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The development and deployment of artificial intelligence (AI) systems, with their profound societal impacts, raise critical challenges for governance. Historically, technological innovations have been governed by concentrated expertise…
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…
Synthetic images, audio, and video can now be generated and edited by Artificial Intelligence (AI). In particular, the malicious use of synthetic data has raised concerns about potential harms to cybersecurity, personal privacy, and public…
The responsible AI (RAI) community has introduced numerous processes and artifacts (e.g., Model Cards, Transparency Notes, Data Cards) to facilitate transparency and support the governance of AI systems. While originally designed to…
Advances in AI-generated content have led to wide adoption of large language models, diffusion-based visual generators, and synthetic audio tools. However, these developments raise critical concerns about misinformation, copyright…
Assessing fairness in artificial intelligence (AI) typically involves AI experts who select protected features, fairness metrics, and set fairness thresholds to assess outcome fairness. However, little is known about how stakeholders,…
The widespread adoption of Artificial Intelligence (AI) technologies in the public and private sectors has resulted in them significantly impacting the lives of people in new and unexpected ways. In this context, it becomes important to…
Generative Artificial Intelligence (AI) tools are increasingly deployed across social media platforms, yet their implications for user behavior and experience remain understudied, particularly regarding two critical dimensions: (1) how AI…
AI is transforming the existing technology landscape at a rapid phase enabling data-informed decision making and autonomous decision making. Unlike any other technology, because of the decision-making ability of AI, ethics and governance…
Governance institutions must respond to societal risks, including those posed by generative AI. This study empirically examines how public trust in institutions and AI technologies, along with perceived risks, shape preferences for AI…
AI agents that take actions in their environment autonomously over extended time horizons require robust governance interventions to curb their potentially consequential risks. Prior proposals for governing AI agents primarily target…
As public sector agencies rapidly introduce new AI tools in high-stakes domains like social services, it becomes critical to understand how decisions to adopt these tools are made in practice. We borrow from the anthropological practice to…
AI-generated media has become a threat to our digital society as we know it. These forgeries can be created automatically and on a large scale based on publicly available technology. Recognizing this challenge, academics and practitioners…
To realize the potential benefits and mitigate potential risks of AI, it is necessary to develop a framework of governance that conforms to ethics and fundamental human values. Although several organizations have issued guidelines and…
Recent developments in artificial intelligence (AI) have permeated through an array of different immersive environments, including virtual, augmented, and mixed realities. AI brings a wealth of potential that centers on its ability to…
Artificial Intelligence (AI) governance regulates the exercise of authority and control over the management of AI. It aims at leveraging AI through effective use of data and minimization of AI-related cost and risk. While topics such as AI…
As artificial intelligence transforms a wide range of sectors and drives innovation, it also introduces complex challenges concerning ethics, transparency, bias, and fairness. The imperative for integrating Responsible AI (RAI) principles…
As AI technologies become more human-facing, there have been numerous calls to adapt participatory approaches to AI development -- spurring the idea of participatory AI. However, these calls often focus only on primary stakeholders, such as…
The increasing integration of artificial intelligence (AI) in digital ecosystems has reshaped privacy dynamics, particularly for young digital citizens navigating data-driven environments. This study explores evolving privacy concerns…
The implementation of responsible AI in an organization is inherently complex due to the involvement of multiple stakeholders, each with their unique set of goals and responsibilities across the entire AI lifecycle. These responsibilities…