Stefaan Verhulst

Paper by Linus Dahlander and Henning Piezunka: ” Crowdsourcing—asking an undefned group of external contributors to work on tasks—allows organizations to tap into the expertise of people around the world. Crowdsourcing is known to increase innovation and loyalty to brands, but many organizations struggle to leverage its potential, as our research shows. Most often this is because organizations fail to properly plan for all the diferent stages of crowd engagement. In this paper, we use several examples to explain these challenges and ofer advice for how organizations can overcome them….(More)”.

Book edited by Kevin Macnish and Jai Galliott: “Considers the morality of using big data in the political sphere, covering cases from the Snowden leaks to the Brexit referendum

• Investigates theories and recommendations for how to align the modern political process with the exponential rise in the availability of digital information
• Opens new avenues for thinking about the philosophy and morality of social media, such as Facebook and Twitter, in the context of political decision-making
• Sets out and objectively assesses the ‘opacity’ framework as an appropriate means of dealing with the challenges associated with big data and democracy

What’s wrong with targeted advertising in political campaigns? Should we be worried about echo chambers? How does data collection impact on trust in society? As decision-making becomes increasingly automated, how can decision-makers be held to account? This collection consider potential solutions to these challenges. It brings together original research on the philosophy of big data and democracy from leading international authors, with recent examples – including the 2016 Brexit Referendum, the Leveson Inquiry and the Edward Snowden leaks. And it asks whether an ethical compass is available or even feasible in an ever more digitised and monitored world….(More)”.

Paper by Teresa M. Harrison and Luis Felipe Luna-Reyes: “While there is growing consensus that the analytical and cognitive tools of artificial intelligence (AI) have the potential to transform government in positive ways, it is also clear that AI challenges traditional government decision-making processes and threatens the democratic values within which they are framed. These conditions argue for conservative approaches to AI that focus on cultivating and sustaining public trust. We use the extended Brunswik lens model as a framework to illustrate the distinctions between policy analysis and decision making as we have traditionally understood and practiced them and how they are evolving in the current AI context along with the challenges this poses for the use of trustworthy AI. We offer a set of recommendations for practices, processes, and governance structures in government to provide for trust in AI and suggest lines of research that support them….(More)”.

Viewpoint by Dan Milz and Curt D. Gervich: “….The COVID-19 pandemic has paved the way for a multitude of experiments in e-democracy as local governments strive to continue to hold public meetings; make and implement plans; issue permits, variances and zoning decisions; and gather public input while under quarantine. This paper anecdotally discusses the role of online participatory technologies (OPTs) during this time.

Amidst the obvious impacts, COVID-19 also represents a threat to public participation. Because meeting in person is too risky, local leaders are cautious about hosting meetings in which citizens, government agents and elected officials gather together in one place. Consequently, municipal and county governments, among others, are taking the public’s business online. The purpose of this Viewpoint is to jump-start a conversation about how we prepare planners for a future in which in-person meetings are not guaranteed and how planners might continue to incorporate new technologies when face-to-face meetings resume….(More)”.

Nicole Gallucci at Mashable: “A lone hashtag might not look very mighty, but when used en masse, the symbols can become incredibly powerful activism tools.

Over the past two decades — largely since product designer Chris Messina pitched hashtags to Twitter in 2007 — activists have learned to harness the symbols to form online communities, raise awareness on pressing issues, organize protests, shape digital narratives, and redirect social media discourse. 

On any given day, a series of hashtags are spotlighted in “Trending” section of Twitter. The hashtags featured are those that have gained traction online and reflect topics being heavily discussed in the moment. More often than not, a trending hashtag’s popularity is organic, but a hashtag’s origin and initial purpose can become clouded when people partake in a clever tactic called hashtag flooding.

Hashtag flooding, or the act of hijacking a hashtag on social media platforms to change its meaning, has been around for years. But in 2020, particularly in the months leading up to the presidential election, activists and social media users looking to make their voices heard used the technique to drown out hateful narratives.

From K-pop fans flooding Donald Trump-related hashtags to members of the gay community putting their own spin on the #ProudBoys hashtag, the method of online communication dominated timelines this year and should be in every activist’s playbook….(More)”.

Introduction to Special Issue of the Journal of Representative Democracy by Alice el-Wakil & Spencer McKay: “Despite controversy over recent referendums and initiatives, populists and social movements continue to call for the use of these popular vote processes. Most political and academic debates about whether these calls should be answered have adopted a dominant framework that focuses on whether we should favour ‘direct’ or ‘representative’ democracy. However, this framework obscures more urgent questions about whether, when, and how popular vote processes should be implemented in democratic systems. How do popular vote processes interact with representative institutions? And how could these interactions be democratized? The contributions in this special issue address these and related questions by replacing the framework of ‘direct democracy’ with systemic approaches. The normative contributions illustrate how these approaches enable the development of counternarratives about the value of popular vote processes and clarify the nature of the underlying ideals they should realize. The empirical contributions examine recent cases with a variety of methodological tools, demonstrating that systemic approaches attentive to context can generate new insights about the use of popular vote processes. This introduction puts these contributions into conversation to illustrate how a shift in approach establishes a basis for (re-)evaluating existing practices and guiding reforms so that referendums and initiatives foster democracy….(More)”.

Hunton’s Privacy Blog: “On December 22, 2020, New York Governor Andrew Cuomo signed into law legislation that temporarily bans the use or purchase of facial recognition and other biometric identifying technology in public and private schools until at least July 1, 2022. The legislation also directs the New York Commissioner of Education (the “Commissioner”) to conduct a study on whether this technology is appropriate for use in schools.

In his press statement, Governor Cuomo indicated that the legislation comes after concerns were raised about potential risks to students, including issues surrounding misidentification by the technology as well as safety, security and privacy concerns. “This legislation requires state education policymakers to take a step back, consult with experts and address privacy issues before determining whether any kind of biometric identifying technology can be brought into New York’s schools. The safety and security of our children is vital to every parent, and whether to use this technology is not a decision to be made lightly,” the Governor explained.

Key elements of the legislation include:

• Defining “facial recognition” as “any tool using an automated or semi-automated process that assists in uniquely identifying or verifying a person by comparing and analyzing patterns based on the person’s face,” and “biometric identifying technology” as “any tool using an automated or semi-automated process that assists in verifying a person’s identity based on a person’s biometric information”;
• Prohibiting the purchase and use of facial recognition and other biometric identifying technology in all public and private elementary and secondary schools until July 1, 2022, or until the Commissioner authorizes the purchase and use of such technology, whichever occurs later; and
• Directing the Commissioner, in consultation with New York’s Office of Information Technology, Division of Criminal Justice Services, Education Department’s Chief Privacy Officer and other stakeholders, to conduct a study and make recommendations as to the circumstances in which facial recognition and other biometric identifying technology is appropriate for use in schools and what restrictions and guidelines should be enacted to protect privacy, civil rights and civil liberties interests….(More)”.

Mark Pesce at IEEE Spectrum: “First articulated in a 1965 white paper by Ivan Sutherland, titled “The Ultimate Display,” augmented reality (AR) lay beyond our technical capacities for 50 years. That changed when smartphones began providing people with a combination of cheap sensors, powerful processors, and high-bandwidth networking—the trifecta needed for AR to generate its spatial illusions. Among today’s emerging technologies, AR stands out as particularly demanding—for computational power, for sensed data, and, I’d argue, for attention to the danger it poses.

Unlike virtual-reality (VR) gear, which creates for the user a completely synthetic experience, AR gear adds to the user’s perception of her environment. To do that effectively, AR systems need to know where in space the user is located. VR systems originally used expensive and fragile systems for tracking user movements from the outside in, often requiring external sensors to be set up in the room. But the new generation of VR accomplishes this through a set of techniques collectively known as simultaneous localization and mapping (SLAM). These systems harvest a rich stream of observational data—mostly from cameras affixed to the user’s headgear, but sometimes also from sonar, lidar, structured light, and time-of-flight sensors—using those measurements to update a continuously evolving model of the user’s spatial environment.

For safety’s sake, VR systems must be restricted to certain tightly constrained areas, lest someone blinded by VR goggles tumble down a staircase. AR doesn’t hide the real world, though, so people can use it anywhere. That’s important because the purpose of AR is to add helpful (or perhaps just entertaining) digital illusions to the user’s perceptions. But AR has a second, less appreciated, facet: It also functions as a sophisticated mobile surveillance system.

This second quality is what makes Facebook’s recent Project Aria experiment so unnerving. Nearly four years ago, Mark Zuckerberg announced Facebook’s goal to create AR “spectacles”—consumer-grade devices that could one day rival the smartphone in utility and ubiquity. That’s a substantial technical ask, so Facebook’s research team has taken an incremental approach. Project Aria packs the sensors necessary for SLAM within a form factor that resembles a pair of sunglasses. Wearers collect copious amounts of data, which is fed back to Facebook for analysis. This information will presumably help the company to refine the design of an eventual Facebook AR product.

The concern here is obvious: When it comes to market in a few years, these glasses will transform their users into data-gathering minions for Facebook. Tens, then hundreds of millions of these AR spectacles will be mapping the contours of the world, along with all of its people, pets, possessions, and peccadilloes. The prospect of such intensive surveillance at planetary scale poses some tough questions about who will be doing all this watching and why….(More)”.

Open Access Book by RethinkX: “During the 2020s, key technologies will converge to completely disrupt the five foundational sectors that underpin the global economy, and with them every major industry in the world today. In information, energy, food, transportation, and materials, costs will fall by a 10x or more, while production processes an order of magnitude more efficient will use 90% fewer natural resources with 10x-100x less waste.

The knock-on effects for society will be as profound as the extraordinary possibilities that emerge. For the first time in history, we could overcome poverty easily. Access to all our basic needs could become a fundamental human right. But this is just one future outcome. The alternative could see our civilization collapse into a new dark age. Which path we take depends on the choices we make, starting today. The stakes could not be higher….(More)”.

Snigdha Poonam and Samarath Bansal at the Rest of the World: “…The black market for data, as it exists online in India, resembles those for wholesale vegetables or smuggled goods. Customers are encouraged to buy in bulk, and the variety of what’s on offer is mind-boggling: There are databases about parents, cable customers, pregnant women, pizza eaters, mutual funds investors, and almost any niche group one can imagine. A typical database consists of a spreadsheet with row after row of names and key details: Sheila Gupta, 35, lives in Kolkata, runs a travel agency, and owns a BMW; Irfaan Khan, 52, lives in Greater Noida, and has a son who just applied to engineering college. The databases are usually updated every three months (the older one is, the less it is worth), and if you buy several at the same time, you’ll get a discount. Business is always brisk, and transactions are conducted quickly. No one will ask you for your name, let alone inquire why you want the phone numbers of five million people who have applied for bank loans.

There isn’t a reliable estimate of the size of India’s data economy or of how much money it generates annually. Regarding the former, each broker we spoke to had a different guess: One said only about one or two hundred professionals make up the top tier, another that every big Indian city has at least a thousand people trading data. To find them, potential customers need only look for their ads on social media or run searches with industry keywords and hashtags — “data,” “leads,” “database” — combined with detailed information about the kind of data they want and the city they want it from.

Privacy experts believe that the data-brokering industry has existed since the early days of the internet’s arrival in India. “Databases have been bought and sold in India for at least 15 years now. I remember a case from way back in 2006 of leaked employee data from Naukri.com (one of India’s first online job portals) being sold on CDs,” says Nikhil Pahwa, the editor and publisher of MediaNama, which covers technology policy. By 2009, data brokers were running SMS-marketing companies that offered complementary services: procuring targeted data and sending text messages in bulk. Back then, there was simply less data, “and those who had it could sell it at whatever price,” says Himanshu Bhatt, a data broker who claims to be retired. That is no longer the case: “Today, everyone has every kind of data,” he said.

No broker we contacted would openly discuss their methods of hunting, harvesting, and selling data. But the day-to-day work generally consists of following the trails that people leave during their travels around the internet. Brokers trawl data storage websites armed with a digital fishing net. “I was shocked when I was surfing [cloud-hosted data sites] one day and came across Aadhaar cards,” Bhatt remarked, referring to India’s state-issued biometric ID cards. Images of them were available to download in bulk, alongside completed loan applications and salary sheets.

Again, the legal boundaries here are far from clear. Anybody who has ever filled out a form on a coupon website or requested a refund for a movie ticket has effectively entered their information into a database that can be sold without their consent by the company it belongs to. A neighborhood cell phone store can sell demographic information to a political party for hyperlocal campaigning, and a fintech company can stealthily transfer an individual’s details from an astrology app onto its own server, to gauge that person’s creditworthiness. When somebody shares employment history on LinkedIn or contact details on a public directory, brokers can use basic software such as web scrapers to extract that data.

But why bother hacking into a database when you can buy it outright? More often, “brokers will directly approach a bank employee and tell them, ‘I need the high-end database’,” Bhatt said. And as demand for information increases, so, too, does data vulnerability. A 2019 survey found that 69% of Indian companies haven’t set up reliable data security systems; 44% have experienced at least one breach already. “In the past 12 months, we have seen an increasing trend of Indians’ data [appearing] on the dark web,” says Beenu Arora, the CEO of the global cyberintelligence firm Cyble….(More)”.