Commission proposes measures to boost data sharing and support European data spaces


Press Release: “To better exploit the potential of ever-growing data in a trustworthy European framework, the Commission today proposes new rules on data governance. The Regulation will facilitate data sharing across the EU and between sectors to create wealth for society, increase control and trust of both citizens and companies regarding their data, and offer an alternative European model to data handling practice of major tech platforms.

The amount of data generated by public bodies, businesses and citizens is constantly growing. It is expected to multiply by five between 2018 and 2025. These new rules will allow this data to be harnessed and will pave the way for sectoral European data spaces to benefit society, citizens and companies. In the Commission’s data strategy of February this year, nine such data spaces have been proposed, ranging from industry to energy, and from health to the European Green Deal. They will, for example, contribute to the green transition by improving the management of energy consumption, make delivery of personalised medicine a reality, and facilitate access to public services.

The Regulation includes:

  • A number of measures to increase trust in data sharing, as the lack of trust is currently a major obstacle and results in high costs.
  • Create new EU rules on neutrality to allow novel data intermediaries to function as trustworthy organisers of data sharing.
  • Measures to facilitate the reuse of certain data held by the public sector. For example, the reuse of health data could advance research to find cures for rare or chronic diseases.
  • Means to give Europeans control on the use of the data they generate, by making it easier and safer for companies and individuals to voluntarily make their data available for the wider common good under clear conditions….(More)”.

European Health Data Space


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)”.

NIH Releases New Policy for Data Management and Sharing


NIH Blogpost by Carrie Wolinetz: “Today, nearly twenty years after the publication of the Final NIH Statement on Sharing Research Data in 2003, we have released a Final NIH Policy for Data Management and Sharing. This represents the agency’s continued commitment to share and make broadly available the results of publicly funded biomedical research. We hope it will be a critical step in moving towards a culture change, in which data management and sharing is seen as integral to the conduct of research. Responsible data management and sharing is good for science; it maximizes availability of data to the best and brightest minds, underlies reproducibility, honors the participation of human participants by ensuring their data is both protected and fully utilized, and provides an element of transparency to ensure public trust and accountability.

This policy has been years in the making and has benefited enormously from feedback and input from stakeholders throughout the process. We are grateful to all those who took the time to comment on Request for Information, the Draft policy, or to participate in workshops or Tribal consultations. That thoughtful feedback has helped shape the Final policy, which we believe strikes a balance between reasonable expectations for data sharing and flexibility to allow for a diversity of data types and circumstances. How we incorporated public comments and decision points that led to the Final policy are detailed in the Preamble to the DMS policy.

The Final policy applies to all research funded or conducted by NIH that results in the generation of scientific data. The Final Policy has two main requirements (1) the submission of a Data Management and Sharing Plan (Plan); and (2) compliance with the approved Plan. We are asking for Plans at the time of submission of the application, because we believe planning and budgeting for data management and sharing needs to occur hand in hand with planning the research itself. NIH recognizes that science evolves throughout the research process, which is why we have built in the ability to update DMS Plans, but at the end of the day, we are expecting investigators and institutions to be accountable to the Plans they have laid out for themselves….

Anticipating that variation in readiness, and in recognition of the cultural change we are trying to seed, there is a two-year implementation period. This time will be spent developing the information, support, and tools that the biomedical enterprise will need to comply with this new policy. NIH has already provided additional supplementary information – on (1) elements of a data management and sharing plan; (2) allowable costs; and (3) selecting a data repository – in concert with the policy release….(More)”

New mathematical idea reins in AI bias towards making unethical and costly commercial choices


The University of Warwick: “Researchers from the University of Warwick, Imperial College London, EPFL (Lausanne) and Sciteb Ltd have found a mathematical means of helping regulators and business manage and police Artificial Intelligence systems’ biases towards making unethical, and potentially very costly and damaging commercial choices—an ethical eye on AI.

Artificial intelligence (AI) is increasingly deployed in commercial situations. Consider for example using AI to set prices of insurance products to be sold to a particular customer. There are legitimate reasons for setting different prices for different people, but it may also be profitable to ‘game’ their psychology or willingness to shop around.

The AI has a vast number of potential strategies to choose from, but some are unethical and will incur not just moral cost but a significant potential economic penalty as stakeholders will apply some penalty if they find that such a strategy has been used—regulators may levy significant fines of billions of Dollars, Pounds or Euros and customers may boycott you—or both.

So in an environment in which decisions are increasingly made without human intervention, there is therefore a very strong incentive to know under what circumstances AI systems might adopt an unethical strategy and reduce that risk or eliminate entirely if possible.

Mathematicians and statisticians from University of Warwick, Imperial, EPFL and Sciteb Ltd have come together to help business and regulators creating a new “Unethical Optimization Principle” and provide a simple formula to estimate its impact. They have laid out the full details in a paper bearing the name “An unethical optimization principle“, published in Royal Society Open Science on Wednesday 1st July 2020….(More)”.

Techlash? America’s Growing Concern with Major Technology Companies


Press Release: “Just a few years ago, Americans were overwhelmingly optimistic about the power of new technologies to foster an informed and engaged society. More recently, however, that confidence has been challenged by emerging concerns over the role that internet and technology companies — especially social media — now play in our democracy.

A new Knight Foundation and Gallup study explores how much the landscape has shifted. This wide-ranging study confirms that, for Americans, the techlash is real, widespread, and bipartisan. From concerns about the spread of misinformation to election interference and data privacy, we’ve documented the deep pessimism of folks across the political spectrum who believe tech companies have too much power — and that they do more harm than good. 

Despite their shared misgivings, Americans are deeply divided on how best to address these challenges. This report explores the contours of the techlash in the context of the issues currently animating policy debates in Washington and Silicon Valley. Below are the main findings from the executive summary….

  • 77% of Americans say major internet and technology companies like Facebook, Google, Amazon and Apple have too muchpower.
  • Americans are equally divided among those who favor (50%) and oppose (49%) government intervention that would require internet and technology companies to break into smaller companies. 
  • Americans do not trust social media companies much (44%) or at all (40%) to make the right decisions about what content should or should not be allowed on online platforms.
  • However, they would still prefer the companies (55%) to make those decisions rather than the government (44%). …(More)

New privacy-protected Facebook data for independent research on social media’s impact on democracy


Chaya Nayak at Facebook: “In 2018, Facebook began an initiative to support independent academic research on social media’s role in elections and democracy. This first-of-its-kind project seeks to provide researchers access to privacy-preserving data sets in order to support research on these important topics.

Today, we are announcing that we have substantially increased the amount of data we’re providing to 60 academic researchers across 17 labs and 30 universities around the world. This release delivers on the commitment we made in July 2018 to share a data set that enables researchers to study information and misinformation on Facebook, while also ensuring that we protect the privacy of our users.

This new data release supplants data we released in the fall of 2019. That 2019 data set consisted of links that had been shared publicly on Facebook by at least 100 unique Facebook users. It included information about share counts, ratings by Facebook’s third-party fact-checkers, and user reporting on spam, hate speech, and false news associated with those links. We have expanded the data set to now include more than 38 million unique links with new aggregated information to help academic researchers analyze how many people saw these links on Facebook and how they interacted with that content – including views, clicks, shares, likes, and other reactions. We’ve also aggregated these shares by age, gender, country, and month. And, we have expanded the time frame covered by the data from January 2017 – February 2019 to January 2017 – August 2019.

With this data, researchers will be able to understand important aspects of how social media shapes our world. They’ll be able to make progress on the research questions they proposed, such as “how to characterize mainstream and non-mainstream online news sources in social media” and “studying polarization, misinformation, and manipulation across multiple platforms and the larger information ecosystem.”

In addition to the data set of URLs, researchers will continue to have access to CrowdTangle and Facebook’s Ad Library API to augment their analyses. Per the original plan for this project, outside of a limited review to ensure that no confidential or user data is inadvertently released, these researchers will be able to publish their findings without approval from Facebook.

We are sharing this data with researchers while continuing to prioritize the privacy of people who use our services. This new data set, like the data we released before it, is protected by a method known as differential privacy. Researchers have access to data tables from which they can learn about aggregated groups, but where they cannot identify any individual user. As Harvard University’s Privacy Tools project puts it:

“The guarantee of a differentially private algorithm is that its behavior hardly changes when a single individual joins or leaves the dataset — anything the algorithm might output on a database containing some individual’s information is almost as likely to have come from a database without that individual’s information. … This gives a formal guarantee that individual-level information about participants in the database is not leaked.” …(More)”

The wisdom of crowds: What smart cities can learn from a dead ox and live fish


Portland State University: “In 1906, Francis Galton was at a country fair where attendees had the opportunity to guess the weight of a dead ox. Galton took the guesses of 787 fair-goers and found that the average guess was only one pound off of the correct weight — even when individual guesses were off base.

This concept, known as “the wisdom of crowds” or “collective intelligence,” has been applied to many situations over the past century, from people estimating the number of jellybeans in a jar to predicting the winners of major sporting events — often with high rates of success. Whatever the problem, the average answer of the crowd seems to be an accurate solution.

But does this also apply to knowledge about systems, such as ecosystems, health care, or cities? Do we always need in-depth scientific inquiries to describe and manage them — or could we leverage crowds?

This question has fascinated Antonie J. Jetter, associate professor of Engineering and Technology Management for many years. Now, there’s an answer. A recent study, which was co-authored by Jetter and published in Nature Sustainability, shows that diverse crowds of local natural resource stakeholders can collectively produce complex environmental models very similar to those of trained experts.

For this study, about 250 anglers, water guards and board members of German fishing clubs were asked to draw connections showing how ecological relationships influence the pike stock from the perspective of the anglers and how factors like nutrients and fishing pressures help determine the number of pike in a freshwater lake ecosystem. The individuals’ drawings — or their so-called mental models — were then mathematically combined into a collective model representing their averaged understanding of the ecosystem and compared with the best scientific knowledge on the same subject.

The result is astonishing. If you combine the ideas from many individual anglers by averaging their mental models, the final outcomes correspond more or less exactly to the scientific knowledge of pike ecology — local knowledge of stakeholders produces results that are in no way inferior to lengthy and expensive scientific studies….(More)”.

Industry and Public Sector Leaders Partner to Launch the Mobility Data Collaborative


Press Release: “The Mobility Data Collaborative (the Collaborative), a multi-sector forum with the goal of creating a framework to improve mobility through data, launches today…

New mobility services, such as shared cars, bikes, and scooters, are emerging and integrating into the urban transportation landscape across the globe. Data generated by these new mobility services offers an exciting opportunity to inform local policies and infrastructure planning. The Collaborative brings together key members from the public and private sectors to develop best practices to harness the potential of this valuable data to support safe, equitable, and livable streets.

The Collaborative will leverage the knowledge of its current and future members to solve the complex challenges facing shared mobility operators and the public agencies who manage access to infrastructure that these new services require. A critical component of this collaboration is providing an open and impartial forum for sharing information and developing best practices. 

Membership is open to public agencies, nonprofits, academic institutions and private companies….(More)”.

Mayor de Blasio Signs Executive Order to Establish Algorithms Management and Policy Officer


Press release: “Mayor Bill de Blasio today signed an Executive Order to establish an Algorithms Management and Policy Officer within the Mayor’s Office of Operations. The Officer will serve as a centralized resource on algorithm policy and develop guidelines and best practices to assist City agencies in their use of algorithms to make decisions. The new Officer will ensure relevant algorithms used by the City to deliver services promote equity, fairness and accountability. The creation of the position follows review of the recommendations from the Automated Decision Systems (ADS) Task Force Report required by Local Law 49 of 2018, published here.

“Fairness and equity are central to improving the lives of New Yorkers,” said Mayor Bill de Blasio.“With every new technology comes added responsibility, and I look forward to welcoming an Algorithms Management and Policy Officer to my team to ensure the tools we use to make decisions are fair and transparent.”…

The Algorithms Management and Policy Officer will develop guidelines and best practices to assist City agencies in their use of tools or systems that rely on algorithms and related technologies to support decision-making. As part of that effort, the Officer and their personnel support will develop processes for agency reporting and provide resources that will help the public learn more about how New York City government uses algorithms to make decisions and deliver services….(More)”.

Community Colleges Boost STEM Student Success Through Behavioral Nudging


Press Release: “JFF, a national nonprofit driving transformation in the American workforce and education systems, and Persistence Plus, which pairs behavioral insights with intelligent text messaging to improve student success, today released the findings from an analysis that examined the effects of personalized nudging on nearly 10,000 community college students. The study, conducted over two years at four community colleges, found that behavioral nudging had a significant impact on student persistence rates—with strong improvements among students of color and older adult learners, who are often underrepresented among graduates of STEM (science, technology, engineering, and math) programs.

“These results offer powerful evidence on the potential, and imperative, of using technology to support students during the most in-demand, and often most challenging, courses and majors,” said Maria Flynn, president and CEO of JFF. “With millions of STEM jobs going unfilled, closing the gap in STEM achievement has profound economic—and equity—implications.” 

In a multiyear initiative called “Nudging to STEM Success, which was funded by the Helmsley Charitable Trust, JFF and Persistence Plus selected four colleges to implement the nudging initiative campuswide:Lakeland Community College in Kirtland, Ohio; Lorain County Community College in Elyria, Ohio; Stark State College in North Canton, Ohio; and John Tyler Community College in Chester, Virginia.

A randomized control trial in the summer of 2017 showed that the nudges increased first-to-second-year persistence for STEM students by 10 percentage points. The results of that trial will be presented in an upcoming peer-reviewed paper titled “A Summer Nudge Campaign to Motivate Community College STEM Students to Reenroll.” The paper will be published in AERA Open, an open-access journal published by the American Educational Research Association. 

Following the 2017 trial, the four colleges scaled the support to nearly 10,000 students, and over the next two years, JFF and Persistence Plus found that the nudging support had a particularly strong impact on students of color and students over the age of 25—two groups that have historically had lower persistence rates than other students….(More)”.