Anne Fleur van Veenstra

Director of Science Strategic Analysis & Policy, TNO

Dr. Anne Fleur van Veenstra is Director of Science of TNO Strategic Analysis & Policy. She has over fifteen years of experience as a researcher of ICT policy and public sector digitalisation, covering topics such as data-driven policy making, smart cities, and responsible data science and artificial intelligence (AI). She set up TNO’s Policy Lab, conducting experiments with municipalities on the use of data analytics, for societal issues such as the energy transition and social policy. Other recent research projects include the use of algorithm in the public sector, and an exploration of public values and practices of responsible data science. Anne Fleur was a visiting researcher at Linköping University in Sweden from 2013 to 2015. Between 2007 and 2012 she worked as a researcher of digital government at the faculty of Technology, Policy and Management of Delft University of Technology, where she also wrote her PhD thesis on ‘IT-induced public sector transformation’.

Anne is speaking at

Focus Track 4 - New challenges ahead: Data, AI and the new Society
November 5, 2020
12:00 pm - 1:30 pm



Recently the EC has issued a consultation in which the need for AI regulation played an important role.  There were 1200 contributions, so 50% more than the Data Strategy consultation. Some 350 companies (the same as data sharing), 400 from citizens (!), and 150 from research institutions. So, AI is really something that keeps citizens busy! Like with data sharing, everybody agrees that the EU should ‘do more’. However, there are highlights. Skills is found very important (89%) to address, also testing facilities (76%) and European Data spaces (75%), Improving existing networks on AI found much support (86%) but a lighthouse research center much less (64%). The section on the risks of AI has been very well addressed by the respondents. This is clearly a concern with many people.
However, the way forward (introduce new regulation, adapt current legislation) is not decided, and there was even less agreement on the identification of high-risk AI applications, how to define them and what to do with them.
The debate on how to move forward with AI applications in terms of requirements, risk, and labelling/certification is clearly still open. In this session we aim to continue the debate and bring it a step further.
The session aims to probe further into the topic ‘AI regulation’ and provide the audience with insights and directions that help them to further shape this EU-wide debate. Specifically, since many of these topics are expected to play a role in the forthcoming Work Programs, the session will create additional links between researchers and practitioners from different backgrounds.
Further description:
The speakers / panelists will be proposed the following questions:
  1. is there a need for a regulatory system for AI systems in Europe? What are the advantages and disadvantages of regulating AI systems?
  2. which AI systems should be regulated? Which criteria should be used to define the need for regulation? 
  3. what types of regulation exist and what is considered to be effective?
  4. how can regulation of AI systems be successful? 
  5. how is the certification of AI systems related to data?
  6. what role do ethical considerations play in the regulation of AI systems?

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