相关论文: Why Companies "Democratise" Artificial Intelligenc…
Artificial Intelligence for Social Good (AI4SG) has emerged as a growing body of research and practice exploring the potential of AI technologies to tackle social issues. This area emphasizes interdisciplinary partnerships with community…
Artificial intelligence (AI) has widespread societal implications, yet social scientists are only beginning to study public attitudes toward the technology. Existing studies find that the public's trust in institutions can play a major role…
Activists, journalists, and scholars have long raised critical questions about the relationship between diversity, representation, and structural exclusions in data-intensive tools and services. We build on work mapping the emergent…
As Artificial Intelligence (AI) technologies proliferate, concern has centered around the long-term dangers of job loss or threats of machines causing harm to humans. All of this concern, however, detracts from the more pertinent and…
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 explores the economic underpinnings of open sourcing advanced large language models (LLMs) by for-profit companies. Empirical analysis reveals that: (1) LLMs are compatible with R&D portfolios of numerous technologically…
Increasingly, laws are being proposed and passed by governments around the world to regulate Artificial Intelligence (AI) systems implemented into the public and private sectors. Many of these regulations address the transparency of AI…
Artificial intelligence functions not as an epistemic leveller, but as an accelerant of cognitive stratification, entrenching and formalising informational castes within liberal-democratic societies. Synthesising formal epistemology,…
Recent decisions by leading AI labs to either open-source their models or to restrict access to their models has sparked debate about whether, and how, increasingly capable AI models should be shared. Open-sourcing in AI typically refers to…
Today, AI is increasingly being used in many high-stakes decision-making applications in which fairness is an important concern. Already, there are many examples of AI being biased and making questionable and unfair decisions. The AI…
AI progress is creating a growing range of risks and opportunities, but it is often unclear how they should be navigated. In many cases, the barriers and uncertainties faced are at least partly technical. Technical AI governance, referring…
The emergence and growth of research on issues of ethics in AI, and in particular algorithmic fairness, has roots in an essential observation that structural inequalities in society are reflected in the data used to train predictive models…
Open Source Software (OSS) communities often resist regulation typical of traditional organizations. Yet formal governance systems are being increasingly adopted among communities, particularly through non-profit mentor foundations. Our…
With the advent of the Data Age, organisations are constantly under pressure to pay attention to the diffusion of data skills, data responsibilities, and management of accessibility to data analysis tools for the technical as well as…
Regulations govern many aspects of citizens' daily lives. Governments and businesses routinely automate these in the form of coded rules (e.g., to check a citizen's eligibility for specific benefits). However, the path to automation is long…
The AI for social good movement has now reached a state in which a large number of one-off demonstrations have illustrated that partnerships of AI practitioners and social change organizations are possible and can address problems faced in…
Artificial Intelligence (AI) is a field that utilizes computing and often, data and statistics, intensively together to solve problems or make predictions. AI has been evolving with literally unbelievable speed over the past few years, and…
DevOps and Artificial Intelligence (AI) are interconnected with each other. DevOps is a business-driven approach to providing quickly delivered quality software, and AI is the technology that can be used in the system to enhance its…
Artificial intelligence (AI) is now ubiquitous in our lives, and we regularly experience its decisions. Yet, the general public has very little knowledge about how it works, its use of data, its lack of objectivity, and its fallibility. In…
Background: The development of AI-enabled software heavily depends on AI model documentation, such as model cards, due to different domain expertise between software engineers and model developers. From an ethical standpoint, AI model…