Stefaan Verhulst
Paper by Arden Rowell: “The nudge – a form of behaviorally-informed regulation that at-tempts to account for people’s scarce cognitive resources – has been explosively successful at colonizing the regulatory state. This Essay argues that the remarkable success of nudges as a species creates new challenges and opportunities for individual nudges that did not exist ten years ago, when nudges were new. These changes follow from the new fact that nudges must now interact with other nudges. This creates opportunities for nudge versus nudge battles, where nudges compete with other nudges for the scarce resource of public cognition; and for nudge & nudge symbiosis, where nudges work complementarily with other nudges to achieve greater good with fewer resources. Because of the potential for positive and negative interactions with other nudges, modern nudges should be expected to operate differently from ancestral nudges in important ways, and future nudges should be expected to operate more differently still. Policymakers should prepare to manage future positive and negative nudge-nudge interactions….(More)”.
and Collaborative-Platforms-as-a-Governance-Strategy?redirectedFrom=fulltextCollaborative governance is increasingly viewed as a proactive policy instrument, one in which the strategy of collaboration can be deployed on a larger scale and extended from one local context to another. This article suggests that the concept of collaborative platforms provides useful insights into this strategy of treating collaborative governance as a generic policy instrument. Building on an organization-theoretic approach, collaborative platforms are defined as organizations or programs with dedicated competences and resources for facilitating the creation, adaptation and success of multiple or ongoing collaborative projects or networks. Working between the theoretical literature on platforms and empirical cases of collaborative platforms, the article finds that strategic intermediation and design rules are important for encouraging the positive feedback effects that help collaborative platforms adapt and succeed. Collaborative platforms often promote the scaling-up of collaborative governance by creating modular collaborative units—a strategy of collaborative franchising….(More)”.
Paper by Amanda Levendowski: “As the use of artificial intelligence (AI) continues to spread, we have seen an increase in examples of AI systems reflecting or exacerbating societal bias, from racist facial recognition to sexist natural language processing. These biases threaten to overshadow AI’s technological gains and potential benefits. While legal and computer science scholars have analyzed many sources of bias, including the unexamined assumptions of its often-homogenous creators, flawed algorithms, and incomplete datasets, the role of the law itself has been largely ignored. Yet just as code and culture play significant roles in how AI agents learn about and act in the world, so too do the laws that govern them. This Article is the first to examine perhaps the most powerful law impacting AI bias: copyright.
Artificial intelligence often learns to “think” by reading, viewing, and listening to copies of human works. This Article first explores the problem of bias through the lens of copyright doctrine, looking at how the law’s exclusion of access to certain copyrighted source materials may create or promote biased AI systems. Copyright law limits bias mitigation techniques, such as testing AI through reverse engineering, algorithmic accountability processes, and competing to convert customers. The rules of copyright law also privilege access to certain works over others, encouraging AI creators to use easily available, legally low-risk sources of data for teaching AI, even when those data are demonstrably biased. Second, it examines how a different part of copyright law — the fair use doctrine — has traditionally been used to address similar concerns in other technological fields, and asks whether it is equally capable of addressing them in the field of AI bias. The Article ultimately concludes that it is, in large part because the normative values embedded within traditional fair use ultimately align with the goals of mitigating AI bias and, quite literally, creating fairer AI systems….(More)”.
Ben Miller at Government Technology: “Hash chains are not a new concept in cryptography. They are, essentially, a long chain of data connected by values called hashes that prove the connection of each part to the next. By stringing all these pieces together and representing them in small values, then, one can represent a large amount of information without doing much. Josh Benaloh, a senior cryptographer for Microsoft Research and director of the International Association for Cryptologic Research, gives the rough analogy of taking a picture of a person, then taking another picture of that person holding the first picture, and so on. Loss of resolution aside, each picture would contain all the images from the previous pictures.
It’s only recently that people have found a way to extend the idea to commonplace applications. That happened with the advent of bitcoin, a digital “cryptocurrency” that has attained real-world value and become a popular exchange medium for ransomware attacks. The bitcoin community operates using a specific type of hash chain called a blockchain. It works by asking a group of users to solve complex problems as a sort of proof that bitcoin transactions took place, in exchange for a reward.
“Academics who have been looking at this for years, when they saw bitcoin, they said, ‘This can’t work, this has too many problems,’” Benaloh said. “It surprised everybody that this seems to work and to hold.”
But the blockchain concept is by no means limited to money. It’s simply a public ledger, a bulletin board meant to ensure accuracy based on the fact that everyone can see it — and what’s been done to it — at all times. It could be used to keep property records, or to provide an audit trail for how a product got from factory to buyer.
Or perhaps it could be used to prove the veracity and accuracy of digital votes in an election.
It is a potential solution to the problem of cybersecurity in online elections because the foundation of blockchain is the audit trail: If anybody tampered with votes, it would be easy to see and prove.
And in fact, blockchain elections have already been run in the U.S. — just not in the big leagues. Voatz, a Massachusetts-based startup that has struck up a partnership with one of the few companies in the country that actually builds voting systems, has used a blockchain paradigm to run elections for colleges, school boards, unions and other nonprofit and quasi-governmental groups. Perhaps its most high-profile endeavor was authenticating delegate badges at the 2016 Massachusetts Democratic Convention….
Rivest and Benaloh both talk about another online voting solution with much more enthusiasm. And much in the spirit of academia, the technology’s name is pragmatic rather than sleek and buzzworthy: end-to-end verifiable Internet voting (E2E-VIV).
It’s not too far off from blockchain in spirit, but it relies on a centralized approach instead of a decentralized one. Votes are sent from remote electronic devices to the election authority, most likely the secretary of state for the state the person is voting in, and posted online in an encrypted format. The person voting can use her decryption key to check that her vote was recorded accurately.
But there are no validating peers, no chain of blocks stretching back to the first vote….(More)”.
Hollie Russon-Gilman and K. Sabeel Rahman at New America Foundation: “For several years now, the institutions of American democracy have been under increasing strain. Widening economic inequality, the persistence and increased virulence of racial and ethnic tensions, and the inability of existing political institutions to manage disputes and solve problems have all contributed to a growing sense of crisis in American democracy. This crisis of democracy extends well beyond immediate questions about elections, voting, and the exercise of political power in Washington. Our democratic challenges are deeper. How do we develop institutions and organizations to enable civic engagement beyond voting every few years? What kinds of institutions, organizations, and practices are needed to make public policies inclusive, equitable, and responsive to the communities they are supposed to serve? How do we create a greater capacity for and commitment to investing in grassroots democracy? How can we do all this while building a multiracial and multiethnic society inclusive of all?
The current political moment creates an opportunity to think more deeply about both the crisis of American democracy today and about the democracy that we want—and how we might get there. Few scholars or practitioners would content themselves with our current democratic institutions. At the same time, generating a more durable, inclusive, and responsive democracy requires being realistic about constraints, limitations, and tensions that will necessarily arise.
In this report we sketch out some of the central challenges and tensions we see, as well as some potential avenues for renewal and transformation. Based on a convening at New America in Washington, D.C. and a series of ongoing conversations with organizers, policymakers, and scholars from around the country, we propose a framework in this report to serve as a resource for continuing these important efforts in pioneering new forms of democratic governance….(More)”.
Nathan Jurgenson in The New Inquiry: “Modernity has long been obsessed with, perhaps even defined by, its epistemic insecurity, its grasping toward big truths that ultimately disappoint as our world grows only less knowable. New knowledge and new ways of understanding simultaneously produce new forms of nonknowledge, new uncertainties and mysteries. The scientific method, based in deduction and falsifiability, is better at proliferating questions than it is at answering them. For instance, Einstein’s theories about the curvature of space and motion at the quantum level provide new knowledge and generates new unknowns that previously could not be pondered.
Since every theory destabilizes as much as it solidifies in our view of the world, the collective frenzy to generate knowledge creates at the same time a mounting sense of futility, a tension looking for catharsis — a moment in which we could feel, if only for an instant, that we know something for sure. In contemporary culture, Big Data promises this relief.
As the name suggests, Big Data is about size. Many proponents of Big Data claim that massive databases can reveal a whole new set of truths because of the unprecedented quantity of information they contain. But the big in Big Data is also used to denote a qualitative difference — that aggregating a certain amount of information makes data pass over into Big Data, a “revolution in knowledge,” to use a phrase thrown around by startups and mass-market social-science books. Operating beyond normal science’s simple accumulation of more information, Big Data is touted as a different sort of knowledge altogether, an Enlightenment for social life reckoned at the scale of masses.
As with the similarly inferential sciences like evolutionary psychology and pop-neuroscience, Big Data can be used to give any chosen hypothesis a veneer of science and the unearned authority of numbers. The data is big enough to entertain any story. Big Data has thus spawned an entire industry (“predictive analytics”) as well as reams of academic, corporate, and governmental research; it has also sparked the rise of “data journalism” like that of FiveThirtyEight, Vox, and the other multiplying explainer sites. It has shifted the center of gravity in these fields not merely because of its grand epistemological claims but also because it’s well-financed. Twitter, for example recently announced that it is putting $10 million into a “social machines” Big Data laboratory.
The rationalist fantasy that enough data can be collected with the “right” methodology to provide an objective and disinterested picture of reality is an old and familiar one: positivism. This is the understanding that the social world can be known and explained from a value-neutral, transcendent view from nowhere in particular. The term comes from Positive Philosophy (1830-1842), by August Comte, who also coined the term sociology in this image. As Western sociology began to congeal as a discipline (departments, paid jobs, journals, conferences), Emile Durkheim, another of the field’s founders, believed it could function as a “social physics” capable of outlining “social facts” akin to the measurable facts that could be recorded about the physical properties of objects. It’s an arrogant view, in retrospect — one that aims for a grand, general theory that can explain social life, a view that became increasingly rooted as sociology became focused on empirical data collection.
A century later, that unwieldy aspiration has been largely abandoned by sociologists in favor of reorienting the discipline toward recognizing complexities rather than pursuing universal explanations for human sociality. But the advent of Big Data has resurrected the fantasy of a social physics, promising a new data-driven technique for ratifying social facts with sheer algorithmic processing power…(More)”
Paper by Young Ji Lee, Janet A. Arida, and Heidi S. Donovan at Cancer Medicine: “Crowdsourcing is “the practice of obtaining participants, services, ideas, or content by soliciting contributions from a large group of people, especially via the Internet.” (Ranard et al. J. Gen. Intern. Med. 29:187, 2014) Although crowdsourcing has been adopted in healthcare research and its potential for analyzing large datasets and obtaining rapid feedback has recently been recognized, no systematic reviews of crowdsourcing in cancer research have been conducted. Therefore, we sought to identify applications of and explore potential uses for crowdsourcing in cancer research. We conducted a systematic review of articles published between January 2005 and June 2016 on crowdsourcing in cancer research, using PubMed, CINAHL, Scopus, PsychINFO, and Embase. Data from the 12 identified articles were summarized but not combined statistically. The studies addressed a range of cancers (e.g., breast, skin, gynecologic, colorectal, prostate). Eleven studies collected data on the Internet using web-based platforms; one recruited participants in a shopping mall using paper-and-pen data collection. Four studies used Amazon Mechanical Turk for recruiting and/or data collection. Study objectives comprised categorizing biopsy images (n = 6), assessing cancer knowledge (n = 3), refining a decision support system (n = 1), standardizing survivorship care-planning (n = 1), and designing a clinical trial (n = 1). Although one study demonstrated that “the wisdom of the crowd” (NCI Budget Fact Book, 2017) could not replace trained experts, five studies suggest that distributed human intelligence could approximate or support the work of trained experts. Despite limitations, crowdsourcing has the potential to improve the quality and speed of research while reducing costs. Longitudinal studies should confirm and refine these findings….(More)”
Report by Erica Hagen for Making All Voices Count: “In Nairobi in 2009, 13 young residents of the informal settlement of Kibera mapped their community using OpenStreetMap, an online mapping platform. This was the start of Map Kibera, and eight years of ongoing work to date on digital mapping, citizen media and open data. In this paper, Erica Hagen – one of the initiators of Map Kibera – reflects on the trajectory of this work. Through research interviews with Map Kibera staff, participants and clients, and users of the data and maps the project has produced, she digs into what it means for citizens to map their communities, and examines the impact of open local information on members of the community. The paper begins by situating the research and Map Kibera in selected literature on transparency, accountability and mapping. It then presents three case studies of mapping in Kibera – in the education, security and water sectors – discussing evidence about the effects not only on project participants, but also on governmental and non-governmental actors in each of the three sectors. It concludes that open, community-based data collection can lead to greater trust, which is sorely lacking in marginalised places. In large-scale data gathering, it is often unclear to those involved why the data is needed or what will be done with it. But the experience of Map Kibera shows that by starting from the ground up and sharing open data widely, it is possible to achieve strong sector-wide ramifications beyond the scope of the initial project, including increased resources and targeting by government and NGOs. While debates continue over the best way to truly engage citizens in the ‘data revolution’ and tracking the Sustainable Development Goals, the research here shows that engaging people fully in the information value chain can be the missing link between data as a measurement tool, and information having an impact on social development….(More)”.
The key to turning privacy notices into something useful for consumers is to rethink their purpose. A company’s policy might show compliance with the regulations the firm is bound to follow, but remains impenetrable to a regular reader.
The starting point for developing consumer-friendly privacy notices is to make them relevant to the user’s activity, understandable and actionable. As part of the Usable Privacy Policy Project, my colleagues and I developed a way to make privacy notices more effective.
The first principle is to break up the documents into smaller chunks and deliver them at times that are appropriate for users. Right now, a single multi-page policy might have many sections and paragraphs, each relevant to different services and activities. Yet people who are just casually browsing a website need only a little bit of information about how the site handles their IP addresses, if what they look at is shared with advertisers and if they can opt out of interest-based ads. Those people doesn’t need to know about many other things listed in all-encompassing policies, like the rules associated with subscribing to the site’s email newsletter, nor how the site handles personal or financial information belonging to people who make purchases or donations on the site.
When a person does decide to sign up for email updates or pay for a service through the site, then an additional short privacy notice could tell her the additional information she needs to know. These shorter documents should also offer users meaningful choices about what they want a company to do – or not do – with their data. For instance, a new subscriber might be allowed to choose whether the company can share his email address or other contact information with outside marketing companies by clicking a check box.
Understanding users’ expectations
Notices can be made even simpler if they focus particularly on unexpected or surprising types of data collection or sharing. For instance, in another study, we learned that most people know their fitness tracker counts steps – so they didn’t really need a privacy notice to tell them that. But they did not expect their data to be collected, aggregated and shared with third parties. Customers should be asked for permission to do this, and allowed to restrict sharing or opt out entirely.
Most importantly, companies should test new privacy notices with users, to ensure final versions are understandable and not misleading, and that offered choices are meaningful….(More)”