotiability of archaeological data as we increasingly depend on online data delivery as the basis for the archaeologies we write and especially as those archaeologies show signs of being partly written by the delivery systems themselves.

A simple illustration of this is the idea of filter bubbles. This term was coined in 2011 by Eli Pariser to describe the way in which search algorithms selectively return results depending on their knowledge of the person who asked the question. It’s an idea previously flagged by, amongst others, Jaron Lanier who wrote about ‘agents of alienation’ in 1995, but it came to the fore through the recognition of the personalisation of Google results and Facebook feeds (and is the counter-selling point of the alternative search engine, DuckDuckGo, for example). So can we see this happening with archaeological data? Perhaps not to the extent described by Pariser, Lanier and others, but still …

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Big Data Analytics

It was only a matter of time before a ‘big data’ company latched onto archaeology for commercial purposes. Reported in a New Scientist article last week (with an unfortunate focus on ‘treasure’), a UK data analytics start-up called Democrata is incorporating archaeological data into a system to allow engineering and construction firms to predict the likelihood of encountering archaeological remains. This, of course, is what local authority archaeologists do, along with environmental impact assessments undertaken by commercial archaeology units. But this isn’t (yet) an argument about a potential threat to archaeological jobs.

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Legibility, agency, and negotiability

There’s a lot of debate in the wider world about digital data – issues of access and privacy, the case of Aaron Swartz and open access to knowledge, the Ed Snowden revelations, and, at the personal level, the way that we all leave data trails behind as we traverse the Internet. Surrendering our personal data is difficult to avoid, even if we forswear Facebook, Google, and their like who build their business models on their ability to capture data about us.

In a recent paper by Richard Mortier et al, (2015), they argue that this new world of data requires a new kind of study of human-data interaction, looking at the implications of the data we generate in all kinds of different ways, knowingly or unknowingly.

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