Related papers: If open source is to win, it must go public
The introductory programming sequence has been the focus of much research in computing education. The recent advent of several viable and freely-available AI-driven code generation tools present several immediate opportunities and…
Artificial Intelligence (AI) systems are frequently employed in online services to provide personalized experiences to users based on large collections of data. However, AI systems can be designed in different ways, with black-box AI…
Like any technology, AI systems come with inherent risks and potential benefits. It comes with potential disruption of established norms and methods of work, societal impacts and externalities. One may think of the adoption of technology as…
Recent advances in artificial intelligence research have led to a profusion of studies that apply deep learning to problems in image analysis and natural language processing among others. Additionally, the availability of open-source…
Advancements in AI heavily rely on large-scale datasets meticulously curated and annotated for training. However, concerns persist regarding the transparency and context of data collection methodologies, especially when sourced through…
Artificial intelligence (AI) and digital public infrastructure (DPI) are two technological developments that have taken center stage in global policy discourse. Yet, to date, there has been relatively little discussion about how AI and DPI…
With the growing adoption of AI systems, reasoning about how society can exert control over AI becomes an increasingly urgent problem. Existing work on democratic control largely focuses on macro-level governance. In contrast, we propose a…
Despite conflicting definitions and conceptions of fairness, AI fairness researchers broadly agree that fairness is context-specific. However, when faced with general-purpose AI, which by definition serves a range of contexts, how should we…
The intense computational demands of AI, especially large foundation models, are driving a global boom in data centers. These facilities bring both tangible benefits and potential environmental burdens to local communities. However, the…
The opaqueness of many complex machine learning algorithms is often mentioned as one of the main obstacles to the ethical development of artificial intelligence (AI). But what does it mean for an algorithm to be opaque? Highly complex…
This paper presents elements that form the structure of a network of data using secure stable and mature technologies that meet the requirement of having code free. The principle would be conflicting code open Tuesday where he wants to keep…
Sustainable software ecosystems are difficult to build, and require concerted effort, community norms and collaborations. In science it is especially important to establish communities in which faculty, staff, students and open-source…
Despite the widespread use of artificial intelligence (AI), designing user experiences (UX) for AI-powered systems remains challenging. UX designers face hurdles understanding AI technologies, such as pre-trained language models, as design…
In the digital society's evolving landscape, open-source tooling and generative AI are pivotal in transforming global collaboration. These technologies promise to dismantle traditional barriers of accessibility, language, and governance,…
The use of artificial intelligence (AI) in the public sector is best understood as a continuation and intensification of long standing rationalization and bureaucratization processes. Drawing on Weber, we take the core of these processes to…
In order to evaluate, compare, and tune graph algorithms, experiments on well designed benchmark sets have to be performed. Together with the goal of reproducibility of experimental results, this creates a demand for a public archive to…
Many generative foundation models (or GFMs) are trained on publicly available data and use public infrastructure, but 1) may degrade the "digital commons" that they depend on, and 2) do not have processes in place to return value captured…
The rapid development of Artificial Intelligence (AI) technology has enabled the deployment of various systems based on it. However, many current AI systems are found vulnerable to imperceptible attacks, biased against underrepresented…
The promise of "free and open" multi-terabyte datasets often collides with harsh realities. While these datasets may be technically accessible, practical barriers -- from processing complexity to hidden costs -- create a system that…
Those best-positioned to profit from the proliferation of artificial intelligence (AI) systems are those with the most economic power. Extant global inequality has motivated Western institutions to involve more diverse groups in the…