Below you can find the first in a series of blogs that aim to clarify and show current key debates concerning the regulatory landscape around (big) data and data for AI. In this BDVe blog series, we ask key thinkers to reflect on a set of questions regarding main challenges, drivers, barriers and solutions that act upon the Digital Single Market. We will publish on a regular basis in the coming months – we hope you will enjoy!

Policy conundrums explained

A series of insights on data regulation in Europe

The Big Data Challenge: 3 takeaways for SMEs and startups on Data Sharing

This raises a number of questions, most notably concerning how to collect and get access to trustworthy, valid and reliable data? How can companies and governments align data from different sources.

Turn that frown upside down – Emotional AI and Regulation

The discussions around the concept of emotional AI is relatively fresh in comparison to more standardised forms of AI we’re traditionally exposed to within the field of regulation and policymaking.

Developing sustainable and responsible data science – A plan for the future in data regulation?

The concept of data regulation is an ever-evolving field, in which scholars are continually debating how the law which regulates this use of data can be moved forward in a realistic and progressive manner.

The Big Data Challenge – Insights by Onyx Insights into the Wind Turbine Industry

The impact of data driven innovations on our society and economy is highly dependent on the framework conditions that are set by the regulator. So far, our blogs have provided a bird’s-eye view on the regulatory landscape from legal scholars. Therefore, to get a more accurate picture, this blog will provide insights on the challenges and recommendations for the big data landscape stemming from a commercial context.

The Big Data Challenge – Shaping AI: Recommendations By Virginia Dignum

So far, we have been discussing the policy framework for Big Data. Data is the fuel for AI and we need a solid data framework, because otherwise the uptake of AI will not be successful. AI has received a lot of attention, mainly focusing on the risks it brings about. In this blog we go beyond these aspects of AI by looking at the benefits of AI and how to mitigate these risks.

The Big Data Challenge – Recommendations by Mercè Crosas

Mercè Crosas is University Research Data Officer at Harvard University and Chief Data Science and Technology Officer at the Institute for Quantitative Social Science.

Spill-overs in data governance: the GDPR’s right to data portability and EU sector-specific data access regimes

Analysing the relationship of these sector-specific regimes with the GDPR’s RtDP that applies horizontally to the entire economy.

Big Data Value PPP: Policy4Data Policy Brief

This policy brief reflects current developments within the several Big Data research projects funded under H2020 and, combined with insights from the BDV PPP summit in Riga 1, aims to contribute to ongoing challenges in Europe around the regulation of big data. This policy brief is a product of the Common Dissemination Booster, funded under H2020. The policy recommendations are based on projects participating in the CDB services.