Q&A: The Data Delusion
The European Union is often called a ‘super-regulator’, especially when it comes to data-protection and privacy rules. Having seen European lawmaking from close by, in all its complexities, I have often considered this qualification an exaggerated one. Yes, the European Union frequently takes the first steps in ensuring principles continue to be protected, even as digitization disrupts. However, the speed with which technology evolves versus the pace of democratic lawmaking leads to perpetual mismatches.
Even the famous, or infamous, General Data Protection Regulation does not meet many essential regulatory needs of the moment. The mainstreaming of Artificial Intelligence in particular, poses new challenges to concepts of the protection of rights and the sustaining of the rule of law. In its White Paper on Artificial Intelligence, as well the Data Strategy, the European Commission references to the common good and the public interest, as well as societal needs as opposed to an emphasis on regulating the digital market. These are welcome steps in acknowledging the depth and scope of technological impact and defining harms not just in economic terms. It remains to be seen how the visions articulated in the White Paper and the Strategy, will translate into concrete legislation.
One proposal to make concrete improvements to legal frameworks, is outlined by Martin Tisné in The Data Delusion. He highlights the need to update legal privacy standards to be more reflective of the harms incurred through collective data analysis, as opposed to individual privacy violations. Martin makes a clear case for addressing the discrepancy between the profit models benefitting from grouped data versus the ability of any individual to prove the harms caused to his or her rights.
The lack of transparency into the inner workings of algorithmic processing of data further hinders the path to much needed accountability of the powerful technology businesses operating growing parts of our information architecture and the data flows they process.
While EU takes the lead in setting values-based standards and rules for the digital layer of our societies and economies, a lot of work remains to be done.
Marietje Schaake: Martin, in your paper you address the gap between the benefits for technology companies through collective data processing, and the harms for society. You point to historic reasons for individual privacy protections in European laws. Do you consider the European Union to be the best positioned to address the legal shortcomings, especially as you point out that some opportunities to do so were missed in the GDPR?
Martin Tisné: Europe is well positioned but perhaps not for the reasons we traditionally think of (strong privacy tradition, empowered regulators). Individual privacy alone is a necessary, but not sufficient foundation stone to build the future of AI regulation. And whilst much is made of European regulators, the GDPR has been hobbled by the lack of funding and capacity of data protection commissioners across Europe. What Europe does have though, is a legal, political and societal tradition of thinking about the public interest, the common good and how this is balanced against individual interests. This is where we should innovate, taking inspiration from environmental legislation such as the Urgenda Climate Case against the Dutch Government which established that the government had a legal duty to prevent dangerous climate change, in the name of the public interest.
And Europe also has a lot to learn from other political and legal cultures. Part of the future of data regulation may come the indigenous data rights movement, with greater emphasis on the societal and group impacts of data, or from the concept of Ubuntu ethics that assigns community and personhood to all people.
Schaake: What scenario do you foresee in 10 years if collective harms are not dealt with in updates of laws?
Tisné: I worry we will see two impacts. The first is a continuation of what we are seeing now: negative impacts of digital technologies on discrimination, voting rights, privacy, consumers. As people become increasingly aware of the problem there will be a corresponding increase in legal challenges. We’re seeing this already for example with the Lloyd class action case against Google for collecting iPhone data. But I worry these will fail to stick and have lasting impact because of the obligation to have these cases turn on one person, or a class of people’s, individual experiences. It is very hard for individuals to seek remedy for collective harms, as opposed to personal privacy invasions. So unless we solve the issue I raise in the paper – the collective impact of AI and automation – these will continue to fuel polarization, discrimination on the basis of age, gender (and many other aspects of our lives) and the further strengthening of populist regimes.
I also worry about the ways in which algorithms will optimize on the basis of seemingly random classifications (e.g. “people who wear blue shirts, get up early on Saturday mornings, and were geo-located in a particular area of town at a particular time”). These may be proxies for protected characteristics (age, gender reassignment, disability, race, religion, sex, marriage, pregnancy/maternity, sexual orientation) and provide grounds for redress. They may also not be and sow the seeds of future discrimination and harms. Authoritarian rulers are likely to take advantage of the seeming invisibility of those data-driven harms to further silence their opponents. How can I protect myself if I don’t know the basis on which I am being discriminated against or targeted?
Schaake: How do you reflect on the difference in speed between technological innovations and democratic lawmaking? Some people imply this will give authoritarian regimes an advantage in setting global standards and rules. What are your thoughts on ensuring democratic governments speed up?
Tisné: Democracies cannot afford to be outpaced by technological innovation and constantly be fighting yesterday’s wars. Our laws have not changed to reflect changes in technology, which extracts value from collective data, and need to catch up. A lot of the problems stem from the fact that in government (as in companies), the people responsible for enforcement are separated from those with the technical understanding. The solution lies in much better translation between technology, policy and the needs of the public.
An innovation and accountability-led government must involve and empower the public in co-creating policies, above and beyond the existing rules that engage individuals (consent forms etc.). In the paper I propose a Public Interest Data Bill that addresses this need: the rules of the digital highway used as a negotiation between the public and regulators, between private data consumers and data generators. Specifically: clear transparency, public participation and realistic sanctions when things go wrong.
This is where democracies should hone their advantage over authoritarian regimes – using such an approach as the basis for setting global standards and best practices (e.g. affected communities providing input into algorithmic impact assessments).
Schaake: The protection of privacy is what sets democratic societies apart from authoritarian ones. How likely is it that we will see an effort between democracies to set legal standards across borders together? Can we overcome the political tensions across the Atlantic, and strengthen democratic alliances globally?
Tisné: I remain a big supporter of international cooperation. I helped found the Open Government Partnership ten years ago, which remains the main forum for 79 countries to develop innovative open government reforms jointly with the public. Its basic principles hold true: involve global south and global north countries with equal representation, bring civil society in jointly with government from the outset, seek out and empower reformers within government (they exist, regardless of who is in power in the given year), and go local to identify exciting innovations.
If we heed those principles we can set legal standards by learning from open data and civic technology reforms in Taiwan, experiments with data trusts in India, legislation to hold algorithms accountable in France; and by identifying and working with the individuals driving those innovations, reformers such as Audrey Tang in Taiwan, Katarzyna Szymielewicz in Poland, and Henri Verdier in France.
These reformers need a home, a base to influence policymakers and technologists, to get those people responsible for enforcement working with those with the technical understanding. The Global Partnership on Artificial Intelligence may be that home but these are early days, it needs to be agile enough to work with the private sector, civil society as well as governments and the international system. I remain hopeful.
Protecting Individual Isn't Enough When the Harm is Collective. A Q&A with Marietje Schaake and Martin Tisne on his new paper The Data Delusion.
