Platform Workers, Data Dominion and Challenges to Work-life Quality

Curated on Posted on by Stefaan Verhulst

Paper by Mabel Choo and Mark Findlay: “Originally this short reflection was intended to explore the relationship between the under-regulated labour environment of gig workers and their appreciation of work-life quality. It was never intended as a comprehensive governance critique of what is variously known as independent, franchised, or autonomous service delivery transactions facilitated through platform providers. Rather it was to represent a suggestive snapshot of how workers in these contested employment contexts viewed the relevance of regulation (or its absence) and the impact that new forms of regulation might offer for work-life quality.

By exploring secondary source commentary on worker experiences and attitudes it became clear that profound information deficits regarding how their personal data was being marketed meant that expecting any detailed appreciation of regulatory need and potentials was unrealistic from such a disempowered workforce. In addition, the more apparent was the practice of the platforms re-using and marketising this data without the knowledge or informed consent of the data subjects (service providers and customers) the more necessary it seemed to factor in this commercialisation when regulatory possibilities are to be considered.

The platform providers have sheltered their clandestine use of worker data (whether it be from pervasive surveillance or transaction histories) behind dubious discourse about disruptive economies, non-employment responsibilities, and the distinction between business and private data. In what follows we endeavor to challenge these disempowering interpretations and assertions, while arguing the case that at the very least data subjects need to know what platforms do with the data they produce and have some say in its re-use. In proposing these basic pre-conditions for labour transactions, we hope that work-life experience can be enhanced. Many of the identified needs for regulation and suggestions as to the form it should take are at this point declaratory in the paper, and as such require more empirical modelling to evaluate their potential influences in bettering work-life quality….(More)”

Treading new ground in household sector innovation research: Scope, emergence, business implications, and diffusion

Curated on Posted on by Stefaan Verhulst

Paper by Jeroen P.J.de Jong et al: “Individual consumers in the household sector increasingly develop products, services and processes, in their discretionary time without payment. Household sector innovation is becoming a pervasive phenomenon, representing a significant share of the innovation activity in any economy. Such innovation emerges from personal needs or self-rewards, and is distinct from and complementary to producer innovations motivated by commercial gains. In this introductory paper to the special issue on household sector innovation, we take stock of emerging research on the topic. We categorize the research into four areas: scope, emergence, implications for business, and diffusion. We develop a conceptual basis for the phenomenon, introduce the articles in the special issue, and show how each article contributes new insights. We end by offering a research agenda for scholars interested in the salient phenomenon of household sector innovation….(More)”.

A growing problem of ‘deepfake geography’: How AI falsifies satellite images

Curated on Posted on by Stefaan Verhulst

Kim Eckart at UW News: “A fire in Central Park seems to appear as a smoke plume and a line of flames in a satellite image. Colorful lights on Diwali night in India, seen from space, seem to show widespread fireworks activity.

Both images exemplify what a new University of Washington-led study calls “location spoofing.” The photos — created by different people, for different purposes — are fake but look like genuine images of real places. And with the more sophisticated AI technologies available today, researchers warn that such “deepfake geography” could become a growing problem.

So, using satellite photos of three cities and drawing upon methods used to manipulate video and audio files, a team of researchers set out to identify new ways of detecting fake satellite photos, warn of the dangers of falsified geospatial data and call for a system of geographic fact-checking.

“This isn’t just Photoshopping things. It’s making data look uncannily realistic,” said Bo Zhao, assistant professor of geography at the UW and lead author of the study, which published April 21 in the journal Cartography and Geographic Information Science. “The techniques are already there. We’re just trying to expose the possibility of using the same techniques, and of the need to develop a coping strategy for it.”

As Zhao and his co-authors point out, fake locations and other inaccuracies have been part of mapmaking since ancient times. That’s due in part to the very nature of translating real-life locations to map form, as no map can capture a place exactly as it is. But some inaccuracies in maps are spoofs created by the mapmakers. The term “paper towns” describes discreetly placed fake cities, mountains, rivers or other features on a map to prevent copyright infringement. On the more lighthearted end of the spectrum, an official Michigan Department of Transportation highway map in the 1970s included the fictional cities of “Beatosu and “Goblu,” a play on “Beat OSU” and “Go Blue,” because the then-head of the department wanted to give a shoutout to his alma mater while protecting the copyright of the map….(More)”.

The EU General Data Protection Regulation: A Commentary/Update of Selected Articles

Curated on Posted on by Stefaan Verhulst

Open Access Book edited by C. Kuner, L.A. Bygrave and C. Docksey et al: ” provides an update for selected articles of the GDPR Commentary published in 2020 by Oxford University Press. It covers developments between the last date of coverage of the Commentary (1 August 2019) and 1 January 2021 (with a few exceptions when later developments are taken into account). Edited by Christopher Kuner, Lee A. Bygrave, Chris Docksey, Laura Drechsler, and Luca Tosoni, it covers 49 articles of the GDPR, and is being made freely accessible with the kind permission of Oxford University Press. It also includes two appendices that cover the same period as the rest of this update: the first deals with judgments of the European courts and some selected judgments of particular importance from national courts, and the second with EDPB papers…(More)”

Experimental Regulations for AI: Sandboxes for Morals and Mores

Curated on Posted on by Stefaan Verhulst

Paper by Sofia Ranchordas: “Recent EU legislative and policy initiatives aim to offer flexible, innovation-friendly, and future-proof regulatory frameworks. Key examples are the EU Coordinated Plan on AI and the recently published EU AI Regulation Proposal which refer to the importance of experimenting with regulatory sandboxes so as to balance innovation in AI against its potential risks. Originally developed in the Fintech sector, regulatory sandboxes create a testbed for a selected number of innovative projects, by waiving otherwise applicable rules, guiding compliance, or customizing enforcement. Despite the burgeoning literature on regulatory sandboxes and the regulation of AI, the legal, methodological, and ethical challenges of regulatory sandboxes have remained understudied. This exploratory article delves into the some of the benefits and intricacies of employing experimental legal instruments in the context of the regulation of AI. This article’s contribution is twofold: first, it contextualizes the adoption of regulatory sandboxes in the broader discussion on experimental approaches to regulation; second, it offers a reflection on the steps ahead for the design and implementation of AI regulatory sandboxes….(More)”.

Can Democracy Safeguard the Future?

Curated on Posted on by Stefaan Verhulst

Book by Graham Smith: “Our democracies repeatedly fail to safeguard the future. From pensions to pandemics, health and social care through to climate, biodiversity and emerging technologies, democracies have been unable to deliver robust policies for the long term.

In this book, Graham Smith asks why. Exploring the drivers of short-termism, he considers ways of reshaping legislatures and constitutions and proposes strengthening independent offices whose overarching goals do not change at every election. More radically, Smith argues that forms of participatory and deliberative politics offer the most effective democratic response to the current political myopia, as well as a powerful means of protecting the interests of generations to come….(More)”.

The Delusions of Crowds: Why People Go Mad in Groups

Curated on Posted on by Stefaan Verhulst

Book by William J. Bernstein: “…Inspired by Charles Mackay’s 19th-century classic Memoirs of Extraordinary Popular Delusions and the Madness of Crowds, Bernstein engages with mass delusion with the same curiosity and passion, but armed with the latest scientific research that explains the biological, evolutionary, and psychosocial roots of human irrationality. Bernstein tells the stories of dramatic religious and financial mania in western society over the last 500 years—from the Anabaptist Madness that afflicted the Low Countries in the 1530s to the dangerous End-Times beliefs that animate ISIS and pervade today’s polarized America; and from the South Sea Bubble to the Enron scandal and dot com bubbles of recent years. Through Bernstein’s supple prose, the participants are as colorful as their motivation, invariably “the desire to improve one’s well-being in this life or the next.”

As revealing about human nature as they are historically significant, Bernstein’s chronicles reveal the huge cost and alarming implications of mass mania: for example, belief in dispensationalist End-Times has over decades profoundly affected U.S. Middle East policy. Bernstein observes that if we can absorb the history and biology of mass delusion, we can recognize it more readily in our own time, and avoid its frequently dire impact….(More)”.

Building on a year of open data: progress and promise

Curated on Posted on by Stefaan Verhulst

Jennifer Yokoyama at Microsoft: “…The biggest takeaway from our work this past year – and the one thing I hope any reader of this post will take away – is that data collaboration is a spectrum. From the presence (or absence) of data to how open that data is to the trust level of the collaboration participants, these factors may necessarily lead to different configurations and different goals, but they can all lead to more open data and innovative insights and discoveries.

Here are a few other lessons we have learned over the last year:

  1. Principles set the foundation for stakeholder collaboration: When we launched the Open Data Campaign, we adopted five principles that guide our contributions and commitments to trusted data collaborations: Open, Usable, Empowering, Secure and Private. These principles underpin our participation, but importantly, organizations can build on them to establish responsible ways to share and collaborate around their data. The London Data Commission, for example, established a set of data sharing principles for public- and private-sector organizations to ensure alignment and to guide the participating groups in how they share data.
  2. There is value in pilot projects: Traditionally, data collaborations with several stakeholders require time – often including a long runway for building the collaboration, plus the time needed to execute on the project and learn from it. However, our learnings show short-term projects that experiment and test data collaborations can provide valuable insights. The London Data Commission did exactly that with the launch of four short-term pilot projects. Due to the success of the pilots, the partners are exploring how they can be expanded upon.
  3. Open data doesn’t require new data: Identifying data to share does not always mean it must be newly shared data; sometimes the data was narrowly shared, but can be shared more broadly, made more accessible or analyzed for a different purpose. Microsoft’s environmental indicator data is an example of data that was already disclosed in certain venues, but was then made available to the Linux Foundation’s OS-Climate Initiative to be consumed through analytics, thereby extending its reach and impact…

To get started, we suggest that emerging data collaborations make use of the wealth of existing resources. When embarking on data collaborations, we leveraged many of the definitions, toolkits and guides from leading organizations in this space. As examples, resources such as the Open Data Institute’s Data Ethics Canvas are extremely useful as a framework to develop ethical guidance. Additionally, The GovLab’s Open Data Policy Lab and Executive Course on Data Stewardship, both supported by Microsoft, highlight important case studies, governance considerations and frameworks when sharing data. If you want to learn more about the exciting work our partners are doing, check out the latest posts from the Open Data Institute and GovLab…(More)”. See also Open Data Policy Lab.

Artificial Intelligence in Migration: Its Positive and Negative Implications

Curated on Posted on by Stefaan Verhulst

Article by Priya Dialani: “Research and development in new technologies for migration management are rapidly increasing. To quote certain migration examples, big data was used to predict population movements in the Mediterranean, AI lie detectors used at the European border, and the recent one is the government of Canada using automated decision-making in immigration and refugee applications. Artificial intelligence in migration is helping countries to manage international migration.

Every corner of the world is encountering an unprecedented number of challenging migration crises. As an increasing number of people are interacting with immigration and refugee determination systems, nations are taking a stab at artificial intelligence. AI in global immigration is helping countries to automate a plethora of decisions that are made almost daily as people want to cross borders and look for new homes.

AI projects in migration management can help in predicting the next migration crisis with better accuracy. Artificial intelligence can predict the movements of people migrating by taking into account different types of data such as WiFi positioning, Google Trends, etc. This data can further help the nations and government to be prepared more efficiently for mass migration. Governments can use AI algorithms to examine huge datasets and look for potential gaps in their reception facilities such as the absence of appropriate places for people or vulnerable unaccompanied children.

Recognizing such gaps can allow the government to alter their reception conditions as well as be prepared to comply with their legal obligations under international human rights law (IHRL).

AI applications can also help in changing the lives of asylum seekers and refugees. AI machine learning and optimized algorithms are helping in improving refugee integration. Annie MOORE (Matching Outcome Optimization for Refugee Empowerment) is one such project that matches refugees to communities where they can find the resources and environment as per their preferences and needs.

Asylum seekers or refugees most of the time lack access to lawyers and legal advice. A UK-based chatbot DoNotPay provides free legal advice to asylum seekers using intelligent algorithms. It also provides personalized legal support, which includes help through the UK asylum application process.

AI tech is not just helpful to the government but also to international organisations taking care of international migration. Some organizations are already leveraging machine learning in association with biometric technology. IOM has introduced the Big Data for Migration Alliance project, which intends to use different technologies in international migration….(More)”.

The Rise of Digital Repression: How Technology is Reshaping Power, Politics, and Resistance

Curated on Posted on by Stefaan Verhulst

Book by Steven Feldstein: “The world is undergoing a profound set of digital disruptions that are changing the nature of how governments counter dissent and assert control over their countries. While increasing numbers of people rely primarily or exclusively on online platforms, authoritarian regimes have concurrently developed a formidable array of technological capabilities to constrain and repress their citizens.

In The Rise of Digital Repression, Steven Feldstein documents how the emergence of advanced digital tools bring new dimensions to political repression. Presenting new field research from Thailand, the Philippines, and Ethiopia, he investigates the goals, motivations, and drivers of these digital tactics. Feldstein further highlights how governments pursue digital strategies based on a range of factors: ongoing levels of repression, political leadership, state capacity, and technological development. The international community, he argues, is already seeing glimpses of what the frontiers of repression look like. For instance, Chinese authorities have brought together mass surveillance, censorship, DNA collection, and artificial intelligence to enforce their directives in Xinjiang. As many of these trends go global, Feldstein shows how this has major implications for democracies and civil society activists around the world.

A compelling synthesis of how anti-democratic leaders harness powerful technology to advance their political objectives, The Rise of Digital Repression concludes by laying out innovative ideas and strategies for civil society and opposition movements to respond to the digital autocratic wave….(More)”.