Paper by Gordon LaForge et al: “In the coming years, advanced artificial intelligence (AI) systems are expected to bring significant benefits and risks for humanity. Many governments, companies, researchers, and civil society organizations are proposing, and in some cases, building global governance frameworks and institutions to promote AI safety and beneficial development. Complexity thinking, a way of viewing the world not just as discrete parts at the macro level but also in terms of bottom-up and interactive complex adaptive systems, can be a useful intellectual and scientific lens for shaping these endeavors. This paper details how insights from the science and theory of complexity can aid understanding of the challenges posed by AI and its potential impacts on society. Given the characteristics of complex adaptive systems, the paper recommends that global AI governance be based on providing a fit, adaptive response system that mitigates harmful outcomes of AI and enables positive aspects to flourish. The paper proposes components of such a system in three areas: access and power, international relations and global stability; and accountability and liability…(More)”
The case for global governance of AI: arguments, counter-arguments, and challenges ahead
Paper by Mark Coeckelbergh: “But why, exactly, is global governance needed, and what form can and should it take? The main argument for the global governance of AI, which is also applicable to digital technologies in general, is essentially a moral one: as AI technologies become increasingly powerful and influential, we have the moral responsibility to ensure that it benefits humanity as a whole and that we deal with the global risks and the ethical and societal issues that arise from the technology, including privacy issues, security and military uses, bias and fairness, responsibility attribution, transparency, job displacement, safety, manipulation, and AI’s environmental impact. Since the effects of AI cross borders, so the argument continues, global cooperation and global governance are the only means to fully and effectively exercise that moral responsibility and ensure responsible innovation and use of technology to increase the well-being for all and preserve peace; national regulation is not sufficient….(More)”.
A Literature Review on the Paradoxes of Public Interest in Spatial Planning within Urban Settings with Diverse Stakeholders
Paper by Danai Machakaire and Masilonyane Mokhele: “The concept of public interest legitimises the planning profession, provides a foundational principle, and serves as an ethical norm for planners. However, critical discourses highlight the problems of the assumptions underlying the notion of public interest in spatial planning. Using an explorative literature review approach, the article aims to analyse various interpretations and applications of public interest in spatial planning. The literature search process, conducted between August and November 2023, targeted journal articles and books published in English and focused on the online databases of Academic Search Premier, Scopus, and Google Scholar. The final selected literature comprised 71 sources. The literature showed that diverse conceptualisations of public interest complicate the ways spatial planners and authorities incorporate it in planning tools, processes, and products. This article concludes by arguing that the prospects of achieving a single definition of the public interest concept are slim and may not be necessary given the heterogeneous conceptualisation and the multiple operational contexts of public interest. The article recommends the development of context-based analytical frameworks to establish linkages that would lead towards the equitable inclusion of public interest in spatial planning…(More)”.
Murky Consent: An Approach to the Fictions of Consent in Privacy Law
Paper by Daniel J. Solove: “Consent plays a profound role in nearly all privacy laws. As Professor Heidi Hurd aptly said, consent works “moral magic” – it transforms things that would be illegal and immoral into lawful and legitimate activities. As to privacy, consent authorizes and legitimizes a wide range of data collection and processing.
There are generally two approaches to consent in privacy law. In the United States, the notice-and-choice approach predominates; organizations post a notice of their privacy practices and people are deemed to consent if they continue to do business with the organization or fail to opt out. In the European Union, the General Data Protection Regulation (GDPR) uses the express consent approach, where people must voluntarily and affirmatively consent.
Both approaches fail. The evidence of actual consent is non-existent under the notice-and-choice approach. Individuals are often pressured or manipulated, undermining the validity of their consent. The express consent approach also suffers from these problems – people are ill-equipped to decide about their privacy, and even experts cannot fully understand what algorithms will do with personal data. Express consent also is highly impractical; it inundates individuals with consent requests from thousands of organizations. Express consent cannot scale.
In this Article, I contend that most of the time, privacy consent is fictitious. Privacy law should take a new approach to consent that I call “murky consent.” Traditionally, consent has been binary – an on/off switch – but murky consent exists in the shadowy middle ground between full consent and no consent. Murky consent embraces the fact that consent in privacy is largely a set of fictions and is at best highly dubious….(More)”. See also: The Urgent Need to Reimagine Data Consent
Automated Social Science: Language Models as Scientist and Subjects
Paper by Benjamin S. Manning, Kehang Zhu & John J. Horton: “We present an approach for automatically generating and testing, in silico, social scientific hypotheses. This automation is made possible by recent advances in large language models (LLM), but the key feature of the approach is the use of structural causal models. Structural causal models provide a language to state hypotheses, a blueprint for constructing LLM-based agents, an experimental design, and a plan for data analysis. The fitted structural causal model becomes an object available for prediction or the planning of follow-on experiments. We demonstrate the approach with several scenarios: a negotiation, a bail hearing, a job interview, and an auction. In each case, causal relationships are both proposed and tested by the system, finding evidence for some and not others. We provide evidence that the insights from these simulations of social interactions are not available to the LLM purely through direct elicitation. When given its proposed structural causal model for each scenario, the LLM is good at predicting the signs of estimated effects, but it cannot reliably predict the magnitudes of those estimates. In the auction experiment, the in silico simulation results closely match the predictions of auction theory, but elicited predictions of the clearing prices from the LLM are inaccurate. However, the LLM’s predictions are dramatically improved if the model can condition on the fitted structural causal model. In short, the LLM knows more than it can (immediately) tell…(More)”.
Democratic innovations beyond the deliberative paradigm
Paper by Christian Opitz: “The current research on deliberative-participatory democratic innovations conducted by state administration agencies exhibits empirical eclecticism and is dominated by a deliberative paradigm. However, this paradigm tends to conflate normative prescription with analytical description. In contrast, this article proposes a comprehensive re-conceptualization of such innovations, drawing from Niklas Luhmann’s systems theory. It outlines the specific problem these innovations address (function), how they operate in tackling this problem (functioning) and the problems they inevitably raise (dysfunctions). In addition, my re-conceptualization retains the possibility to critically compare these (and other) experiments regarding their capability to address emerging challenges within the modern democratic political system…(More)”.
On the Manipulation of Information by Governments
Paper by Ariel Karlinsky and Moses Shayo: “Governmental information manipulation has been hard to measure and study systematically. We hand-collect data from official and unofficial sources in 134 countries to estimate misreporting of Covid mortality during 2020-21. We find that between 45%–55% of governments misreported the number of deaths. The lion’s share of misreporting cannot be attributed to a country’s capacity to accurately diagnose and report deaths. Contrary to some theoretical expectations, there is little evidence of governments exaggerating the severity of the pandemic. Misreporting is higher where governments face few social and institutional constraints, in countries holding elections, and in countries with a communist legacy…(More)”
Technological Progress and Rent Seeking
Paper by Vincent Glode & Guillermo Ordoñez: “We model firms’ allocation of resources across surplus-creating (i.e., productive) and surplus-appropriating (i.e., rent-seeking) activities. Our model predicts that industry-wide technological advancements, such as recent progress in data collection and processing, induce a disproportionate and socially inefficient reallocation of resources toward surplus-appropriating activities. As technology improves, firms rely more on appropriation to obtain their profits, endogenously reducing the impact of technological progress on economic progress and inflating the price of the resources used for both types of activities. We apply our theoretical insights to shed light on the rise of high-frequency trading…(More)”,
Crowdsourcing for collaborative crisis communication: a systematic review
Paper by Maria Clara Pestana, Ailton Ribeiro and Vaninha Vieira: “Efficient crisis response and support during emergency scenarios rely on collaborative communication channels. Effective communication between operational centers, civilian responders, and public institutions is vital. Crowdsourcing fosters communication and collaboration among a diverse public. The primary objective is to explore the state-of-the-art in crowdsourcing for collaborative crisis communication guided by a systematic literature review. The study selected 20 relevant papers published in the last decade. The findings highlight solutions to facilitate rapid emergency responses, promote seamless coordination between stakeholders and the general public, and ensure data credibility through a rigorous validation process…(More)”.
Global Contract-level Public Procurement Dataset
Paper by Mihály Fazekas et al: “One-third of total government spending across the globe goes to public procurement, amounting to about 10 trillion dollars a year. Despite its vast size and crucial importance for economic and political developments, there is a lack of globally comparable data on contract awards and tenders run. To fill this gap, this article introduces the Global Public Procurement Dataset (GPPD). Using web scraping methods, we collected official public procurement data on over 72 million contracts from 42 countries between 2006 and 2021 (time period covered varies by country due to data availability constraints). To overcome the inconsistency of data publishing formats in each country, we standardized the published information to fit a common data standard. For each country, key information is collected on the buyer(s) and supplier(s), geolocation information, product classification, price information, and details of the contracting process such as contract award date or the procedure type followed. GPPD is a contract-level dataset where specific filters are calculated allowing to reduce the dataset to the successfully awarded contracts if needed. We also add several corruption risk indicators and a composite corruption risk index for each contract which allows for an objective assessment of risks and comparison across time, organizations, or countries. The data can be reused to answer research questions dealing with public procurement spending efficiency among others. Using unique organizational identification numbers or organization names allows connecting the data to company registries to study broader topics such as ownership networks…(More)”.