Technologies adopted by the public sector have transformed the work practices of employees in public agencies by creating different means of communication and decision-making. Although much of the recent research in the future of work domain has ...

Digital platforms have become central in job search. Job-seekers’ experiences with these platforms, however, is a relatively new research area. This paper presents findings from 27 interviews with US low-income job-seekers. Job-seekers encountered many ...

A large body of research has attempted to ensure that algorithmic systems adhere to notions of fairness and transparency. Increasingly, researchers have highlighted that mitigating algorithmic harms requires explicitly taking power structures into ...

As more algorithmic systems have come under scrutiny for their potential to inflict societal harms, an increasing number of organizations that hold power over harmful algorithms have chosen, or were required under the law, to abandon them. While social ...

The recent advancements in Large Language Models (LLMs) have significantly impacted numerous, and will impact more, real-world applications. However, these models also pose significant risks to individuals and society. To mitigate these issues and guide ...

In recent years, interest in directly involving end users in testing, auditing, and contesting AI systems has grown. The involvement of end users, especially from diverse backgrounds, can be essential to overcome AI developers’ blind spots and to ...

Youth regularly use technology driven by artificial intelligence (AI). However, it is increasingly well-known that AI can cause harm on small and large scales, especially for those underrepresented in tech fields. Recently, users have played active roles ...

An emerging body of research indicates that ineffective cross-functional collaboration – the interdisciplinary work done by industry practitioners across roles – represents a major barrier to addressing issues of fairness in AI design and development. ...

Recent years have witnessed an interesting phenomenon in which users come together to interrogate potentially harmful algorithmic behaviors they encounter in their everyday lives. Researchers have started to develop theoretical and empirical ...

Artificial intelligence (AI) literacy is especially important for those who may not be well-represented in technology design. We worked with ten Black girls in fifth and sixth grade from a predominantly Black school to understand their perceptions ...

Recent years have seen growing interest among both researchers and practitioners in user-engaged approaches to algorithm auditing, which directly engage users in detecting problematic behaviors in algorithmic systems. However, we know little about ...

Algorithmic systems help manage the governance of digital platforms featuring user-generated content, including how money is distributed to creators from the profits a platform earns from advertising on this content. However, creators producing content ...

Local governments use a wide array of software, algorithms, and data systems across domains such as policing, probation, child protective services, courts, education, public employment services, homelessness services, etc. A growing body of work in ...

Recent work in HCI suggests that users can be powerful in surfacing harmful algorithmic behaviors that formal auditing approaches fail to detect. However, it is not well understood how users are often able to be so effective, nor how we might support ...

How do power dynamics and value conflicts affect our ability to design and maintain socio-technical algorithmic processes? In this paper, we study the SIGCHI student volunteer (SV) selection process that uses a weighted semi-randomized algorithm to ...

A growing body of literature has proposed formal approaches to audit algorithmic systems for biased and harmful behaviors. While formal auditing approaches have been greatly impactful, they often suffer major blindspots, with critical issues surfacing ...

Algorithms in online platforms interact with users' identities in different ways. However, little is known about how users understand the interplay between identity and algorithmic processes on these platforms, and if and how such understandings shape ...

The power, opacity, and bias of algorithmic systems have opened up new research areas for bringing transparency, fairness, and accountability into these systems. In this talk, I will revisit these lines of work, and argue that while they are critical to ...

Algorithms exert great power in curating online information, yet are often opaque in their operation, and even existence. Since opaque algorithms sometimes make biased or deceptive decisions, many have called for increased transparency. However, little ...

Users frequently use search systems on the Web as well as online social media to learn about ongoing events and public opinion on personalities. Prior studies have shown that the top-ranked results returned by these search engines can shape user opinion ...