Some of my PhD research has been published in the current issue of the Journal of Open Access to Law, from Cornell University.
“Data protection laws require organisations to be transparent about how they use personal data. This article explores the potential of machine-readable privacy notices to address this transparency challenge. We analyse a large source of open data comprised of semi-structured privacy notifications from hundreds of thousands of organisations in the UK, to investigate the reasons for data collection, the types of personal data collected and from whom, and the types of recipients who have access to the data. We analyse three specific sectors in detail; health, finance, and data brokerage. Finally, we draw recommendations for possible future applications of open data to privacy policies and transparency notices.”
It’s available under open access at the JOAL website (or download the PDF)
A little while ago I wrote a short post for the IAPP on the notion of ‘surprise minimisation’. In summary, I’m not that keen on it;
I’m left struggling to see the point of introducing yet another term in an already jargon-filled debate. Taken at face-value, recommending surprise minimisation seems no better than simply saying “don’t use data in ways people might not like”—if anything, it’s worse because it unhelpfully equates surprise with objection, and vice-versa. The available elaborations of the concept don’t add much either, as they seem to boil down to an ill-defined mixture of existing principles.
Why Surprise Minimisation is a Misguided Principle
Whilst researching open registers of data controllers, I was left with some interesting data on international data transfers which didn’t make it into my main research paper. This formed the basis of a short paper for the 2014 Web Science conference which took place last month.
The paper presents a brief analysis of the destinations of 16,000 personal data transfers from the UK. Each ‘transfer’ represents an arrangement between a data controller in the UK to send data to a country located overseas. Many of these destinations are simply listed by the rather general categories of ‘European Economic Area’ or ‘Worldwide’, so the analysis focuses on just those transfers where specific countries were mentioned.
I found that even when we adjust for the size of their existing UK export market, countries whose data protection regimes are approved as ‘adequate’ by the European Commission had higher rates of data transfers. This indicates that easing legal restrictions on cross-border transfers does indeed positively correlate with a higher number of transfers (although the direction of causation can’t be established). I was asked by the organisers to produce a graphic to illustrate the findings, so I’m sharing that below.