Article by Anne Marte Gardenier, Rinie van Est & Lambèr Royakkers: “This article introduces an integrative framework for technological citizenship, examining the impact of digitization and the active roles of citizens in shaping this impact across the private, social, and public sphere. It outlines the dual nature of digitization, offering opportunities for enhanced connectivity and efficiency while posing challenges to privacy, security, and democratic integrity. Technological citizenship is explored through the lenses of liberal, communitarian, and republican theories, highlighting the active roles of citizens in navigating the opportunities and risks presented by digital technologies across all life spheres. By operationalizing technological citizenship, the article aims to address the gap in existing literature on the active roles of citizens in the governance of digitization. The framework emphasizes empowerment and resilience as crucial capacities for citizens to actively engage with and govern digital technologies. It illuminates citizens’ active participation in shaping the digital landscape, advocating for policies that support their engagement in safeguarding private, social, and public values in the digital age. The study calls for further research into technological citizenship, emphasizing its significance in fostering a more inclusive and equitable digital society…(More)”.
Artificial intelligence and complex sustainability policy problems: translating promise into practice
Paper by Ruby O’Connor et al: “Addressing sustainability policy challenges requires tools that can navigate complexity for better policy processes and outcomes. Attention on Artificial Intelligence (AI) tools and expectations for their use by governments have dramatically increased over the past decade. We conducted a narrative review of academic and grey literature to investigate how AI tools are being used and adapted for policy and public sector decision-making. We found that academics, governments, and consultants expressed positive expectations about AI, arguing that AI could or should be used to address a wide range of policy challenges. However, there is much less evidence of how public decision makers are actually using AI tools or detailed insight into the outcomes of use. From our findings we draw four lessons for translating the promise of AI into practice: 1) Document and evaluate AI’s application to sustainability policy problems in the real-world; 2) Focus on existing and mature AI technologies, not speculative promises or external pressures; 3) Start with the problem to be solved, not the technology to be applied; and 4) Anticipate and adapt to the complexity of sustainability policy problems…(More)”.
Automatic Generation of Model and Data Cards: A Step Towards Responsible AI
Paper by Jiarui Liu, Wenkai Li, Zhijing Jin, Mona Diab: “In an era of model and data proliferation in machine learning/AI especially marked by the rapid advancement of open-sourced technologies, there arises a critical need for standardized consistent documentation. Our work addresses the information incompleteness in current human-generated model and data cards. We propose an automated generation approach using Large Language Models (LLMs). Our key contributions include the establishment of CardBench, a comprehensive dataset aggregated from over 4.8k model cards and 1.4k data cards, coupled with the development of the CardGen pipeline comprising a two-step retrieval process. Our approach exhibits enhanced completeness, objectivity, and faithfulness in generated model and data cards, a significant step in responsible AI documentation practices ensuring better accountability and traceability…(More)”.
Digital Sovereignty: A Descriptive Analysis and a Critical Evaluation of Existing Models
Paper by Samuele Fratini et al: “Digital sovereignty is a popular yet still emerging concept. It is claimed by and related to various global actors, whose narratives are often competing and mutually inconsistent. Various scholars have proposed different descriptive approaches to make sense of the matter. We argue that existing works help advance our analytical understanding and that a critical assessment of existing forms of digital sovereignty is needed. Thus, the article offers an updated mapping of forms of digital sovereignty, while testing their effectiveness in response to radical changes and challenges. To do this, the article undertakes a systematic literature review, collecting 271 peer-reviewed articles from Google Scholar. They are used to identify descriptive features (how digital sovereignty is pursued) and value features (why digital sovereignty is pursued), which are then combined to produce four models: the rights-based model, market-oriented model, centralisation model, and state-based model. We evaluate their effectiveness within a framework of robust governance that accounts for the models’ ability to absorb the disruptions caused by technological advancements, geopolitical changes, and evolving societal norms. We find that none of the available models fully combines comprehensive regulations of digital technologies with a sufficient degree of responsiveness to fast-paced technological innovation and social and economic shifts. However, each offers valuable lessons to policymakers who wish to implement an effective and robust form of digital sovereignty…(More)”.
The Age of AI Nationalism and its Effects
Paper by Susan Ariel Aaronson: “This paper aims to illuminate how AI nationalistic policies may backfire. Over time, such actions and policies could alienate allies and prod other countries to adopt “beggar-thy neighbor” approaches to AI (The Economist: 2023; Kim: 2023 Shivakumar et al. 2024). Moreover, AI nationalism could have additional negative spillovers over time. Many AI experts are optimistic about the benefits of AI, whey they are aware of its many risks to democracy, equity, and society. They understand that AI can be a public good when it is used to mitigate complex problems affecting society (Gopinath: 2023; Okolo: 2023). However, when policymakers take steps to advance AI within their borders, they may — perhaps without intending to do so – make it harder for other countries with less capital, expertise, infrastructure, and data prowess to develop AI systems that could meet the needs of their constituents. In so doing, these officials could undermine the potential of AI to enhance human welfare and impede the development of more trustworthy AI around the world. (Slavkovik: 2024; Aaronson: 2023; Brynjolfsson and Unger: 2023; Agrawal et al. 2017).
Governments have many means of nurturing AI within their borders that do not necessarily discriminate between foreign and domestic producers of AI. Nevertheless, officials may be under pressure from local firms to limit the market power of foreign competitors. Officials may also want to use trade (for example, export controls) as a lever to prod other governments to change their behavior (Buchanan: 2020). Additionally, these officials may be acting in what they believe is the nation’s national security interest, which may necessitate that officials rely solely on local suppliers and local control. (GAO: 2021)
Herein the author attempts to illuminate AI nationalism and its consequences by answering 3 questions:
• What are nations doing to nurture AI capacity within their borders?
• Are some of these actions trade distorting?
• What are the implications of such trade-distorting actions?…(More)”
Learning from Ricardo and Thompson: Machinery and Labor in the Early Industrial Revolution, and in the Age of AI
Paper by Daron Acemoglu & Simon Johnson: “David Ricardo initially believed machinery would help workers but revised his opinion, likely based on the impact of automation in the textile industry. Despite cotton textiles becoming one of the largest sectors in the British economy, real wages for cotton weavers did not rise for decades. As E.P. Thompson emphasized, automation forced workers into unhealthy factories with close surveillance and little autonomy. Automation can increase wages, but only when accompanied by new tasks that raise the marginal productivity of labor and/or when there is sufficient additional hiring in complementary sectors. Wages are unlikely to rise when workers cannot push for their share of productivity growth. Today, artificial intelligence may boost average productivity, but it also may replace many workers while degrading job quality for those who remain employed. As in Ricardo’s time, the impact of automation on workers today is more complex than an automatic linkage from higher productivity to better wages…(More)”.
Complexity and the Global Governance of AI
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