Opening the Scope of Openness in AI
The concept of openness in AI has so far been heavily inspired by the definition and community practice of open source software. This positions openness in AI as having positive connotations; it introduces assumptions of certain advantages, such as collaborative innovation and transparency. However, the practices and benefits of open source software are not fully transferable to AI, which has its own challenges. Framing a notion of openness tailored to AI is crucial to addressing its growing societal implications, risks, and capabilities. We argue that considering the fundamental scope of openness in different disciplines will broaden discussions, introduce important perspectives, and reflect on what openness in AI should mean. Toward this goal, we qualitatively analyze 98 concepts of openness discovered from topic modeling, through which we develop a taxonomy of openness. Using this taxonomy as an instrument, we situate the current discussion on AI openness, identify gaps and highlight links with other disciplines. Our work contributes to the recent efforts in framing openness in AI by reflecting principles and practices of openness beyond open source software and calls for a more holistic view of openness in terms of actions, system properties, and ethical objectives.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Trade Openness, Tariffs and Economic Growth: An Empirical Study from Countries of G-20
International trade has been in the forefront of economic development and growth debates. Trade openness, its definition, scope, and impacts have also been studied numerously. Tariff has been dubbed as negative influence…
regressionTowards a Framework for Openness in Foundation Models: Proceedings from the Columbia Convening on Openness in Artificial Intelligence
Over the past year, there has been a robust debate about the benefits and risks of open sourcing foundation models. However, this discussion has often taken place at a high level of generality or with a narrow focus on s…
DescriptiveDe facto Openness to Immigration
Various factors influence why some countries are more open to immigration than others. Policy is only one of them. We design country-specific measures of openness to immigration that aim to capture de facto levels of ope…
Opening up ChatGPT: Tracking openness, transparency, and accountability in instruction-tuned text generators
Large language models that exhibit instruction-following behaviour represent one of the biggest recent upheavals in conversational interfaces, a trend in large part fuelled by the release of OpenAI's ChatGPT, a proprieta…
FairnessInstruction FollowingLanguage ModelingLanguage Modelling+2PeeriScope: A Multi-Faceted Framework for Evaluating Peer Review Quality
The increasing scale and variability of peer review in scholarly venues has created an urgent need for systematic, interpretable, and extensible tools to assess review quality. We present PeeriScope, a modular platform t…