Who Controls Big Data?

“Big Data allows you to see the woods, the trees, and the forest.” I also could have gone with “Big Data.. is it all 0s and 1s.”

The reason — A forest is an apt metaphor for the use of big data. If trees represent individuals and woods groups, the forest could represent a system of dynamic, interconnected communities. Big data can give its users a new view of what was, before, just a bunch of trees.

However, the rise of big data is not without ethical implications. One emerging issue is that of data control: i.e. should data be used to control how the forest grows and evolves? We try to outline what distinguishes big data from previous data collection methods and explores the ethical implications of how these new tools are being used to shape society.

Big data is more than just more data. Rather, it “refers to things one can do at a large scale that cannot be done at a smaller one”, and is characterized by ‘ the ability to access a whole data set rather than relying on a supposedly representative sample’; a preference for more, “messy data” over limited clean data; and a shift away from knowing exactly why something happens and an increased focus on knowing what has happened.

Even without perfect insight, big data can be used to anticipate human behavior with stunning accuracy.

For instance, Uber uses big data to predict where their customers will direct their rides; even without entering a destination (Google Kafka). The opportunity implied by such accuracy is huge. One report estimates big data “will generate $300 billion of value per year in the US healthcare industry, Euro 250 billion of value per year in European public sector administration…and 60 percent increases in net margins across the retail industry”.

But what if Uber could not only predict but could also direct where customers travel? This is the threat of big data; that those who have access to it will exercise disproportionate and inappropriate influence.

This is not just a hypothetical scenario. In 2010, Facebook conducted a secret experiment which manipulated users’ newsfeeds with information on which friends had voted. Since social networks strongly influence behavior, it is speculated that Facebook could intentionally sway election results; for instance, by posting more voting statuses only from users at one end of the political spectrum, encouraging likeminded users to do the same. In other words, Facebook would not just be studying the forest, it would be telling it where to grow. in 2015, Cambridge Analytica Happened and we all know the end to that.

Big Data and Cambridge Analytica

So what do we do with this Big Data problem?

Some have sought to get ahead of potential dilemmas by proposing guidelines use of big data. In 2013, Cate and Mayer-Schoberger proposed that big data should be guided by a set of principles covering collection limitation, data quality, data usage, security safeguards, individual participation, and accountability.

However, if the principles are clear, the path to implementation is not. For instance, a recent McKinsey study mapped organizations with high access to big data against those with high-value potential. Public and non-profit sector organizations had high potential value but relatively low-potential access. All those with high potential access sat in the private sector. This implies that the institutions with the most vested interested in big data are the ones least directly accountable to individual data creators.

The uses of big data cannot be left solely to the private sector or to voluntary codes of conduct. Effective regulation of big data principles requires several prerequisites not yet in place: Citizen demand especially in emerging economies where maximum data lies, where society do not yet recognize this as an issue of yet, informed lawmakers able to navigate a technologically complex field, and ability from all stakeholders to envision creative and effective solutions which address the challenges of big data without limiting its potential opportunities.

“If big data is about seeing the forest; big data / AI regulation is about making sure that forest grows safely and sustainably”.