Tag: businessintelligence

Bookmarked Do we really want to “sell” ourselves? The risks of a property law paradigm for personal data ownership. by Elizabeth Renieris and Dazza Greenwood

Elizabeth Renieris and Dazza Greenwood give different words to my previously expressed concerns about the narrative frame of personal ownership of data and selling it as a tool to counteract the data krakens like Facebook. The key difference is in tying it to different regulatory frameworks, and when each of those comes into play. Property law versus human rights law. [UPDATE in the EU digital data cannot be owned, as it isn’t an object. There may be intellectual property rights to databases (but not to data where it is factual).]

I feel the human rights angle also will serve us better in coming to terms with the geopolitical character of data (and one that the EU is baking into its geopolitical proposition concerning data). In the final paragraph they point to the ‘basic social compact’ that needs explicit support. That I connect to my notion of how so much personal data is also more like communal data, not immediately created or left by me as an individual, but the traces I leave acting in public. At Techfestival Aza Raskin pointed to fiduciary roles for those holding data on those publicly left personal data traces, and Martin von Haller mentioned how those personal data traces also can serve communal purposes and create communal value, placing it in yet another legal setting (that of weighing privacy versus public interest).

…viewing this data as property that is capable of being bought, sold, and owned by others is in large part how we ended up with a broken internet funded by advertising — or the “ad tech model” of the Internet. A property law-based, ownership model of our data risks extending this broken ad tech model of the Internet to all other facets of our digital identity and digital lives expressed through data. While new technology solutions are emerging to address the use of our data online, the threat is not solved with technology alone. Rather, it is time for our attitudes and legal frameworks to catch up. The basic social compact should be explicitly supported and reflected by our business models, legal frameworks and technology architectures, not silently eroded and replaced by them.

Elizabeth Renieris and Dazza Greenwood

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Even though quite a number of companies regard social media as dangerous, I think companies have in fact a lot going for them as a suitable environment for social software.

Because social software tools all work from the same principles:
1 they thrive on large volumes of data and information (Flickr and delicious e.g. only come into their own when the volume involved is big enough)
2 they thrive when existing social networks adopt the same tool (your fraternity in Facebook, Wikipedians doing wiki maintenance, your blog roll)

Social software works well given these conditions because these tools are the internet’s response to the enormous volume of information the internet helped create. Social software is the answer to the internet by the internet.
The quantitative change in information availability (going from scarcity to abundance) leads to qualitative changes in our information strategies. Social filtering is one of those changed information strategies. Social software caters to social filtering.

Companies are excellent environments for social filtering.
Because they sit on large volumes of data and information, going largely unused.
Because organisations are a group of people with shared goals and tasks.

In short, companies are their own objects of sociality as well as their own user group.

An information manager of a large internationally operating Dutch company told me the other day that they had given a number of their professionals access to their business intelligence data. Because they were gathering so much data nobody really looked at for lack of good questions to ask of the dataset. The professionals put the data to good use, because they could formulate the right questions. They were adding social structures and context to the data. Basically adding social software design principles to a large volume of data.

The information manager was surprised by this, saying something like “and I have these BI specialists who never came up with this kind of use for the data”.
I wasn’t surprised. Throwing social relationships at large volumes of data works. We see it in our feed-readers, presence streams, yasn’s, wiki’s, and tag-clouds every day.