Stefaan Verhulst
Book by Tim Harford: “…When was the last time you read a grand statement, accompanied by a large number, and wondered whether it could really be true? Statistics are vital in helping us tell stories – we see them in the papers, on social media, and we hear them used in everyday conversation – and yet we doubt them more than ever.
But numbers – in the right hands – have the power to change the world for the better. Contrary to popular belief, good statistics are not a trick, although they are a kind of magic. Good statistics are not smoke and mirrors; in fact, they help us see more clearly. Good statistics are like a telescope for an astronomer, a microscope for a bacteriologist, or an X-ray for a radiologist. If we are willing to let them, good statistics help us see things about the world around us and about ourselves – both large and small - that we would not be able to see in any other way.
In How to Make the World Add Up, Tim Harford draws on his experience as both an economist and presenter of the BBC’s radio show ‘More or Less’. He takes us deep into the world of disinformation and obfuscation, bad research and misplaced motivation to find those priceless jewels of data and analysis that make communicating with numbers worthwhile. Harford’s characters range from the art forger who conned the Nazis to the stripper who fell in love with the most powerful congressman in Washington, to famous data detectives such as John Maynard Keynes, Daniel Kahneman and Florence Nightingale. He reveals how we can evaluate the claims that surround us with confidence, curiosity and a healthy level of scepticism.
Using ten simple rules for understanding numbers – plus one golden rule – this extraordinarily insightful book shows how if we keep our wits about us, thinking carefully about the way numbers are sourced and presented, we can look around us and see with crystal clarity how the world adds up….(More)”.
Book by Ryan Abbott: “AI and people do not compete on a level-playing field. Self-driving vehicles may be safer than human drivers, but laws often penalize such technology. People may provide superior customer service, but businesses are automating to reduce their taxes. AI may innovate more effectively, but an antiquated legal framework constrains inventive AI. In The Reasonable Robot, Ryan Abbott argues that the law should not discriminate between AI and human behavior and proposes a new legal principle that will ultimately improve human well-being. This work should be read by anyone interested in the rapidly evolving relationship between AI and the law….(More)”.
Paper by Lydia X. Z. Brown, Michelle Richardson, Ridhi Shetty, and Andrew Crawford: “Governments are increasingly turning to algorithms to determine whether and to what extent people should receive crucial benefits for programs like Medicaid, Medicare, unemployment, and Social Security Disability. Billed as a way to increase efficiency and root out fraud, these algorithm-driven decision-making tools are often implemented without much public debate and are incredibly difficult to understand once underway. Reports from people on the ground confirm that the tools are frequently reducing and denying benefits, often with unfair and inhumane results.
Benefits recipients are challenging these tools in court, arguing that flaws in the programs’ design or execution violate their due process rights, among other claims. These cases are some of the few active courtroom challenges to algorithm-driven decision-making, producing important precedent about people’s right to notice, explanation, and other procedural due process safeguards when algorithm-driven decisions are made about them. As the legal and policy world continues to recognize the outsized impact of algorithm-driven decision-making in various aspects of our lives, public benefits cases provide important insights into how such tools can operate; the risks of errors in design and execution; and the devastating human toll when tools are adopted without effective notice, input, oversight, and accountability.
This report analyzes lawsuits that have been filed within the past 10 years arising from the use of algorithm-driven systems to assess people’s eligibility for, or the distribution of, public benefits. It identifies key insights from the various cases into what went wrong and analyzes the legal arguments that plaintiffs have used to challenge those systems in court. It draws on direct interviews with attorneys who have litigated these cases and plaintiffs who sought to vindicate their rights in court – in some instances suing not only for themselves, but on behalf of similarly situated people. The attorneys work in legal aid offices, civil rights litigation shops, law school clinics, and disability protection and advocacy offices. The cases cover a range of benefits issues and have netted mixed results.
People with disabilities experience disproportionate and particular harm because of unjust algorithm-driven decision-making, and we have attempted to center disabled people’s stories and cases in this paper. As disabled people fight for rights inside and outside the courtroom on a wide range of issues, we focus on litigation and highlight the major legal theories for challenging improper algorithm-driven benefit denials in the U.S.
The good news is that in some cases, plaintiffs are successfully challenging improper adverse benefits decisions with Constitutional, statutory, and administrative claims. But like other forms of civil rights and impact litigation, the bad news is that relief can be temporary and is almost always delayed. Litigation must therefore work in tandem with the development of new processes driven by people who require access to public assistance and whose needs are centered in these processes. We hope this contribution informs not only the development of effective litigation, but a broader public conversation about the thoughtful design, use, and oversight of algorithm-driven decision-making systems….(More)”.
Essay by Marion Fourcade and Jeff Gordon: “…Recent books have argued that we live in an age of “informational” or “surveillance” capitalism, a new form of market governance marked by the accumulation and assetization of information, and by the dominance of platforms as sites of value extraction. Over the last decade-plus, both actual and idealized governance have been transformed by a combination of neoliberal ideology, new technologies for tracking and ranking populations, and the normative model of the platform behemoths, which carry the banner of technological modernity. In concluding a review of Julie Cohen’s and Shoshana Zuboff’s books, Amy Kapcyznski asks how we might build public power sufficient to govern the new private power. Answering that question, we believe, requires an honest reckoning with how public power has been warped by the same ideological, technological, and legal forces that brought about informational capitalism.
In our contribution to the inaugural JLPE issue, we argue that governments and their agents are starting to conceive of their role differently than in previous techno-social moments. Our jumping-off point is the observation that what may first appear as mere shifts in the state’s use of technology—from the “open data” movement to the NSA’s massive surveillance operation—actually herald a deeper transformation in the nature of statecraft itself. By “statecraft,” we mean the state’s mode of learning about society and intervening in it. We contrast what we call the “dataist” state with its high modernist predecessor, as portrayed memorably by the anthropologist James C. Scott, and with neoliberal governmentality, described by, among others, Michel Foucault and Wendy Brown.
The high modernist state expanded the scope of sovereignty by imposing borders, taking censuses, and coercing those on the outskirts of society into legibility through broad categorical lenses. It deployed its power to support large public projects, such as the reorganization of urban infrastructure. As the ideological zeitgeist evolved toward neoliberalism in the 1970s, however, the priority shifted to shoring up markets, and the imperative of legibility trickled down to the individual level. The poor and working class were left to fend for their rights and benefits in the name of market fitness and responsibility, while large corporations and the wealthy benefited handsomely.
As a political rationality, dataism builds on both of these threads by pursuing a project of total measurement in a neoliberal fashion—that is, by allocating rights and benefits to citizens and organizations according to (questionable) estimates of moral desert, and by re-assembling a legible society from the bottom up. Weakened by decades of anti-government ideology and concomitantly eroded capacity, privatization, and symbolic degradation, Western states have determined to manage social problems as they bubble up into crises rather than affirmatively seeking to intervene in their causes. The dataist state sets its sights on an expanse of emergent opportunities and threats. Its focus is not on control or competition, but on “readiness.” Its object is neither the population nor a putative homo economicus, but (as Gilles Deleuze put it) “dividuals,” that is, discrete slices of people and things (e.g. hospital visits, police stops, commuting trips). Under dataism, a well-governed society is one where events (not persons) are aligned to the state’s models and predictions, no matter how disorderly in high modernist terms or how irrational in neoliberal terms….(More)”.
Chris Zollinger at Diplomatic Courier: “What a difference a year makes. A survey in April showed that almost 40% of people in the EU had switched to remote work, while estimates in the U.S. range from 30-50%. The video conference has become a staple of our daily working lives in a way that would have been inconceivable 12 months ago, while virtual collaboration tools have become ubiquitous.
Given the straightened economic climate, it is unsurprising that many businesses see the situation as an opportunity to permanently reduce their cost base. Facebook, for example, has announced that it expects half of its global workforce to work remotely within the next five to ten years, with Twitter, Barclays and Mondelez International making similar moves. On a purely financial level, this seems like a win-win for everyone concerned: employers can save on the capital and operational costs of providing office space, while employees can save the time and money that it would have cost to commute.
However, if we want to move beyond mere economic survival towards recovery and growth, we need to be more ambitious in our thinking. Rather than merely cutting costs, we now have the chance to drive greater innovation and productivity by building more flexible, remote teams. In addition to the cost and time savings associated with remote work, companies now have an opportunity to shift the focus of their recruitment to new geographic areas and hire talented new employees without the need for them to physically relocate. In this way, they can form purpose-built teams to solve specific tasks over a defined time period….(More)”.
Martin Reeves , Simon Levin , Thomas Fink and Ania Levina at Harvard Business Review: “….“Complexity” is one of the most frequently used terms in business but also one of the most ambiguous. Even in the sciences it has numerous definitions. For our purposes, we’ll define it as a large number of different elements (such as specific technologies, raw materials, products, people, and organizational units) that have many different connections to one another. Both qualities can be a source of advantage or disadvantage, depending on how they’re managed.
Let’s look at their strengths. To begin with, having many different elements increases the resilience of a system. A company that relies on just a few technologies, products, and processes—or that is staffed with people who have very similar backgrounds and perspectives—doesn’t have many ways to react to unforeseen opportunities and threats. What’s more, the redundancy and duplication that also characterize complex systems typically give them more buffering capacity and fallback options.
Ecosystems with a diversity of elements benefit from adaptability. In biology, genetic diversity is the grist for natural selection, nature’s learning mechanism. In business, as environments shift, sustained performance requires new offerings and capabilities—which can be created by recombining existing elements in fresh ways. For example, the fashion retailer Zara introduces styles (combinations of components) in excess of immediate needs, allowing it to identify the most popular products, create a tailored selection from them, and adapt to fast-changing fashion as a result.
Another advantage that complexity can confer on natural ecosystems is better coordination. That’s because the elements are often highly interconnected. Flocks of birds or herds of animals, for instance, share behavioral protocols that connect the members to one another and enable them to move and act as a group rather than as an uncoordinated collection of individuals. Thus they realize benefits such as collective security and more-effective foraging.
Finally, complexity can confer inimitability. Whereas individual elements may be easily copied, the interrelationships among multiple elements are hard to replicate. A case in point is Apple’s attempt in 2012 to compete with Google Maps. Apple underestimated the complexity of Google’s offering, leading to embarrassing glitches in the initial versions of its map app, which consequently struggled to gain acceptance with consumers. The same is true of a company’s strategy: If its complexity makes it hard to understand, rivals will struggle to imitate it, and the company will benefit….(More)”.
Paper by Kaitlin Fender Throgmorton, Bree Norlander and Carole L. Palmer: “As the open data movement grows, public libraries must assess if and how to invest resources in this new service area. This paper reports on a recent survey on open data in public libraries across Washington state, conducted by the Open Data Literacy project (ODL) in collaboration with the Washington State Library. Results document interests and activity in open data across small, medium, and large libraries in relation to traditional library services and priorities. Libraries are particularly active in open data through reference services and are beginning to release their own library data to the public. While capacity and resource challenges hinder progress for some, many libraries, large and small, are making progress on new initiatives, including strategic collaborations with local government agencies. Overall, the level and range of activity suggest that Washington state public libraries of all sizes recognize the value of open data for their communities, with a groundswell of libraries moving beyond ambition to action as they develop new services through evolution and innovation….(More)”.
Paper by Karl de Fine Licht & Jenny de Fine Licht: “The increasing use of Artificial Intelligence (AI) for making decisions in public affairs has sparked a lively debate on the benefits and potential harms of self-learning technologies, ranging from the hopes of fully informed and objectively taken decisions to fear for the destruction of mankind. To prevent the negative outcomes and to achieve accountable systems, many have argued that we need to open up the “black box” of AI decision-making and make it more transparent. Whereas this debate has primarily focused on how transparency can secure high-quality, fair, and reliable decisions, far less attention has been devoted to the role of transparency when it comes to how the general public come to perceive AI decision-making as legitimate and worthy of acceptance. Since relying on coercion is not only normatively problematic but also costly and highly inefficient, perceived legitimacy is fundamental to the democratic system. This paper discusses how transparency in and about AI decision-making can affect the public’s perception of the legitimacy of decisions and decision-makers and produce a framework for analyzing these questions. We argue that a limited form of transparency that focuses on providing justifications for decisions has the potential to provide sufficient ground for perceived legitimacy without producing the harms full transparency would bring….(More)”.
Paper by Michael Kwet: “South Africa’s long legacy of racism and colonial exploitation continues to echo throughout post-apartheid society. For centuries, European conquerors marshaled surveillance as a means to control the black population. This began with the requirements for passes to track and control the movements, settlements, and labor of Africans. Over time, surveillance technologies evolved alongside complex shifts in power, culture, and the political economy.
This Chapter explores the evolution of surveillance regimes in South Africa. The first surveillance system in South Africa used paper passes to police slave movements and enforce labor contracts. To make the system more robust, various white authorities marked the skin of workers and livestock with symbols registered in paper databases. At the beginning of the twentieth century, fingerprinting was introduced in some areas to simplify and improve the passes. Under apartheid, the National Party aimed to streamline a national, all-seeing surveillance system. They imported computers to impose a regime of fixed race classification and keep detailed records about the African population. The legal apparatus of race-based surveillance was finally abolished during the transition to democracy. However, today a regime of Big Data, artificial intelligence, and centralized cloud computing has ushered in a new era of mass surveillance in South Africa.
South Africa’s surveillance regimes were always devised in collaboration with foreign colonizers, imperialists, intellectuals, and profit-seeking capitalists. In each era, the United States increased its participation. During the period of settler conquest, the US had a modest presence in Southern Africa. With the onset of the minerals revolution, US power expanded, and American capitalists and engineers with business interests in the mines pushed for an improved pass system to police African workers. Under apartheid, US corporations supplied the computer technology essential to apartheid governance and business enterprise. Finally, during the latter years of post-apartheid, Silicon Valley corporations, together with US surveillance agencies, began imposing surveillance capitalism on South African society. A new form of domination, digital colonialism, has emerged, vesting the United States with unprecedented control over South African affairs. To counter the force of digital colonialism, a new movement may emerge to push to redesign the digital ecosystem as a socialist commons based on open technology, socialist legal solutions, bottom-up democracy, and Internet decentralization….(More).”
Paper (and site) by Stefaan G. Verhulst, Andrew Young, Andrew J. Zahuranec, Susan Ariel Aaronson, Ania Calderon, and Matt Gee on “How To Accelerate the Re-Use of Data for Public Interest Purposes While Ensuring Data Rights and Community Flourishing”: “The paper begins with a description of earlier waves of open data. Emerging from freedom of information laws adopted over the last half century, the First Wave of Open Data brought about newfound transparency, albeit one only available on request to an audience largely composed of journalists, lawyers, and activists.
The Second Wave of Open Data, seeking to go beyond access to public records and inspired by the open source movement, called upon national governments to make their data open by default. Yet, this approach too had its limitations, leaving many data silos at the subnational level and in the private sector untouched..
The Third Wave of Open Data seeks to build on earlier successes and take into account lessons learned to help open data realize its transformative potential. Incorporating insights from various data experts, the paper describes the emergence of a Third Wave driven by the following goals:
- Publishing with Purpose by matching the supply of data with the demand for it, providing assets that match public interests;
- Fostering Partnerships and Data Collaboration by forging relationships with community-based organizations, NGOs, small businesses, local governments, and others who understand how data can be translated into meaningful real-world action;
- Advancing Open Data at the Subnational Level by providing resources to cities, municipalities, states, and provinces to address the lack of subnational information in many regions.
- Prioritizing Data Responsibility and Data Rights by understanding the risks of using (and not using) data to promote and preserve the public’s general welfare.
Riding the Wave
Achieving these goals will not be an easy task and will require investments and interventions across the data ecosystem. The paper highlights eight actions that decision and policy makers can take to foster more equitable, impactful benefits… (More) (PDF) “