“I Predict A Riot”: Thoughts on Collective Intelligence
Posted by Brian Kelly on 29 September 2011
Technology Outlook: UK Higher Education
The New Media Horizon’s “Technology Outlook: UK Higher Education” report, which was commissioned by UKOLN and CETIS, explores the impact of emerging technologies on teaching, learning, research or information management in UK tertiary education over the next five years. As described in a recent post on What’s On The Technology Horizon? Implications for Librarians I’ll be summarising the technologies featured in the report which I feel will have particular relevance to those working in Libraries at the forthcoming Internet Librarian International (ILI 2011) conference.
The report highlights ‘Collective Intelligence‘ as one emerging technology which is predicted to have an time-to-adoption horizon of 4-5 years. But what exactly is ‘collective intelligence’ and what impact might it have on those working in libraries?
Collective intelligence is defined in Wikipedia as “a shared or group intelligence that emerges from the collaboration and competition of many individuals and appears in consensus decision making in bacteria, animals, humans and computer networks“. The article uses the delicious.com social bookmarking service as an example of collective intelligence :
Recent research using data from the social bookmarking website Del.icio.us, has shown that collaborative tagging systems exhibit a form of complex systems (or self-organizing) dynamics. Although there is no central controlled vocabulary to constrain the actions of individual users, the distributions of tags that describe different resources has been shown to converge over time to a stable power law distributions. Once such stable distributions form, examining the correlations between different tags can be used to construct simple folksonomy graphs, which can be efficiently partitioned to obtained a form of community or shared vocabularies. Such vocabularies can be seen as a form of collective intelligence, emerging from the decentralised actions of a community of users.
Other examples of ways of the relevance of social media in providing collective intelligence might include:
Predicting flu epidemics by observing search terms in Google: Back in 2008 an article published in the Guardian entitled “Google predicts spread of flu using huge search data” described how “Google Flu Trends takes the general search tracking technology pioneered by Google Trends and applies it specifically to influenza. The firm’s engineers claim to have devised a way of analysing millions of individual searches related to the disease that in tests proved to correlate closely with the actual incidence of illness.“. A Google Scholar search for “predicting flu epidemics using google“
Predicting earthquakes using Twitter: An article entitled “Twitter can predict earthquakes, typhoons and rainbows too..” described an “academic paper introduced by Takeshi Sakaki, Makoto Okazaki and Yutaka Matsuo from the University of Tokyo [which] investigates the real-time interaction of events such as earthquakes in Twitter and proposes an algorithm to monitor tweets and to detect a target event“.
Predicting social unrest in the Middle East using social media: An article on “The Social Media Revolution” described how “the CIA has been criticized for not being ‘followers’ on Facebook and Twitter and therefore failing to capitalize on the information those sites could have provided in predicting the recent turmoil“.
“We Predict A Riot”
These examples illustrate how social media can be used for predictions. But predictions usually aren’t provided in isolation: rather predictions are used to identify appropriate actions which may need to be taken. In the first example we might example doctors to ensure that they stock up on medical supplies and, if a particularly severe flu epidemic is predicted, the NHS may decide to fund a marketing campaign aimed at sectors of the population most at risk. The second example could also result in government action such as as mobilising emergency forces which could help to save lives. The third example, however, could result in less benign interventions.
The Kaiser Chiefs sang “I predict a riot” but as suggested in a blog post which hosted the accompanying carton it might now be the crowds which are now predicting upheavals, whether geo-physical or social.
This move to collective intelligence might seem to challenge notions of centralisation and authority and thus, returning to the talk I’ll be giving at the ILI 2011 conference, be challenging to the traditional roles of libraries.
But these examples also highlight both the potential benefits and risks associated with trends which may be predicted through large scale use of social media. As has been highlighted in recent posts about privacy concerns related for Facebook users such issues are very relevant for mainstream users of social media today. (And yesterday’s announcement about the new range of Amazon Kindle devices and the Amazon Silk browser have raised additional privacy concerns).
Facebook’s analysis of users’ attention data can be clearly financially beneficial to Facebook in providing targetted advertising (which may also be beneficial for the end user) and of concern to users when information thought to be private is made available to others in unexpected ways (which tends to be the current focus of user education of the risks of use of social media). But rather than the obvious embarrassing photos which people may be worried about, might it be the less obvious activities which may have the more significant impact in the future?
If I update my status saying I’ll be celebrating with a few pints of Deuchars IPA if England beat Scotland in the Rugby World Cup game on Saturday (while I am in Glasgow) this might be used to suggest that myself and others in my demographic like real ale and use this for targetting adverts (which might help me discover a Scottish real ale which I am unfamiliar with).
If I update my status saying I’m getting a sore throat this might help in providing signals of the flu (and could be more significant in terms of instigating change than my wasted vote in a General Election in Bath).
And if I update my status if I notice possibly illegal activities taking place, am I being helpful to society or could my status update be used by the authorities to justify unnecessary actions? And could a provocative status update (which might be part of a large number of updates which cause people to riot) be therefore treated as incitement? Has the future described in Minority Report (which addresses the theme of “the role of preventative government in protecting its citizenry“) arrived?
Lots of questions, I know. But I also feel that information professionals should have an important role in engaging with the debate. I should also add, as suggested in the post on “The Facebook Chart That Freaks Google Out” and the accompanying chart which is illustrated above, Facebook’s popularity does mean that it is a significant harvester of activity data, since people spend their time on the service and will often have provided their profile information. But if Facebook users migrated overnight to, say, Diaspora would that mean that the benefits of analysis of activity data and content updates could be lost, including the positive benefits? Or might it mean that although users will own their own data, they, understandably, won’t be aware of the possible misuses which could be made of their content updates?
There is a need to address the concerns raised by Facebook’s dominance and their cavalier approaches to privacy – but there’s also a need to look at the wider issues and not assume that any service which provides an alternative to Facebook will necessarily provide benefits across all areas.