Stefaan Verhulst

Blog post by Bill Gates: “My family loves to do jigsaw puzzles. It’s one of our favorite activities to do together, especially when we’re on vacation. There is something so satisfying about everyone working as a team to put down piece after piece until finally the whole thing is done.

In a lot of ways, the fight against Alzheimer’s disease reminds me of doing a puzzle. Your goal is to see the whole picture, so that you can understand the disease well enough to better diagnose and treat it. But in order to see the complete picture, you need to figure out how all of the pieces fit together.

Right now, all over the world, researchers are collecting data about Alzheimer’s disease. Some of these scientists are working on drug trials aimed at finding a way to stop the disease’s progression. Others are studying how our brain works, or how it changes as we age. In each case, they’re learning new things about the disease.

But until recently, Alzheimer’s researchers often had to jump through a lot of hoops to share their data—to see if and how the puzzle pieces fit together. There are a few reasons for this. For one thing, there is a lot of confusion about what information you can and can’t share because of patient privacy. Often there weren’t easily available tools and technologies to facilitate broad data-sharing and access. In addition, pharmaceutical companies invest a lot of money into clinical trials, and often they aren’t eager for their competitors to benefit from that investment, especially when the programs are still ongoing.

Unfortunately, this siloed approach to research data hasn’t yielded great results. We have only made incremental progress in therapeutics since the late 1990s. There’s a lot that we still don’t know about Alzheimer’s, including what part of the brain breaks down first and how or when you should intervene. But I’m hopeful that will change soon thanks in part to the Alzheimer’s Disease Data Initiative, or ADDI….(More)“.

Paper by Maria Ralli et al: “The lack of granular and rich descriptive metadata highly affects the discoverability and usability of the digital content stored in museums, libraries and archives, aggregated and served through Europeana, thus often frustrating the user experience offered by these institutions’ portals. In this context, metadata enrichment services through automated analysis and feature extraction along with crowdsourcing annotation services can offer a great opportunity for improving the metadata quality of digital cultural content in a scalable way, while at the same time engaging different user communities and raising awareness about cultural heritage assets. Such an effort is Crowdheritage, an open crowdsourcing platform that aims to employ machine and human intelligence in order to improve the digital cultural content metadata quality….(More)”.

Article by Daria Gritsenko and Matthew Wood: “This article examines how modes of governance are reconfigured as a result of using algorithms in the governance process. We argue that deploying algorithmic systems creates a shift toward a special form of design‐based governance, with power exercised ex ante via choice architectures defined through protocols, requiring lower levels of commitment from governing actors. We use governance of three policy problems – speeding, disinformation, and social sharing – to illustrate what happens when algorithms are deployed to enable coordination in modes of hierarchical governance, self‐governance, and co‐governance. Our analysis shows that algorithms increase efficiency while decreasing the space for governing actors’ discretion. Furthermore, we compare the effects of algorithms in each of these cases and explore sources of convergence and divergence between the governance modes. We suggest design‐based governance modes that rely on algorithmic systems might be re‐conceptualized as algorithmic governance to account for the prevalence of algorithms and the significance of their effects….(More)”.

Paper by A humanoid robot named ‘Sophia’ has sparked controversy since it has been given citizenship and has done media performances all over the world. The company that made the robot, Hanson Robotics, has touted Sophia as the future of artificial intelligence (AI). Robot scientists and philosophers have been more pessimistic about its capabilities, describing Sophia as a sophisticated puppet or chatbot. Looking behind the rhetoric about Sophia’s citizenship and intelligence and going beyond recent discussions on the moral status or legal personhood of AI robots, we analyse the performativity of Sophia from the perspective of what we call ‘political choreography’: drawing on phenomenological approaches to performance-oriented philosophy of technology. This paper proposes to interpret and discuss the world tour of Sophia as a political choreography that boosts the rise of the social robot market, rather than a statement about robot citizenship or artificial intelligence. We argue that the media performances of the Sophia robot were choreographed to advance specific political interests. We illustrate our philosophical discussion with media material of the Sophia performance, which helps us to explore the mechanisms through which the media spectacle functions hand in hand with advancing the economic interests of technology industries and their governmental promotors. Using a phenomenological approach and attending to the movement of robots, we also criticize the notion of ‘embodied intelligence’ used in the context of social robotics and AI. In this way, we put the discussions about the robot’s rights or citizenship in the context of AI politics and economics….(More)”

Paper by Florian Eyert, Florian Irgmaier, and Lena Ulbricht: “In this article, we take forward recent initiatives to assess regulation based on contemporary computer technologies such as big data and artificial intelligence. In order to characterize current phenomena of regulation in the digital age, we build on Karen Yeung’s concept of “algorithmic regulation,” extending it by building bridges to the fields of quantification, classification, and evaluation research, as well as to science and technology studies. This allows us to develop a more fine‐grained conceptual framework that analyzes the three components of algorithmic regulation as representation, direction, and intervention and proposes subdimensions for each. Based on a case study of the algorithmic regulation of Uber drivers, we show the usefulness of the framework for assessing regulation in the digital age and as a starting point for critique and alternative models of algorithmic regulation….(More)”.

Paper by Heather McKay, Sara Haviland, and Suzanne Michael: “There is increasing interest in sharing data across agencies and even between states that was once siloed in separate agencies. Driving this is a need to better understand how people experience education and work, and their pathways through each. A data-sharing approach offers many possible advantages, allowing states to leverage pre-existing data systems to conduct increasingly sophisticated and complete analyses. However, information sharing across state organizations presents a series of complex challenges, one of which is the central role trust plays in building successful data-sharing systems. Trust building between organizations is therefore crucial to ensuring project success.

This brief examines the process of building trust within the context of the development and implementation of the Multistate Longitudinal Data Exchange (MLDE). The brief is based on research and evaluation activities conducted by Rutgers’ Education & Employment Research Center (EERC) over the past five years, which included 40 interviews with state leaders and the Western Interstate Commission for Higher Education (WICHE) staff, observations of user group meetings, surveys, and MLDE document analysis. It is one in a series of MLDE briefs developed by EERC….(More)”.

Paper by Cass R. Sunstein: “Behavioral science is playing an increasing role in public policy, and it is raising new questions about fundamental issues – the role of government, freedom of choice, paternalism, and human welfare. In diverse nations, public officials are using behavioral findings to combat serious problems – poverty, air pollution, highway safety, COVID-19, discrimination, employment, climate change, and occupational health. Exploring theory and practice, this Element attempts to provide one-stop shopping for those who are new to the area and for those who are familiar with it. With reference to nudges, taxes, mandates, and bans, it offers concrete examples of behaviorally informed policies. It also engages the fundamental questions, include the proper analysis of human welfare in light of behavioral findings. It offers a plea for respecting freedom of choice – so long as people’s choices are adequately informed and free from behavioral biases….(More)”.

European Commission Press Release: “The set-up of the European Health Data Space will be an integral part of building a European Health Union, a process launched by the Commission today with a first set of proposals to reinforce preparedness and response during health crisis. This  is also a direct follow up of the Data strategy adopted by the Commission in February this year, where the Commission had already stressed the importance of creating European data spaces, including on health….

In this perspective, as part of the implementation of the Data strategy, a data governance act is set to be presented still this year, which will support the reuse of public sensitive data such as health data. A dedicated legislative proposal on a European health data space is planned for next year, as set out in the 2021 Commission work programme.

As first steps, the following activities starting in 2021 will pave the way for better data-driven health care in Europe:

• The Commission proposes a European Health Data Space in 2021;
• A Joint Action with 22 Member States to propose options on governance, infrastructure, data quality and data solidarity and empowering citizens with regards to secondary health data use in the EU;
• Investments to support the European Health Data Space under the EU4Health programme, as well as common data spaces and digital health related innovation under Horizon Europe and the Digital Europe programmes;
• Engagement with relevant actors to develop targeted Codes of Conduct for secondary health data use;
• A pilot project, to demonstrate the feasibility of cross border analysis for healthcare improvement, regulation and innovation;
• Other EU funding opportunities for digital transformation of health and care will be available for Member States as of 2021 under Recovery and Resilience Facility, European Regional Development Fund, European Social Fund+, InvestEU.

The set of proposals adopted by the Commission today to strengthen the EU’s crisis preparedness and response, taking the first steps towards a European Health Union, also pave the way for the participation of the European Medicines Agency (EMA) and the European Centre for Disease Prevention and Control (ECDC) in the future European Health Data Space infrastructure, along with research institutes, public health bodies, and data permit authorities in the Member States….(More)”.

Q&A with Stefaan G. Verhulst and Andrew Young …” working in collaboration with UNICEF on an initiative called Responsible Data for Children initiative (RD4C) . Its focus is on data – the risks it poses to children, as well as the opportunities it offers.

You have been working with UNICEF on the Responsible Data for Children initiative (RD4C). What is this and why do we need to be talking more about ‘responsible data’?

To date, the relationship between the datafication of everyday life and child welfare has been under-explored, both by researchers in data ethics and those who work to advance the rights of children. This neglect is a lost opportunity, and also poses a risk to children.

Today’s children are the first generation to grow up amid the rapid datafication of virtually every aspect of social, cultural, political and economic life. This alone calls for greater scrutiny of the role played by data. An entire generation is being datafied, often starting before birth. Every year the average child will have more data collected about them in their lifetime than would a similar child born any year prior. Ironically, humanitarian and development organizations working with children are themselves among the key actors contributing to the increased collection of data. These organizations rely on a wide range of technologies, including biometrics, digital identity systems, remote-sensing technologies, mobile and social media messaging apps, and administrative data systems. The data generated by these tools and platforms inevitably includes potentially sensitive PII data (personally identifiable information) and DII data (demographically identifiable information). All of this begs much closer scrutiny, and a more systematic framework to guide how child-related data is collected, stored, and used.

Towards this aim, we have also been working with the Data for Children Collaborative, based in Edinburgh in establishing innovative and ethical practices around the use of data to improve the lives of children worldwide….(More)”.

Daphne Leprince-Ringuet at ZDNet: “A crowdsourcing platform aims to provide better insight into health issues than is currently available….In the age of social media, blogs, and online forums, the most common practice when feeling slightly under the weather has undeniably become to resort to a quick Google search. Unfortunately, when they are not unnecessarily worrying, the answers found on the web are typically inconclusive. That observation is what prompted Israeli entrepreneur Yael Elish to launch StuffThatWorks, an AI-based online platform that collects crowdsourced data about a host of chronic conditions.

The idea being that, unlike Facebook groups or Reddit threads, the information shared by patients is centralized and assessed for quality to readily provide informed data to other users who are enquiring about their own symptoms. Healthline cuts through the confusion with straightforward, expert-reviewed, person-first experiences — all designed to help you make the best decisions. Elish is a former member of the founding team for crowdsourced navigation app Waze, but this time instead of tapping user-generated content to come up with traffic predictions and accident warnings, StuffThatWorks is intended to give users better insights into illness…(More)”.