Paper by Oh-Hyun Kwon, Jisung Yoon, Lav R. Varshney, Woo-Sung Jung, Hyejin Youn: “We envision future technologies through science fiction, strategic planning, or academic research. Yet, our expectations do not always match with what actually unfolds, much like navigating a story where some events align with expectations while others surprise us. This gap indicates the inherent uncertainty of innovation-how technologies emerge and evolve in unpredictable ways. Here, we elaborate on this inherent uncertainty of innovation in the way technologies emerge and evolve. We define suspense captures accumulated uncertainty and describing events anticipated before their realization, while surprise represents a dramatic shift in understanding when an event occurs unexpectedly. We identify those connections in U.S. patents and show that suspenseful innovations tend to integrate more smoothly into society, achieving higher citations and market value. In contrast, surprising innovations, though often disruptive and groundbreaking, face challenges in adoption due to their extreme novelty. We further show that these categories allow us to identify distinct stages of technology life cycles, suggesting a way to identify the systematic trajectory of technologies and anticipate their future paths…(More)”.
Developing a Framework for Collective Data Rights
Report by Jeni Tennison: “Are collective data rights really necessary? Or, do people and communities already have sufficient rights to address harms through equality, public administration or consumer law? Might collective data rights even be harmful by undermining individual data rights or creating unjust collectivities? If we did have collective data rights, what should they look like? And how could they be introduced into legislation?
Data protection law and policy are founded on the notion of individual notice and consent, originating from the handling of personal data gathered for medical and scientific research. However, recent work on data governance has highlighted shortcomings with the notice-and-consent approach, especially in an age of big data and artificial intelligence. This special reports considers the need for collective data rights by examining legal remedies currently available in the United Kingdom in three scenarios where the people affected by algorithmic decision making are not data subjects and therefore do not have individual data protection rights…(More)”.
Un-Plateauing Corruption Research?Perhaps less necessary, but more exciting than one might think
Article by Dieter Zinnbauer: “There is a sense in the anti-corruption research community that we may have reached some plateau (or less politely, hit a wall). This article argues – at least partly – against this claim.
We may have reached a plateau with regard to some recurring (staid?) scholarly and policy debates that resurface with eerie regularity, tend to suck all oxygen out of the room, yet remain essentially unsettled and irresolvable. Questions aimed at arriving closure on what constitutes corruption, passing authoritative judgements on what works and what does not and rather grand pronouncements on whether progress has or has not been all fall into this category.
At the same time, there is exciting work often in unexpected places outside the inner ward of the anti-corruption castle, contributing new approaches and fresh-ish insights and there are promising leads for exciting research on the horizon. Such areas include the underappreciated idiosyncrasies of corruption in the form of inaction rather than action, the use of satellites and remote sensing techniques to better understand and measure corruption, the overlooked role of short-sellers in tackling complex forms of corporate corruption and the growing phenomena of integrity capture, the anti-corruption apparatus co-opted for sinister, corrupt purposes.
These are just four examples of the colourful opportunity tapestry for (anti)corruption research moving forward, not in form of a great unified project and overarching new idea but as little stabs of potentiality here and there and somewhere else surprisingly unbeknownst…(More)”
Reimagining data for Open Source AI: A call to action
Report by Open Source Initiative: “Artificial intelligence (AI) is changing the world at a remarkable pace, with Open Source AI playing a pivotal role in shaping its trajectory. Yet, as AI advances, a fundamental challenge emerges: How do we create a data ecosystem that is not only robust but also equitable and sustainable?
The Open Source Initiative (OSI) and Open Future have taken a significant step toward addressing this challenge by releasing a white paper: “Data Governance in Open Source AI: Enabling Responsible and Systematic Access.” This document is the culmination of a global co-design process, enriched by insights from a vibrant two-day workshop held in Paris in October 2024….
The white paper offers a blueprint for a data ecosystem rooted in fairness, inclusivity and sustainability. It calls for two transformative shifts:
- From Open Data to Data Commons: Moving beyond the notion of unrestricted data to a model that balances openness with the rights and needs of all stakeholders.
- Broadening the stakeholder universe: Creating collaborative frameworks that unite communities, stewards and creators in equitable data-sharing practices.
To bring these shifts to life, the white paper delves into six critical focus areas:
- Data preparation
- Preference signaling and licensing
- Data stewards and custodians
- Environmental sustainability
- Reciprocity and compensation
- Policy interventions…(More)”
Wikenigma – an Encyclopedia of Unknowns
About: “Wikenigma is a unique wiki-based resource specifically dedicated to documenting fundamental gaps in human knowledge.
Listing scientific and academic questions to which no-one, anywhere, has yet been able to provide a definitive answer. [ 1141 so far ]
That’s to say, a compendium of so-called ‘Known Unknowns’.
The idea is to inspire and promote interest in scientific and academic research by highlighting opportunities to investigate problems which no-one has yet been able to solve.
You can start browsing the content via the main menu on the left (or in the ‘Main Menu’ section if you’re using a small-screen device) Alternatively, the search box (above right) will find any articles with details that match your search terms…(More)”.
State of Digital Local Government
Report by the Local Government Association (UK): “This report is themed around four inter-related areas on the state of local government digital: market concentration, service delivery, technology, and delivery capabilities. It is particularly challenging to assess the current state of digital transformation in local government, given the diversity of experience, resources and lack of consistent data collection on digital transformation and technology estates.
This report is informed through our regular and extensive engagement with local government, primary research carried out by the LGA, and the research of stakeholders. It is worth noting that research on market concentration is challenging as it is a highly sensitive area.
Key messages:
- Local Government is a vital part of the public sector innovation ecosystem. Local government needs their priorities and context to be understood within cross public sector digital transformation ambitions through representation on public sector strategic boards and subsequently integrated into the design of public sector guidance and cross-government products at the earliest point. This will reduce the likelihood of duplication at public expense. Local government must also have equivalent access to training as civil servants…(More)”.
Nearly all Americans use AI, though most dislike it, poll shows
Axios: “The vast majority of Americans use products that involve AI, but their views of the technology remain overwhelmingly negative, according to a Gallup-Telescope survey published Wednesday.
Why it matters: The rapid advancement of generative AI threatens to have far-reaching consequences for Americans’ everyday lives, including reshaping the job market, impacting elections, and affecting the health care industry.
The big picture: An estimated 99% of Americans used at least one AI-enabled product in the past week, but nearly two-thirds didn’t realize they were doing so, according to the poll’s findings.
- These products included navigation apps, personal virtual assistants, weather forecasting apps, streaming services, shopping websites and social media platforms.
- Ellyn Maese, a senior research consultant at Gallup, told Axios that the disconnect is because there is “a lot of confusion when it comes to what is just a computer program versus what is truly AI and intelligent.”
Zoom in: Despite its prevalent use, Americans’ views of AI remain overwhelmingly bleak, the survey found.
- 72% of those surveyed had a “somewhat” or “very” negative opinion of how AI would impact the spread of false information, while 64% said the same about how it affects social connections.
- The only area where a majority of Americans (61%) had a positive view of AI’s impact was regarding how it might help medical diagnosis and treatment…
State of play: The survey found that 68% of Americans believe the government and businesses equally bear responsibility for addressing the spread of false information related to AI.
- 63% said the same about personal data privacy violations.
- Majorities of those surveyed felt the same about combatting the unauthorized use of individuals’ likenesses (62%) and AI’s impact on job losses (52%).
- In fact, the only area where Americans felt differently was when it came to national security threats; 62% of those surveyed said the government bore primary responsibility for reducing such threats…(More).”
Artificial Intelligence Narratives
A Global Voices Report: “…Framing AI systems as intelligent is further complicated and intertwined with neighboring narratives. In the US, AI narratives often revolve around opposing themes such as hope and fear, often bridging two strong emotions: existential fears and economic aspirations. In either case, they propose that the technology is powerful. These narratives contribute to the hype surrounding AI tools and their potential impact on society. Some examples include:
- An “AI arms race” between the United States and other global powers, particularly China.
- AI is a driver of economic growth and a transformative agent reshaping society.
- AI is a threat to labor.
- AI as a tool for good to benefit society.
- AI is an inevitable force that requires urgent regulation.
- If you don’t use AI, you will fall behind.
- AI is a democratizing force, lowering barriers to entry globally.
Many of these framings often present AI as an unstoppable and accelerating force. While this narrative can generate excitement and investment in AI research, it can also contribute to a sense of technological determinism and a lack of critical engagement with the consequences of widespread AI adoption. Counter-narratives are many and expand on the motifs of surveillance, erosions of trust, bias, job impacts, exploitation of labor, high-risk uses, the concentration of power, and environmental impacts, among others.
These narrative frames, combined with the metaphorical language and imagery used to describe AI, contribute to the confusion and lack of public knowledge about the technology. By positioning AI as a transformative, inevitable, and necessary tool for national success, these narratives can shape public opinion and policy decisions, often in ways that prioritize rapid adoption and commercialization…(More)”
Information Ecosystems and Troubled Democracy
Report by the Observatory on Information and Democracy: “This inaugural meta-analysis provides a critical assessment of the role of information ecosystems in the Global North and Global Majority World, focusing on their relationship with information integrity (the quality of public discourse), the fairness of political processes, the protection of media freedoms, and the resilience of public institutions.
The report addresses three thematic areas with a cross-cutting theme of mis- and disinformation:
- Media, Politics and Trust;
- Artificial Intelligence, Information Ecosystems and Democracy;
- and Data Governance and Democracy.
The analysis is based mainly on academic publications supplemented by reports and other materials from different disciplines and regions (1,664 citations selected among a total corpus of over +2700 resources aggregated). The report showcases what we can learn from landmark research on often intractable challenges posed by rapid changes in information and communication spaces…(More)”.
Generative Artificial Intelligence and Open Data: Guidelines and Best Practices
US Department of Commerce: “…This guidance provides actionable guidelines and best practices for publishing open data optimized for generative AI systems. While it is designed for use by the Department of Commerce and its bureaus, this guidance has been made publicly available to benefit open data publishers globally…(More)”. See also: A Fourth Wave of Open Data? Exploring the Spectrum of Scenarios for Open Data and Generative AI