Stefaan Verhulst
Paper by Benjamin H. Detenber: “The city state of Singapore has a long history of social engineering efforts, yet only recently have social scientists and civil servants started to use behavioural insights (BI) to create ‘nudges’ and integrate them into the daily lives of citizens. Colloquially known as a nanny state for its extensive social programmes and sometimes heavy-handed approach to guiding social behaviour, Singapore is often regarded favourably by its neighbours in terms of its cleanliness, efficiency, and productivity. Yet how it manages its populace and the restrictions it imposes on unwanted behaviours are sometimes viewed sceptically by others in Asia and the West. Thus, many in the Singapore Civil Service have come to see nudging as a less coercive way to promote social welfare and well-being. This article reviews some of the latest actions in three areas: finance, health, and the environment. In discussing the range of nudging practices, their effectiveness will be assessed and some of the implications for society and individuals will be addressed. To the extent that Singapore can be considered a bellwether or harbinger, its use of nudges may offer a glimpse of what lies ahead for other countries in the region….(More)”.
Paper by Stefan Wojcik et al: “While digital trace data from sources like search engines hold enormous potential for tracking and understanding human behavior, these streams of data lack information about the actual experiences of those individuals generating the data. Moreover, most current methods ignore or under-utilize human processing capabilities that allow humans to solve problems not yet solvable by computers (human computation). We demonstrate how behavioral research, linking digital and real-world behavior, along with human computation, can be utilized to improve the performance of studies using digital data streams. This study looks at the use of search data to track prevalence of Influenza-Like Illness (ILI). We build a behavioral model of flu search based on survey data linked to users’ online browsing data. We then utilize human computation for classifying search strings. Leveraging these resources, we construct a tracking model of ILI prevalence that outperforms strong historical benchmarks using only a limited stream of search data and lends itself to tracking ILI in smaller geographic units. While this paper only addresses searches related to ILI, the method we describe has potential for tracking a broad set of phenomena in near real-time….(More)”
Paper by Sabelo Mhlambi: “What is the measure of personhood and what does it mean for machines to exhibit human-like qualities and abilities? Furthermore, what are the human rights, economic, social, and political implications of using machines that are designed to reproduce human behavior and decision making? The question of personhood is one of the most fundamental questions in philosophy and it is at the core of the questions, and the quest, for an artificial or mechanical personhood.
The development of artificial intelligence has depended on the traditional Western view of personhood as rationality. However, the traditional view of rationality as the essence of personhood, designating how humans, and now machines, should model and approach the world, has always been marked by contradictions, exclusions, and inequality. It has shaped Western economic structures (capitalism’s free markets built on colonialism’s forced markets), political structures (modernity’s individualism imposed through coloniality), and discriminatory social hierarchies (racism and sexism as institutions embedded in enlightenment-era rationalized social and gender exclusions from full person status and economic, political, and social participation), which in turn shape the data, creation, and function of artificial intelligence. It is therefore unsurprising that the artificial intelligence industry reproduces these dehumanizations. Furthermore, the perceived rationality of machines obscures machine learning’s uncritical imitation of discriminatory patterns within its input data, and minimizes the role systematic inequalities play in harmful artificial intelligence outcomes….(More)”.
Article by Jeffrey Brown and Stefaan Verhulst: “…But in many cases, policymakers face a blizzard of contradictory information and forecasts that can lead to confusion and inaction. Unable to make sense of the torrent of data being thrown their way, policymakers often end up being preoccupied by the answers presented — rather than reflecting on the questions that matter.
If we want to design “good” future-of-work policies, we must have an inclusive and wide-ranging discussion of what we are trying to solve before we attempt to develop and deploy solutions….
We have found that policymakers often fail to ask questions and are often uncertain about the variables that underpin a problem.
In addition, few of the interventions that have been deployed make the best use of data, an emerging but underused asset that is increasingly available as a result of the ongoing digital transformation. If civil society, think tanks and others fail to create the space for a sustainable future-of-work policy to germinate, “solutions” without clearly articulated problems will continue to dictate policy…
Our 100 Questions Initiative seeks to interrupt this cycle of preoccupation with answers by ensuring that policymakers are, first of all, armed with a methodology they can use to ask the right questions and from there, craft the right solutions.
We are now releasing the top 10 questions and are seeking the public’s assistance through voting and providing feedback on whether or not these are really the right questions we should be asking:
Preparing for the Future of Work
- How can we determine the value of skills relevant to the future-of work-marketplace, and how can we increase the value of human labor in the 21st century?
- What are the economic and social costs and benefits of modernizing worker-support systems and providing social protection for workers of all employment backgrounds, but particularly for women and those in part-time or informal work?
- How does the current use of AI affect diversity and equity in the labor force? How can AI be used to increase the participation of underrepresented groups (including women, Black people, Latinx people, and low-income communities)? What aspects/strategies have proved most effective in reducing AI biases?…(More) (See also: https://future-of-work.the100questions.org/)
The fourth report in this series by the OECD: “…explores the powerful new technologies and opportunities that governments have at their disposal to let them better understand the needs of citizens. The research shows that governments must balance the tensions of using data harvesting and monitoring, and technologies that can identify individuals, to serve the public interest, with the inevitable concerns and legitimate fears about “big brother” and risks of infringing on freedoms and rights. Through the lens of navigating Public Provider versus Big Brother, innovation efforts fall into two key themes:
Theme 1: Data harvesting and monitoring
Governments have access to more detailed data than ever before, but such access involves risks and considerations which require serious reflection on the part of government.
Theme 2: Biometric technologies and facial recognition
A range of biometric tools offer opportunities to provide tailored services, as well as the unprecedented ability to identify and track individuals’ behaviours and movements….(More)”.
Paper by Manuel Morales et al: “COVID-19 testing, the cornerstone for effective screening and identification of COVID-19 cases, remains paramount as an intervention tool to curb the spread of COVID-19 both at local and national levels. However, the speed at which the pandemic struck and the response was rolled out, the widespread impact on healthcare infrastructure, the lack of sufficient preparation within the public health system, and the complexity of the crisis led to utter confusion among test-takers. Invasion of privacy remains a crucial concern. The user experience of test takers remains low. User friction affects user behavior and discourages participation in testing programs. Test efficacy has been overstated. Test results are poorly understood resulting in inappropriate follow-up recommendations. Herein, we review the current landscape of COVID-19 testing, identify four key challenges, and discuss the consequences of the failure to address these challenges. The current infrastructure around testing and information propagation is highly privacy-invasive and does not leverage scalable digital components. In this work, we discuss challenges complicating the existing covid-19 testing ecosystem and highlight the need to improve the testing experience for the user and reduce privacy invasions. Digital tools will play a critical role in resolving these challenges….(More)”.
Gabriel Geiger at Motherboard: “An algorithm used by the popular European food delivery app Deliveroo to rank and offer shifts to riders is discriminatory, an Italian court ruled late last week, in what some experts are calling a historic decision for the gig economy. The case was brought by a group of Deliveroo riders backed by CGIL, Italy’s largest trade union.
A markedly detailed ordinance written by presiding judge Chiara Zompi gives an intimate look at one of many often secretive algorithms used by gig platforms to micromanage workers and which can have profound impacts on their livelihoods.
While machine-learning algorithms are central to Deliveroo’s entire business model, the particular algorithm examined by the court allegedly was used to determine the “reliability” of a rider. According to the ordinance, if a rider failed to cancel a shift pre-booked through the app at least 24 hours before its start, their “reliability index” would be negatively affected. Since riders deemed more reliable by the algorithm were first to be offered shifts in busier timeblocks, this effectively meant that riders who can’t make their shifts—even if it’s because of a serious emergency or illness—would have fewer job opportunities in the future….(More)”
Paper by Mahmood Jasim: “Local governments still depend on traditional town halls for community consultation, despite problems such as a lack of inclusive participation for attendees and difficulty for civic organizers to capture attendees’ feedback in reports. Building on a formative study with 66 town hall attendees and 20 organizers, we designed and developed CommunityClick, a community sourcing system that captures attendees’ feedback in an inclusive manner and enables organizers to author more comprehensive reports. During the meeting, in addition to recording meeting audio to capture vocal attendees’ feedback, we modify iClickers to give voice to reticent attendees by allowing them to provide real-time feedback beyond a binary signal. This information then automatically feeds into a meeting transcript augmented with attendees’ feedback and organizers’ tags. The augmented transcript along with a feedback-weighted summary of the transcript generated from text analysis methods is incorporated into an interactive authoring tool for organizers to write reports. From a field experiment at a town hall meeting, we demonstrate how CommunityClick can improve inclusivity by providing multiple avenues for attendees to share opinions. Additionally, interviews with eight expert organizers demonstrate CommunityClick’s utility in creating more comprehensive and accurate reports to inform critical civic decision-making. We discuss the possibility of integrating CommunityClick with town hall meetings in the future as well as expanding to other domains….(More)”.
Jonathan Rauch in National Affairs: “…As a child, I asked my father, a lawyer, what the word “professional” meant. He replied, “it means you do something for a living.” He contrasted it with the term “amateur,” meaning someone who works for pleasure.
My father’s definition has merit. I recall it whenever I tell interns that, to me, professionalism means performing a job to the highest standards, even when I don’t feel like doing it at all. One might think of the doctor who shows up for emergency surgery on Christmas Eve, the journalist who takes care to verify every fact mentioned in a report, or the concert pianist who gives the audience the best he is capable of night after night, even on nights when he would much rather be doing anything else.
That concept of professionalism is a good starting point, but we can dig deeper by drawing on the work of the American Enterprise Institute’s Yuval Levin. In his book A Time to Build, Levin explores the role and meaning of institutions. Institutions, he says, are — or, when they function well, should be — forms, training and shaping people to work together toward a larger goal. The military is a classic example, as are churches and schools. These “structures of social life” provide the durable arrangements that frame our perceptions, mold our character, and delineate our social existence.
When institutions do not or cannot perform those shaping functions, they collapse into something more like platforms — stages upon which individuals perform in order to build audiences and self-advertise. He locates the collapse of trust in institutions — and the resulting public sense of anomie and disconnectedness — in the conversion of many institutions from places where people are formed to places where people perform. Thus a self-promoting real-estate magnate can become a self-promoting reality-TV host and then a self-promoting presidential candidate, hopping from one stage to the next, all while putting on pretty much the same show.
As institutions have drifted away from shaping us and toward displaying us, they have lost both efficacy and legitimacy. And we, in turn, have naturally lost confidence in them. Moreover, Levin argues, institutions have been taken for granted for so long, and yet are neglected so generally, that we have lost even the vocabulary for talking about what they are supposed to be doing. We don’t realize what we are missing, although we acutely feel the void.
Something very much like that has happened with professionalism. A combination of institutional absence, lazy thinking, and populist politics has collapsed the idea of professionalism down to the much flatter notion of elitism.
To some extent, it is natural to think of professionalism and elitism as two sides of the same coin. After all, many professionals are people with advanced degrees and high incomes who occupy elite positions in society. We imagine professionalism to be about excluding others from certain pursuits or occupations like law and medicine — a seemingly elitist practice. We think of it, too, as synonymous with professional schooling, something not everyone can aspire to.
Still, there is a world of difference between professionals and elites. Elites are influential by dint of who they are and whom they know. They are elite because they have social connections and powerful positions. Professionals, by contrast, are influential by dint of what they know and what they do. Their status is contingent on both their standing and their behavior.
That distinction gestures toward a fuller definition of professionalism, one that implies commitment to personal standards, social norms, and expert knowledge in furtherance of a mission or an institution. That is, professionalism defines a right way of doing things — a notion of best practices — that is grounded in dedication to a mission or an institution rather than personal advancement or partisan loyalty. As Levin says, professionalism “tends to yield a strong internal ethos among practitioners. In uncertain situations, a professional asks himself, ‘What should I do here, given my professional responsibilities?’ And his profession will generally have an answer to that question.”
As Levin notices, institutionalism and professionalism are cousins. Both institutions and professions organize individuals to accomplish missions, they seek to inculcate norms and guide behavior, they assemble and transmit knowledge and best practices across generations, they cultivate reputational capital over long spans of time, and they draw and enforce boundaries between insiders and outsiders….(More)”
Paper by Amy Kristin Sanders at the Journal of Civic Information: “As the U.S. has grappled with COVID-19, the government has resisted repeated requests to follow open records laws, which are essential to transparency. Current efforts to reduce access to death records and other public information amid the pandemic jeopardizes government accountability and undermines the public’s trust. Given that COVID-19 has disproportionately affected low-income Americans, incarcerated populations and people of color, access to government-held data has serious implications for social justice. Importantly, those goals can be met without violating personal privacy. After analyzing state open records laws, court decisions and attorney general opinions, the author has developed a set of best practices for advocating access to death records to provide journalists and government watchdogs with important public health information that’s squarely in the public interest….(More)”.