Thoughts on Big Data for NGOs from the OECD Technology Foresight Forum
The Internet Society recently named TechSoup Global Communications Manager Keisha Taylor as one of two Fellows to participate in the 2012 Organisation of Economic Cooperation and Development (OECD) Technology Foresight Forum held in Paris October 22, 2012. We asked Keisha to tell us more about the Forum and her thoughts on what she learned about what "Big Data" might have for NGOs.
What is the Technology Foresight Forum?
This year the Forum focused on Harnessing data as a new source of growth: Big Data analytics and policies. The OECD enables its 30 member governments to work together, with non-member governments and multiple stakeholders to share experiences and seek solutions to socio-economic problems. Technology Foresight Forums are organised annually to help identify opportunities and challenges for the Internet Economy posed by technical developments. They are a collaborative effort of policy makers from member and non-member governments, business, civil society, and the Internet technical community.
The term "Big Data" is usually described as being characterised by 3 V’s: Velocity, Variety and Volume (in some cases also Value). I liked that the discussions focused around Big Data also characterised it as Smart, Predictive, Recursive, Re-combinatory, Ubiquitous.
What were your 3 main highlights at the Forum?
The first highlight for me had to do with liability for not using Big Data. Interestingly, one thing that stood out was discussion around the future potential for industry, governments and other stakeholders to actually be held accountable for failing to use Big Data in their decision-making. This means that by default they would have to use Big Data when making decisions or be held liable for failure to do so. But then there is also the reverse, liability for using Big Data as there is a lack of accountability and transparency around algorithms being used. Since data analytics is an interpretive process, the identity and the perspective of those gathering the data and doing the analysis will influence the result. However, algorithms are trade secrets, and there is no transparency around their use, which has serious economic and social consequences in the real world.
A second interesting topic I heard about was how Big Data technology and tools have democratised data, which can now be used not only by large corporations, but small companies too. Actually, smaller companies can sometimes find correlations faster, as they can afford to experiment and have less bureaucracy to deal with it. The new data environment requires agility and adaptability; so much so that big companies are also working with smaller companies to help process and understand Big Data. Data intermediaries are now very important.
It is not just internal data that is important however, but external data over which we have little control. This is probably why crowdsourcing initiatives, with all the inherent problems they face, such as reliability and validity etc., will continue to be very important. Also, a lot of our data is held by large corporations and is unavailable not only because of privacy issues, but also because of competitive advantage. This therefore limits the possibilities for combining datasets, which really provides the most insight. In essence, data has become the Internet’s currency.
The third interesting thing for me at the conference had to do with privacy. Reassuringly this was a recurring topic, especially as lots of discussions focused on using Big Data for health. This is a very big policy issue that many governments are grappling with. Some speakers discussed the shifting of the risk/reward ratio, arguing that the acquisition, aggregation, and analysis of data offers enormous shared benefits that overwhelm potential individual harms.
Finding ways to encourage innovation without jeopardizing privacy is a big dilemma. The fact remains that stakeholders want to get their hands on more and more data, but the bigger data gets, the more it becomes mathematically impossible to make the datasets anonymous. Also, what can be inferred about you depends not only on what data you give, but what other data has revealed. There is a large trade in personal data that is largely unknown to the public which includes third parties that have no direct relationship with consumers.
Is there anything you wished you could have heard more about?
It would have been good to hear more about ways to involve citizens in helping to address Big Data challenges. I think each of us is an important stakeholder and should not be left out. After all, we are the source of the data. We can also be active participants in the data collection and analysis process.
Also, there was not much discussion beyond developed countries. Given we live in a global economy where changes in ICT policies in one part of the world affect others and by extension everyone, I think it is also important to have a view on this.
How do these issues relate to NGOs?
NGOs are not only a source of data but also a data intermediary for the public who give data and need to reuse it. It is important for the sector to understand how it is being used because the work we do spans many areas and many interests.
The social sector, like Big Data, is characterised by volume and variety. We have a long way to go to improve sharing and coordination of data efforts and data standards. Unlike Big Data, we are not velocity, and like Big Data we need to demonstrate our value.
There is a lot of work that must still be done on educating NGOs and their public on how they can report and maximise the use of data to their benefit. TechSoup Global is playing a part in helping the social sector understand how it can provide and use data securely.
Much needs to be done to inject the civil society perspective on data and their data as well in the Big Data landscape. Only by doing so will a much more holistic view of what is needed for socio-economic development be realised.