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Stefaan Verhulst

Ben Moscovitch at Pew: “…The Office of the National Coordinator for Health Information Technology (ONC) will collect clinicians’ feedback through a survey developed by the Urban Institute under a contract with the agency. ONC will release aggregated results as part its EHR reporting program. Congress required the program’s creation in the 21st Century Cures Act, the wide-ranging federal health legislation enacted in 2016. The act directs ONC to determine which data to gather from health information technology vendors. That information can then be used to illuminate the strengths and weaknesses of EHR products, as well as industry trends.

The Pew Charitable Trusts, major medical organizations and hospital groups, and health information technology experts have urged that the reporting program examine usability-related patient risks. Confusing, cumbersome, and poorly customized EHR systems can cause health care providers to order the wrong drug or miss test results and other information critical to safe, effective treatment. Usability challenges also can increase providers’ frustration and, in turn, their likelihood of making mistakes.

The data collected from clinicians will shed light on these problems, encourage developers to improve the safety of their products, and help hospitals and doctor’s offices make better-informed decisions about the purchase, implementation, and use of these tools. Research shows that aggregated data about EHRs can generate product-specific insights about safety deficiencies, even when health care facilities implement the same system in distinct ways….(More)”.

Federal Regulators Increase Focus on Patient Risks From Electronic Health Records

Joseph Cox at Vice: “The U.S. military is buying the granular movement data of people around the world, harvested from innocuous-seeming apps, Motherboard has learned. The most popular app among a group Motherboard analyzed connected to this sort of data sale is a Muslim prayer and Quran app that has more than 98 million downloads worldwide. Others include a Muslim dating app, a popular Craigslist app, an app for following storms, and a “level” app that can be used to help, for example, install shelves in a bedroom.

Through public records, interviews with developers, and technical analysis, Motherboard uncovered two separate, parallel data streams that the U.S. military uses, or has used, to obtain location data. One relies on a company called Babel Street, which creates a product called Locate X. U.S. Special Operations Command (USSOCOM), a branch of the military tasked with counterterrorism, counterinsurgency, and special reconnaissance, bought access to Locate X to assist on overseas special forces operations. The other stream is through a company called X-Mode, which obtains location data directly from apps, then sells that data to contractors, and by extension, the military.

The news highlights the opaque location data industry and the fact that the U.S. military, which has infamously used other location data to target drone strikes, is purchasing access to sensitive data. Many of the users of apps involved in the data supply chain are Muslim, which is notable considering that the United States has waged a decades-long war on predominantly Muslim terror groups in the Middle East, and has killed hundreds of thousands of civilians during its military operations in Pakistan, Afghanistan, and Iraq. Motherboard does not know of any specific operations in which this type of app-based location data has been used by the U.S. military.

The apps sending data to X-Mode include Muslim Pro, an app that reminds users when to pray and what direction Mecca is in relation to the user’s current location. The app has been downloaded over 50 million times on Android, according to the Google Play Store, and over 98 million in total across other platforms including iOS, according to Muslim Pro’s website….(More)”.

How the U.S. Military Buys Location Data from Ordinary Apps

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)“.

Data could hold the key to stopping Alzheimer’s

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)”.

CrowdHeritage: Improving the quality of Cultural Heritage through crowdsourcing methods

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)”.

Algorithmic governance: A modes of governance approach

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)”

The political choreography of the Sophia robot: beyond robot rights and citizenship to political performances for the social robotics market

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 representationdirection, 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)”.

Extending the framework of algorithmic regulation. The Uber case

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)”.

Building Trust for Inter-Organizational Data Sharing: The Case of the MLDE

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)”.

Behavioral Science and Public Policy

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)”.

European Health Data Space

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