Collective bargaining on digital platforms and data stewardship

Curated on Posted on by Stefaan Verhulst

Paper by Astha Kapoor: “… there is a need to think of exploitation on platforms not only through the lens of labour rights but also that of data rights. In the current context, it is impossible to imagine well-being without more agency on the way data are collected, stored and used. It is imperative to envision structures through which worker communities and representatives can be more involved in determining their own data lives on platforms. There is a need to organize and mobilize workers on data rights.

One of the ways in which this can be done is through a mechanism of community data stewards who represent the needs and interests of workers to their platforms, thus negotiating and navigating the data-based decisions. This paper examines the need for data rights as a critical requirement for worker well-being in the platform economy and the ways in which it can be actualized. It argues, given that workers on platforms produce data through collective labour on and off the platform, that worker data are a community resource and should be governed by representatives of workers who can negotiate with platforms on the use of that data for workers and for the public interest. The paper analyses the opportunity for a community data steward mechanism that represents workers’ interests and intermediates on data issues, such as transparency and accountability, with offline support systems. And is also a voice to online action to address some of the injustices of the data economy. Thus, a data steward is a tool through which workers better control their data—consent, privacy and rights—better and organize online. Essentially, it is a way forward for workers to mobilize collective bargaining on data rights.

The paper covers the impact of the COVID-19 pandemic on workers’ rights and well-being. It explores the idea of community data rights on the platform economy and why collective bargaining on data is imperative for any kind of meaningful negotiation with technology companies. The role of a community data steward in reclaiming workers’ power in the platform economy is explained, concluding with policy recommendations for a community data steward structure in the Indian context….(More)”.

Public-Private Partnerships: Compound and Data Sharing in Drug Discovery and Development

Curated on Posted on by Stefaan Verhulst

Paper by Andrew M. Davis et al: “Collaborative efforts between public and private entities such as academic institutions, governments, and pharmaceutical companies form an integral part of scientific research, and notable instances of such initiatives have been created within the life science community. Several examples of alliances exist with the broad goal of collaborating toward scientific advancement and improved public welfare. Such collaborations can be essential in catalyzing breaking areas of science within high-risk or global public health strategies that may have otherwise not progressed. A common term used to describe these alliances is public-private partnership (PPP). This review discusses different aspects of such partnerships in drug discovery/development and provides example applications as well as successful case studies. Specific areas that are covered include PPPs for sharing compounds at various phases of the drug discovery process—from compound collections for hit identification to sharing clinical candidates. Instances of PPPs to support better data integration and build better machine learning models are also discussed. The review also provides examples of PPPs that address the gap in knowledge or resources among involved parties and advance drug discovery, especially in disease areas with unfulfilled and/or social needs, like neurological disorders, cancer, and neglected and rare diseases….(More)”.

Time to evaluate COVID-19 contact-tracing apps

Curated on Posted on by Stefaan Verhulst

Letter to the Editor of Nature by Vittoria Colizza et al: “Digital contact tracing is a public-health intervention. Real-time monitoring and evaluation of the effectiveness of app-based contact tracing is key for improvement and public trust.

SARS-CoV-2 is likely to become endemic in many parts of the world, and there is still no certainty about how quickly vaccination will become available or how long its protection will last. For the foreseeable future, most countries will rely on a combination of various measures, including vaccination, social distancing, mask wearing and contact tracing.

Digital contact tracing via smartphone apps was established as a new public-health intervention in many countries in 2020. Most of these apps are now at a stage at which they need to be evaluated as public-health tools. We present here five key epidemiological and public-health requirements for COVID-19 contact-tracing apps and their evaluation.

1. Integration with local health policy. App notifications should be consistent with local health policies. The app should be integrated into access to testing, medical care and advice on isolation, and should work in conjunction with conventional contact tracing where available1. Apps should be interoperable across countries, as envisaged by the European Commission’s eHealth Network.

2. High user uptake and adherence. Contact-tracing apps can reduce transmission at low levels of uptake, including for those without smartphones2. However, large numbers of users increase effectiveness3,4. An effective communication strategy that explains the apps’ role and addresses privacy concerns is essential for increasing adoption5. Design, implementation and deployment should make the apps accessible to harder-to-reach communities. Adherence to quarantine should be encouraged and supported.

3. Quarantine infectious people as accurately as possible. The purpose of contact tracing is to quarantine as many potentially infectious people as possible, but to minimize the time spent in quarantine by uninfected people. To achieve optimal performance, apps’ algorithms must be ‘tunable’, to adjust to the epidemic as it evolves6.

4. Rapid notification. The time between the onset of symptoms in an index case and the quarantine of their contacts is of key importance in COVID-19 contact tracing7,8. Where a design feature introduces a delay, it needs to be outweighed by gains in, for example, specificity, uptake or adherence. If the delays exceed the period during which most contacts transmit the disease, the app will fail to reduce transmission.

5. Ability to evaluate effectiveness transparently. The public must be provided with evidence that notifications are based on the best available data. The tracing algorithm should therefore be transparent, auditable, under oversight and subject to review. Aggregated data (not linked to individual people) are essential for evaluation of and improvement in the performance of the app. Data on local uptake at a sufficiently coarse-grained spatial resolution are equally key. As apps in Europe do not ‘geolocate’ people, this additional information can be provided by the user or through surveys. Real-time monitoring should be performed whenever possible….(More)”.

AI Ethics Needs Good Data

Curated on Posted on by Stefaan Verhulst

Paper by Angela Daly, S Kate Devitt, and Monique Mann: “In this chapter we argue that discourses on AI must transcend the language of ‘ethics’ and engage with power and political economy in order to constitute ‘Good Data’. In particular, we must move beyond the depoliticised language of ‘ethics’ currently deployed (Wagner 2018) in determining whether AI is ‘good’ given the limitations of ethics as a frame through which AI issues can be viewed. In order to circumvent these limits, we use instead the language and conceptualisation of ‘Good Data’, as a more expansive term to elucidate the values, rights and interests at stake when it comes to AI’s development and deployment, as well as that of other digital technologies.

Good Data considerations move beyond recurring themes of data protection/privacy and the FAT (fairness, transparency and accountability) movement to include explicit political economy critiques of power. Instead of yet more ethics principles (that tend to say the same or similar things anyway), we offer four ‘pillars’ on which Good Data AI can be built: community, rights, usability and politics. Overall we view AI’s ‘goodness’ as an explicly political (economy) question of power and one which is always related to the degree which AI is created and used to increase the wellbeing of society and especially to increase the power of the most marginalized and disenfranchised. We offer recommendations and remedies towards implementing ‘better’ approaches towards AI. Our strategies enable a different (but complementary) kind of evaluation of AI as part of the broader socio-technical systems in which AI is built and deployed….(More)”.

A new intelligence paradigm: how the emerging use of technology can achieve sustainable development (if done responsibly)

Curated on Posted on by Stefaan Verhulst

Peter Addo and Stefaan G. Verhulst in The Conversation: “….This month, the GovLab and the French Development Agency (AFD) released a report looking at precisely these possibilities. “Emerging Uses of Technology for Development: A New Intelligence Paradigm” examines how development practitioners are experimenting with emerging forms of technology to advance development goals. It considers when practitioners might turn to these tools and provides some recommendations to guide their application.

Broadly, the report concludes that experiments with new technologies in development have produced value and offer opportunities for progress. These technologies – which include data intelligence, artificial intelligence, collective intelligence, and embodied intelligence tools – are associated with different prospective benefits and risks. It is essential they be informed by design principles and practical considerations.

Four intelligences

The report derives its conclusions from an analysis of dozens of projects around Africa, including Senegal, Tanzania, Uganda. Linking practice and theory, this approach allows us to construct a conceptual framework that helps development practitioners allocate resources and make key decisions based on their specific circumstances. We call this framework the “four intelligences” paradigm; it offers a way to make sense of how new and emerging technologies intersect with the development field….(More)” (Full Report).

Author provided, CC BY

Citizen Scientists Are Filling Research Gaps Created by the Pandemic

Curated on Posted on by Stefaan Verhulst

Article by  Theresa Crimmins, Erin Posthumus, and Kathleen Prudic: “The rapid spread of COVID-19 in 2020 disrupted field research and environmental monitoring efforts worldwide. Travel restrictions and social distancing forced scientists to cancel studies or pause their work for months. These limits measurably reduced the accuracy of weather forecasts and created data gaps on issues ranging from bird migration to civil rights in U.S. public schools.

Our work relies on this kind of information to track seasonal events in nature and understand how climate change is affecting them. We also recruit and train citizens for community science – projects that involve amateur or volunteer scientists in scientific research, also known as citizen science. This often involves collecting observations of phenomena such as plants and animals, daily rainfall totals, water quality or asteroids.

Participation in many community science programs has skyrocketed during COVID-19 lockdowns, with some programs reporting record numbers of contributors. We believe these efforts can help to offset data losses from the shutdown of formal monitoring activities….(More)”.

Data Responsibility in Humanitarian Action

Curated on Posted on by Stefaan Verhulst

InterAgency Standing Committee: “Data responsibility in humanitarian action is the safe, ethical and effective management of personal and non-personal data for operational response. It is a critical issue for the humanitarian system to address and the stakes are high. Ensuring we ‘do no harm’ while maximizing the benefits of data requires collective action that extends across all levels of the humanitarian system. Humanitarians must be careful when handling data to avoid placing already vulnerable individuals and communities at further risk. This is especially important in contexts where the urgency of humanitarian needs drives pressure for fast, sometimes untested, data solutions, and the politicization of data can have more extreme consequences for people. 

The implementation of data responsibility in practice is often inconsistent within and across humanitarian response contexts. This is true despite established principles, norms and professional standards regarding respect for the rights of affected populations; the range of resources on data responsibility available in the wider international data community; as well as significant efforts by many humanitarian organizations to develop and update their policies and guidance in this area. However, given that the humanitarian data ecosystem is inherently interconnected, no individual organization can tackle all these challenges alone. 

This system-wide Operational Guidance, which is a first, will ensure concrete steps for data responsibility in all phases of humanitarian action. It is the result of an inclusive and consultative process, involving more than 250 stakeholders from the humanitarian sector. Partners across the system will implement these guidelines in accordance with their respective mandates and the decisions of their governing bodies….(More)”

The Legal Limits of Direct Democracy

Curated on Posted on by Stefaan Verhulst

Book edited by Daniel Moeckli, Anna Forgács, and Henri Ibi: “With the rise of direct-democratic instruments, the relationship between popular sovereignty and the rule of law is set to become one of the defining political issues of our time. This important and timely book provides an in-depth analysis of the limits imposed on referendums and citizens’ initiatives, as well as of systems of reviewing compliance with these limits, in 11 European states.

Chapters explore and lay the scientific basis for answering crucial questions such as ‘Where should the legal limits of direct democracy be drawn?’ and ‘Who should review compliance with these limits?’ Providing a comparative analysis of the different issues in the selected countries, the book draws out key similarities and differences, as well as an assessment of the law and the practice at national levels when judged against the international standards contained in the Venice Commission’s Guidelines on the Holding of Referendums.

Presenting an up-to-date analysis of the relationship between popular sovereignty and the rule of law, The Legal Limits of Direct Democracy will be a key resource for scholars and students in comparative and constitutional law and political science. It will also be beneficial to policy-makers and practitioners in parliaments, governments and election commissions, and experts working for international organisations….(More)”.

Tracking COVID-19 using online search

Curated on Posted on by Stefaan Verhulst

Paper by Vasileios Lampos et al: “Previous research has demonstrated that various properties of infectious diseases can be inferred from online search behaviour. In this work we use time series of online search query frequencies to gain insights about the prevalence of COVID-19 in multiple countries. We first develop unsupervised modelling techniques based on associated symptom categories identified by the United Kingdom’s National Health Service and Public Health England. We then attempt to minimise an expected bias in these signals caused by public interest—as opposed to infections—using the proportion of news media coverage devoted to COVID-19 as a proxy indicator. Our analysis indicates that models based on online searches precede the reported confirmed cases and deaths by 16.7 (10.2–23.2) and 22.1 (17.4–26.9) days, respectively. We also investigate transfer learning techniques for mapping supervised models from countries where the spread of the disease has progressed extensively to countries that are in earlier phases of their respective epidemic curves. Furthermore, we compare time series of online search activity against confirmed COVID-19 cases or deaths jointly across multiple countries, uncovering interesting querying patterns, including the finding that rarer symptoms are better predictors than common ones. Finally, we show that web searches improve the short-term forecasting accuracy of autoregressive models for COVID-19 deaths. Our work provides evidence that online search data can be used to develop complementary public health surveillance methods to help inform the COVID-19 response in conjunction with more established approaches….(More)”.

Politics and Open Science: How the European Open Science Cloud Became Reality (the Untold Story)

Curated on Posted on by Stefaan Verhulst

Jean-Claude Burgelman at Data Intelligence: “This article will document how the European Open Science Cloud (EOSC) emerged as one of the key policy intentions to foster Open Science (OS) in Europe. It will describe some of the typical, non-rational roadblocks on the way to implement EOSC. The article will also argue that the only way Europe can take care of its research data in a way that fits the European specificities fully, is by supporting EOSC.

It is fair to say—note the word FAIR here—that realizing the European Open Science Cloud (EOSC) is now part and parcel of the European Data Science (DS) policy. In particular since EOSC will be from 2021 in the hands of the independent EOSC Association and thus potentially way out of the so-called “Brussels Bubble”.

This article will document the whole story of how EOSC emerged in this “bubble” as one of the policy intentions to foster Open Science (OS) in Europe. In addition, it will describe some of the typical, non-rational roadblocks on the way to implement EOSC. The article will also argue that the only way Europe can take care of its research data in a way that fits the European specificities fully, is by supporting EOSC….(More)”