Max Craglia and Henk Scholten
We are not sure when it started to change but whilst in the past governments were the main collectors of data about lands, people, and resources. Now the commercial sector collects vast amounts of real-time data and knows more about society than governments not just at the aggregate level but down to the behaviour, preferences, and real-time location of individuals.
How does this shift in knowledge, and therefore power, among these key actors: the state, the commercial sector, people and machines, affect the governance of human society? How can we shape our futures in an increasingly fast-evolving technological, social, and physical environment? More fundamentally, can we shape our future at all, or are we just passive objects of decisions taken elsewhere?
We started with these questions about four years ago with a small group of enthusiasts in setting up the Digitranscope (*1) project at the Centre for Advanced Studies of the European Commission Joint Research Centre. We have since involved more than 300 colleagues from governments, academia, industry and civil society to try and find some of the answers that we have now published in the Digitranscope Report (*2) on the Governance of Digitally-Transformed Society.
We realised very quickly that in societies that are being quickly transformed by the digital revolution, the questions of governance revolve primarily about data: The governance of data and new forms of governance with data.
Why is this important? Because you will all be familiar with the increasing political and media attention given to Artificial Intelligence (AI), which is seen as a key enabling technology for the future development of societies and nations. Whilst many countries are developing their national strategies to become world-leaders in AI (*3) , controlling the data upon which AI applications and products are developed is just as important as mastering the development of AI algorithms.
Why now? A shift in paradigm: In the past 20 years data publication for reuse, via catalogues and portals, was seen as the end of the process of data collection, analysis and use by the (public sector) data custodian. It was often also perceived as a burden because the organisation publishing the data was not a direct beneficiary of the value subsequently generated by third parties or accrued by society as a whole in terms of greater transparency and accountability. Observing the big data platforms at work it became noticeable that to them data publication was the beginning of the value-creation chain, not the end! In fact, social media platforms and search engines, do not even create the original data, they let the users do so. They then integrate the users’ data, add value through analytics, repackage into products or services, and sell to third parties thus monetizing the added value created. This shift in the datafication paradigm has led to an increasing call for public authorities to also shift from publishing datasets in portals to open access via machine-to-machine Application Protocol Interfaces (APIs) and add value to the data they publish by adding the intelligence via analytics on who uses the data for what purpose (*4) .
From data analytics to digital twins: Digital twins, i.e. digital replicas of living or non-living things, have been used in industry for several decades, largely as an extension of computer-aided design. They allow simulation and testing of artefacts before moving into production. With the vast increase in sensors networks and computer processing digital twins have seen a significant growth in every sector, particularly in the environmental domain and urban management (*5).
This brings an evolution in data handling as depicted in Fig 1 below. As shown, the shift from traditional data processing to big data already required a closer integration of data processing and analytics into a single (virtual) platform. The development of the IoT and edge computing brings analytics and processing already at the level of the sensor collecting the data while the development of digital twins integrates simulation into the data processing and analytics platforms strengthening the move towards dynamic and interactive environments based on data streams and feedbacks-loops (*6).
So, technology and policy environments are changing rapidly posing challenges for the governance of society but also offering new opportunities.
On the Governance of data
In the current digital society, the dominant model for the governance of personal data is the one established by a few ‘big tech’ companies that are collecting, aggregating and financially exploiting massive amounts of personal data. Yet, other actors beyond those companies are progressively becoming involved in controlling personal data and producing value from it through different practices. These actors include public bodies (such as local administrations), private entities (comprising of small businesses and start-ups), scientific and civil society organisations, activists, social entrepreneurs, and citizens themselves. We explored some of the models for the governance of data that are emerging from the practices of these actors.
In particular, we identified four key models: data sharing pools; data co-operatives; public data trusts; and personal data sovereignty. The goal of our analysis was to investigate to what extent they support different, more balanced, power-relations and how they redistribute more equitably the value generated from data across society compared to the current practices of ‘big-tech’ corporations.
Our analysis shows that particularly data co-operatives and public data trusts seem to be good models to share more equally the value generated through data analytics to all the parties involved. They are in their infancy, but we see a shift in policy, at least in Europe, to encourage these alternative models of data governance and increase the social value derived from data.
On new forms of governance with data
We ran some experiments to see how we could use digital twins at national and urban level and gaming environments to reach more effectively different audiences. For city administrators and analysts, we leveraged the digital twins of the cities of Amsterdam and Duisburg to develop a city operating system that would integrate the different data flows pertaining to mobility and energy and visualised the real-time analytics and simulations via city dashboards. The experiments allowed to interact with city officials and decision-makers and develop a mutual understanding of what is needed and what is possible. The explorations were successful and there is already a request from both cities for the implementation of the overall system.
In another experiment, we were able to leverage the digital twin of The Netherlands developed by the Vrije Universiteit of Amsterdam, Geodan, the Dutch Cadastre and the Dutch Ministry of Infrastructure and Water using Minecraft™ to raise the awareness through gaming of young adults in two schools in Amsterdam and Warsaw on the trade-offs needed in the energy transition. Moreover, we were able to contribute to a big event in the stadium of the Ajax football team in Amsterdam where 500 kids used the digital twin of their city to design a new sustainable neighborhood. In that occasion, the UN Environment Program (UNEP) signed a partnership agreement with the Dutch EduGIS Foundation. Under the agreement, geospatial data tools will allow the game to map territories around the globe and simulate environmental challenges related to achieving the UN’s Sustainable Development Goals (SDGs).
Last but not least, we used AI, and modelling to explore how governments could design personalised policies targeted to the those who are in greatest need in a similar way to the approach of digital platforms use consumer profiling to develop personalised services. In our case, however, we used synthetic population to avoid using personal data, and applied this technique successfully in the context of the COVID-19 pandemic to model the impact reopening different economic activities after the lock down introduced to limit the spread of the virus.
We started with the fundamental questions: can we shape our future? The answer is a resounding yes! Governments have a key role to play in shaping the regulatory environment, companies have of course a big role as engines of innovation and growth, but all of us, as individuals have a key role too by exercising our rights and becoming empowered citizens of the digital society.
If there is a take-away message from the Digitranscope journey is that the governance of our digitally-transforming society is challenging and complex, full of opportunities and pitfalls, but that ultimately it is up to all of us to shape it, we cannot afford to leave it to others.
In the Digitranscope project we have worked in close cooperation with the colleagues from Geodan. The experiments with synthetic people, energy transition, digital twinning, Ecocraft were all based on this cooperation.
*3 See for example https://knowledge4policy.ec.europa.eu/ai-watch/national-strategies-artificial-intelligence_en for the EU and https://oecd.ai/countries-and-initiatives for a more global perspective.
*4 For an overview of AIs in government see https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/application-programming-interfaces-governments-why-what-and-how
*5 For a survey of digital twins see https://publications.jrc.ec.europa.eu/repository/handle/JRC122457
*6 IoT 2.0 and the INTERNET of TRANSFORMATION (Web of Things and Digital Twins): A multi-facets analysis.