Stefaan Verhulst
Paper by Sophie Devillers, Julien Vrydagh, Didier Caluwaerts & Min Reuchamps: “Random sampling offers an equal chance to all citizens to be randomly invited to a deliberative mini-public. However, a large number of randomly invited citizens usually refuses to participate, which is why larger sample has to be drawn to obtain enough positive responses to compose the mini-public. Then, a second random sampling is operated among the people who accepted to participate, usually along quotas reflecting the population at large. This paper seeks to investigate those people who were randomly invited but finally not selected to participate the citizen panel “Make your Brussels Mobility”. On the first stage, 8000 residents of Brussels were randomly invited. Among them, 377 accepted to participate. On the second stage, 40 citizens were randomly selected to compose the panel. Our paper builds on a survey sent to the 336 citizens who were finally not selected to participate and studies their perceptions of the legitimacy of the citizen panel….(More)”.
Book by Mario J. Rizzo and Glen Whitman: “The burgeoning field of behavioral economics has produced a new set of justifications for paternalism. This book challenges behavioral paternalism on multiple levels, from the abstract and conceptual to the pragmatic and applied. Behavioral paternalism relies on a needlessly restrictive definition of rational behavior. It neglects nonstandard preferences, experimentation, and self-discovery. It relies on behavioral research that is often incomplete and unreliable. It demands a level of knowledge from policymakers that they cannot reasonably obtain. It assumes a political process largely immune to the effects of ignorance, irrationality, and the influence of special interests and moralists. Overall, behavioral paternalism underestimates the capacity of people to solve their own problems, while overestimating the ability of experts and policymakers to design beneficial interventions. The authors argue instead for a more inclusive theory of rationality in economic policymaking….(More)”.
Domhnall O’Sullivan at swissinfo.ch:” “Voting up to four times a year, as the Swiss do, is a nice democratic right, but it also means keeping up with a lot of topics.
Usually this means following the media, talking to family and friends, watching what political parties and campaigners are saying, and wading through information sent out by authorities before vote day.
Last week, in advance of the next national ballot on February 9, 21,000 voters in the town of Sion got something new in the post: an informational sheet, drafted by a group of 20 randomly selected locals, giving a citizen’s take on what’s at stake.
The document, written by the citizen panel over two weekends last November, is the first output of ‘demoscan’: a project aiming to spur participation in a country where turnout rates are low and electoral issues sometimes complex.
On the front side, the issue (a proposed increase in the building of social housing) is presented in eight key points, listed in order of perceived importance; on the back, there are three arguments for and three arguments against the proposal.
At first reading, it’s not clear how different or more digestible the information is compared with what’s sent out by federal authorities, aside from the fact that unlike in the government’s package, there is no recommendation on how to vote. (Official materials include the position of parliament and government on each issue).
Demoscan project leader Nenad Stojanović says however that the main added value is that the document presents a “filtering” and “prioritising” of information – ultimately giving an overview of the most pertinent points as seen through the eyes of 20 “normal” citizens.
He also reckons that the process was as important as the output.
By selecting the participants randomly and representatively, the project included social groups not normally involved in the political debate, he says. Four days of research and deliberation were like a “democracy school”, teaching them about the functioning of previously distant institutions….(More)”.
Paper by Chiara Certoma, Filippo Corsini and MarcoFrey: “This paper critically explores the construction and diffusion of the socio-technical imaginary of crowdsourcing for public governance in Europe via a quali-quantitative analysis of academic publications, research and innovation projects funded by the European Commission (EC) and local initiatives. Building upon the increasing narrative of digital social participation that describes crowdsourcing processes as short ways towards democratisation of public decision-making processes, our research describes the trends and threats associated with the “hyperconnected city” imaginary advanced by (part of) scholarly research and EC policy documents and projects.
We show how, while these last describe digital-supported participation processes as (at least potentially) able to bootstrap an open governance agenda, local urban initiatives suggest the need to question this technology-optimistic imaginary.
A critical analysis of crowdsourcing for public governance prototyped and piloted in some European cities makes it evident that at local level, alternative imaginaries are emerging. We describe them in this paper as the “receptive city” (often adopted by public institutions and administration), and the “do-it-yourself city” (referring to the critical perspective of (digital) social activists) imaginaries, both emerging from local-based experiences and debates; and clarify their convergence and divergence how these differs from the above-mentioned “hyperconnected city” imaginary prefigured by EC guidelines.
The conclusive section further expands the analysis prefiguring future research possibilities promises in terms of local experiences influencing the future internet for society and digital agenda for Europe….(More)”.
Evan Nesterak at the Behavioral Scientist: “If you asked Richard Thaler in 2010, what he thought would become of the then very new field of behavioral science over the next decade, he would have been wrong, at least for the most part. Could he have predicted the expansion of behavioral economics research? Probably. The Nobel Prize? Maybe. The nearly 300 and counting behavioral teams in governments, businesses, and other organizations around the world? Not a chance.
When we asked him a year and a half ago to sum up the 10 years since the publication of Nudge, he replied “Am I too old to just say OMG? … [Cass Sunstein and I] would never have anticipated one “nudge unit” much less 200….Every once in a while, one of us will send the other an email that amounts to just ‘wow.’”
As we closed last year (and the last decade), we put out a call to help us imagine the next decade of behavioral science. We asked you to share your hopes and fears, predictions and warnings, open questions and big ideas.
We received over 120 submissions from behavioral scientists around the world. We picked the most thought-provoking submissions and curated them below.
We’ve organized the responses into three sections. The first section, Promises and Pitfalls, houses the responses about the field as whole—its identity, purpose, values. In that section, you’ll find authors challenging the field to be bolder. You’ll also find ideas to unite the field, which in its growth has felt for some like the “Wild West.” Ethical concerns are also top of mind. “Behavioral science has confronted ethical dilemmas before … but never before has the essence of the field been so squarely in the wheelhouse of corporate interests,” writes Phillip Goff.
In the second section, we’ve placed the ideas about specific domains. This includes “Technology: Nightmare or New Norm,” where Tania Ramos considers the possibility of a behaviorally optimized tech dystopia. In “The Future of Work,” Lazslo Bock imagines that well-timed, intelligent nudges will foster healthier company cultures, and Jon Jachomiwcz emphasizes the importance of passion in an economy increasingly dominated by A.I. In “Climate Change: Targeting Individuals and Systems” behavioral scientists grapple with how the field can pull its weight in this existential fight. You’ll also find sections on building better governments, health care at the digital frontier and final mile, and the next steps for education.
The third and final section gets the most specific of all. Here you’ll find commentary on the opportunities (and obligations) for research and application. For instance, George Lowenstein suggests we pay more attention to attention—an increasingly scarce resource. Others, on the application side, ponder how behavioral science will influence the design of our neighborhoods and wonder what it will take to bring behavioral science into the courtroom. The section closes with ideas on the future of intervention design and ways we can continue to master our methods….(More)”.
Paper by Vivian Reckers-Droog et al: “A deliberative citizens panel was held to obtain insight into criteria considered relevant for healthcare priority setting in the Netherlands. Our aim was to examine whether and how panel participation influenced participants’ views on this topic. Participants (n = 24) deliberated on eight reimbursement cases in September and October, 2017. Using Q methodology, we identified three distinct viewpoints before (T0) and after (T1) panel participation. At T0, viewpoint 1 emphasised that access to healthcare is a right and that prioritisation should be based solely on patients’ needs. Viewpoint 2 acknowledged scarcity of resources and emphasised the importance of treatment-related health gains. Viewpoint 3 focused on helping those in need, favouring younger patients, patients with a family, and treating diseases that heavily burden the families of patients. At T1, viewpoint 1 had become less opposed to prioritisation and more considerate of costs. Viewpoint 2 supported out-of-pocket payments more strongly. A new viewpoint 3 emerged that emphasised the importance of cost-effectiveness and that prioritisation should consider patient characteristics, such as their age. Participants’ views partly remained stable, specifically regarding equal access and prioritisation based on need and health gains. Notable changes concerned increased support for prioritisation, consideration of costs, and cost-effectiveness. Further research into the effects of deliberative methods is required to better understand how they may contribute to the legitimacy of and public support for allocation decisions in healthcare….(More)”.
Report by John Villasenor: “Much has been written, and rightly so, about the potential that artificial intelligence (AI) can be used to create and promote misinformation. But there is a less well-recognized but equally important application for AI in helping to detect misinformation and limit its spread. This dual role will be particularly important in geopolitics, which is closely tied to how governments shape and react to public opinion both within and beyond their borders. And it is important for another reason as well: While nation-state interest in information is certainly not new, the incorporation of AI into the information ecosystem is set to accelerate as machine learning and related technologies experience continued advances.
The present article explores the intersection of AI and information integrity in the specific context of geopolitics. Before addressing that topic further, it is important to underscore that the geopolitical implications of AI go far beyond information. AI will reshape defense, manufacturing, trade, and many other geopolitically relevant sectors. But information is unique because information flows determine what people know about their own country and the events within it, as well as what they know about events occurring on a global scale. And information flows are also critical inputs to government decisions regarding defense, national security, and the promotion of economic growth. Thus, a full accounting of how AI will influence geopolitics of necessity requires engaging with its application in the information ecosystem.
This article begins with an exploration of some of the key factors that will shape the use of AI in future digital information technologies. It then considers how AI can be applied to both the creation and detection of misinformation. The final section addresses how AI will impact efforts by nation-states to promote–or impede–information integrity….(More)”.
Book edited by Mireille Hildebrandt and Kieron O’Hara: “This ground-breaking and timely book explores how big data, artificial intelligence and algorithms are creating new types of agency, and the impact that this is having on our lives and the rule of law. Addressing the issues in a thoughtful, cross-disciplinary manner, the authors examine the ways in which data-driven agency is transforming democratic practices and the meaning of individual choice.
Leading scholars in law, philosophy, computer science and politics analyse the latest innovations in data science and machine learning, assessing the actual and potential implications of these technologies. They investigate how this affects our understanding of such concepts as agency, epistemology, justice, transparency and democracy, and advocate a precautionary approach that takes the effects of data-driven agency seriously without taking it for granted….(More)”.
Essay by Bruce Sterling: “This is an essay about lists of moral principles for the creators of Artificial Intelligence. I collect these lists, and I have to confess that I find them funny.
Nobody but AI mavens would ever tiptoe up to the notion of creating godlike cyber-entities that are much smarter than people. I hasten to assure you — I take that weird threat seriously. If we could wipe out the planet with nuclear physics back in the late 1940s, there must be plenty of other, novel ways to get that done.
What I find comical is a programmer’s approach to morality — the urge to carefully type out some moral code before raising unholy hell. Many professions other than programming have stern ethical standards: lawyers and doctors, for instance. Are lawyers and doctors evil? It depends. If a government is politically corrupt, then a nation’s lawyers don’t escape that moral stain. If a health system is slaughtering the population with mis-prescribed painkillers, then doctors can’t look good, either.
So if AI goes south, for whatever reason, programmers are just bound to look culpable and sinister. Careful lists of moral principles will not avert that moral judgment, no matter how many earnest efforts they make to avoid bias, to build and test for safety, to provide feedback for user accountability, to design for privacy, to consider the colossal abuse potential, and to eschew any direct involvement in AI weapons, AI spyware, and AI violations of human rights.
I’m not upset by moral judgments in well-intentioned manifestos, but it is an odd act of otherworldly hubris. Imagine if car engineers claimed they could build cars fit for all genders and races, test cars for safety-first, mirror-plate the car windows and the license plates for privacy, and make sure that military tanks and halftracks and James Bond’s Aston-Martin spy-mobile were never built at all. Who would put up with that presumptuous behavior? Not a soul, not even programmers.
In the hermetic world of AI ethics, it’s a given that self-driven cars will kill fewer people than we humans do. Why believe that? There’s no evidence for it. It’s merely a cranky aspiration. Life is cheap on traffic-choked American roads — that social bargain is already a hundred years old. If self-driven vehicles doubled the road-fatality rate, and yet cut shipping costs by 90 percent, of course those cars would be deployed.
I’m not a cynic about morality per se, but everybody’s got some. The military, the spies, the secret police and organized crime, they all have their moral codes. Military AI flourishes worldwide, and so does cyberwar AI, and AI police-state repression….(More)”.
Grzegorz Mazurek and Karolina Małagocka at Business Horizons: “Technological progress—including the development of online channels and universal access to the internet via mobile devices—has advanced both the quantity and the quality of data that companies can acquire. Private information such as this may be considered a type of fuel to be processed through the use of technologies, and represents a competitive market advantage.
This article describes situations in which consumers tend to disclose personal information to companies and explores factors that encourage them to do so. The empirical studies and examples of market activities described herein illustrate to managers just how rewards work and how important contextual integrity is to customer digital privacy expectations. Companies’ success in obtaining client data depends largely on three Ts: transparency, type of data, and trust. These three Ts—which, combined, constitute a main T (i.e., the transfer of personal data)—deserve attention when seeking customer information that can be converted to competitive advantage and market success….(More)”.