Contributing to Accessibility Datasets: Reflections on Sharing Study Data by Blind People
Abstrak
To ensure that AI-infused systems work for disabled people, we need to bring accessibility datasets sourced from this community in the development lifecycle. However, there are many ethical and privacy concerns limiting greater data inclusion, making such datasets not readily available. We present a pair of studies where 13 blind participants engage in data capturing activities and reflect with and without probing on various factors that influence their decision to share their data via an AI dataset. We see how different factors influence blind participants’ willingness to share study data as they assess risk-benefit tradeoffs. The majority support sharing of their data to improve technology but also express concerns over commercial use, associated metadata, and the lack of transparency about the impact of their data. These insights have implications for the development of responsible practices for stewarding accessibility datasets, and can contribute to broader discussions in this area.
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Leah Findlater Kelly Avery Mack Jon E. Froehlich + 3 lainnya
12 Januari 2021
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 at CHI and ASSETS since ASSETS’ founding in 1994. We qualitatively coded areas of focus and methodological decisions for the past 10 years (2010-2019, N=506 papers), and analyzed paper counts and keywords over the full 26 years (N=836 papers). Our findings highlight areas that have received disproportionate attention and those that are underserved—for example, over 43% of papers in the past 10 years are on accessibility for blind and low vision people. We also capture common study characteristics, such as the roles of disabled and nondisabled participants as well as sample sizes (e.g., a median of 13 for participant groups with disabilities and older adults). We close by critically reflecting on gaps in the literature and offering guidance for future work in the field.
Jaylin Herskovitz Robin Brewer Rahaf Alharbi + 2 lainnya
13 Agustus 2024
Blind people use artificial intelligence-enabled visual assistance technologies (AI VAT) to gain visual access in their everyday lives, but these technologies are embedded with errors that may be difficult to verify non-visually. Previous studies have primarily explored sighted users' understanding of AI output and created vision-dependent explainable AI (XAI) features. We extend this body of literature by conducting an in-depth qualitative study with 26 blind people to understand their verification experiences and preferences. We begin by describing errors blind people encounter, highlighting how AI VAT fails to support complex document layouts, diverse languages, and cultural artifacts. We then illuminate how blind people make sense of AI through experimenting with AI VAT, employing non-visual skills, strategically including sighted people, and cross-referencing with other devices. Participants provided detailed opportunities for designing accessible XAI, such as affordances to support contestation. Informed by disability studies framework of misfitting and fitting, we unpacked harmful assumptions with AI VAT, underscoring the importance of celebrating disabled ways of knowing. Lastly, we offer practical takeaways for Responsible AI practice to push the field of accessible XAI forward.
Bongshin Lee Kathleen F. McCoy Edward Cutrell + 6 lainnya
27 April 2021
driven communication by business, government, and science. Furthermore, the use and need for visualizations is not just confined to data experts: Data visualizations are becoming ubiquitous in textbooks, presentations, and reports, as well as in popular media, both online and in print. The design of these visualizations, however, is premised on implicit assumptions about the reader's sensory, cognitive, and motor abilities. People without these abilities are ultimately disenfranchised, and access to the benefits of data visualization and to the underlying information is limited. Data visualizations, such as statistical charts, diagrams, and maps, are an effective means to represent, analyze, and explore data as well as identify and communicate insights. They take advantage of the human visual system’s high bandwidth, parallel processing, and ability to quickly recognize patterns. For instance, a table of numbers may be hard to understand, while those same numbers shown in a graphic form (such as a line chart) will immediately reveal a steadily increasing trend. For these reasons, interactive data visualization is central to both exploratory data analysis and dataD Insights → Lack of accessible access to data visualizations is a significant equity issue. → It's not only visual impairments that can restrict access but also other kinds of disabilities including cognitive and learning disabilities, and motor disabilities. → Overcoming this challenge requires visualization practitioners, visualization and accessibility researchers, and the relevant disability communities to work together.
E. J. Edwards Isabela Figueira Joshua Garcia + 4 lainnya
11 Mei 2024
Scholars have investigated numerous barriers to accessible software development tools and processes for Blind and Low Vision (BLV) developers. However, the research community has yet to study the accessibility of software development meetings, which are known to play a crucial role in software development practice. We conducted semi-structured interviews with 26 BLV software professionals about software development meeting accessibility. We found four key themes related to in-person and remote software development meetings: (1) participants observed that certain meeting activities and software tools used in meetings were inaccessible, (2) participants performed additional labor in order to make meetings accessible, (3) participants avoided disclosing their disability during meetings due to fear of career repercussions, (4) participants suggested technical, social and organizational solutions for accessible meetings, including developing their own solutions. We suggest recommendations and design implications for future accessible software development meetings including technical and policy-driven solutions.
Ingrid Teixeira Monteiro Erik Henrique Da Costa Nunes Enyo Gonçalves + 1 lainnya
16 Oktober 2023
In 2015, Brazil enacted Law No. 13,146 (Statute of Persons with Disabilities), establishing a new range of rights for people with disabilities. Among the changes made was the inclusion of good practices in the concept of accessibility, including the digital realm. This paper presents the results of a Systematic Literature Review regarding the works presented at the Brazilian Symposium on Human Factors in Computing Systems from 2016 to 2022, with the aim of evaluating the impact of Digital Accessibility initiatives after the enactment of the mentioned law. The objective is to reveal part of the event’s history, highlighting the needs imposed by the law. The study analyzed 406 papers from the event deposited in the ACM Digial Library, selecting 91 of them (22.4%). The results showed that visual impairment is the most addressed theme, present in 33 papers (36.2%). Also, there are 254 different researchers working on this topic in Brazil and other countries. Surprisingly, only 21 (23%) of the papers mention any laws, showing that there is neglect or lack of knowledge regarding Brazilian laws on accessibility.
Daftar Referensi
2 referensiSix Human-Centered Artificial Intelligence Grand Challenges
Joe Kider Sean Koon + 25 lainnya
2 Januari 2023
Abstract Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the human condition in ways that are not yet well understood. Negative unintended consequences abound including the perpetuation and exacerbation of societal inequalities and divisions via algorithmic decision making. We present six grand challenges for the scientific community to create AI technologies that are human-centered, that is, ethical, fair, and enhance the human condition. These grand challenges are the result of an international collaboration across academia, industry and government and represent the consensus views of a group of 26 experts in the field of human-centered artificial intelligence (HCAI). In essence, these challenges advocate for a human-centered approach to AI that (1) is centered in human well-being, (2) is designed responsibly, (3) respects privacy, (4) follows human-centered design principles, (5) is subject to appropriate governance and oversight, and (6) interacts with individuals while respecting human’s cognitive capacities. We hope that these challenges and their associated research directions serve as a call for action to conduct research and development in AI that serves as a force multiplier towards more fair, equitable and sustainable societies.
Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy
B. Shneiderman
10 Februari 2020
ABSTRACT Well-designed technologies that offer high levels of human control and high levels of computer automation can increase human performance, leading to wider adoption. The Human-Centered Artificial Intelligence (HCAI) framework clarifies how to (1) design for high levels of human control and high levels of computer automation so as to increase human performance, (2) understand the situations in which full human control or full computer control are necessary, and (3) avoid the dangers of excessive human control or excessive computer control. The methods of HCAI are more likely to produce designs that are Reliable, Safe & Trustworthy (RST). Achieving these goals will dramatically increase human performance, while supporting human self-efficacy, mastery, creativity, and responsibility.