相关论文: Increasing Data Equity Through Accessibility

Many recent technological advances (e.g. ChatGPT and search engines) are possible only because of massive amounts of user-generated data produced through user interactions with computing systems or scraped from the web (e.g. behavior logs,…

Along with the rapid development of information technology, the amount of information generated at a given time far exceeds human's ability to organize, search, and manipulate without the help of automatic systems. Now a days so many tools…

The increasing generation and collection of personal data has created a complex ecosystem, often collaborative but sometimes combative, around companies and individuals engaging in the use of these data. We propose that the interactions…

Recent research has helped to cultivate growing awareness that machine learning systems fueled by big data can create or exacerbate troubling disparities in society. Much of this research comes from outside of the practicing data science…

Social Media and the Internet have catalyzed an unprecedented potential for exposure to human diversity in terms of demographics, talents, opinions, knowledge, and the like. However, this potential has not come with new, much-needed,…

Modern healthcare domain incorporates a feature of digital accessibility to ensure seamless flow of online services for the patients. However, this feature of digital accessibility poses a challenge particularly for patients with…

Calls for heightened consideration of fairness and accountability in algorithmically-informed public decisions---like taxation, justice, and child protection---are now commonplace. How might designers support such human values? We…

This paper critically analyzes the National Science Foundation's Division of Equity for Excellence in STEM. While supporting its mission to broaden participation for underrepresented groups, the study finds current policies inadequate for…

Although there are various ways to represent data patterns and models, visualization has been primarily taught in many data science courses for its efficiency. Such vision-dependent output may cause critical barriers against those who are…

The Advancing Data Justice Research and Practice project aims to broaden understanding of the social, historical, cultural, political, and economic forces that contribute to discrimination and inequity in contemporary ecologies of data…

As testified by new regulations like the European AI act, the worries about the societal impact of (autonomous) software technologies are becoming of public concern. Social and human values, besides the traditional software behaviour and…

Data science has been described as the fourth paradigm for scientific discovery. The latest wave of data science research, pertaining to machine learning and artificial intelligence (AI), is growing exponentially and garnering millions of…

Accessibility research has grown substantially in the past few decades, yet there has been no literature review of the field. To understand current and historical trends, we created and analyzed a dataset of accessibility papers appearing…

Virtual collaboration has transformed how people in mixed-ability teams, composed of disabled and non-disabled people, work together by offering greater flexibility. In these settings, accessibility practices, such as accommodations and…

Recommendation, information retrieval, and other information access systems pose unique challenges for investigating and applying the fairness and non-discrimination concepts that have been developed for studying other machine learning…

Artificial Intelligence has the potential to exacerbate societal bias and set back decades of advances in equal rights and civil liberty. Data used to train machine learning algorithms may capture social injustices, inequality or…

Among the seven key requirements to achieve trustworthy AI proposed by the High-Level Expert Group on Artificial Intelligence (AI-HLEG) established by the European Commission (EC), the fifth requirement ("Diversity, non-discrimination and…

Accessible epidemiological data are of great value for emergency preparedness and response, understanding disease progression through a population, and building statistical and mechanistic disease models that enable forecasting. The status…

Open data is an emerging paradigm to share large and diverse datasets -- primarily from governmental agencies, but also from other organizations -- with the goal to enable the exploitation of the data for societal, academic, and commercial…

Across academia, government, and industry, data stewards are facing increasing pressure to make datasets more openly accessible for researchers while also protecting the privacy of data subjects. Differential privacy (DP) is one promising…