AI and ML models have already found many applications in critical domains, such as healthcare and criminal justice. However, fully automating such high-stakes applications can raise ethical or fairness concerns. Instead, in such cases, humans should be assisted by automated … Continued
The disruptive potential of AI systems roots in the emergence of big data. Yet, a significant portion is scattered and locked in data silos, leaving its potential untapped. Federated Machine Learning is a novel AI paradigm enabling the creation of … Continued
In AI-assisted decision-making, a central promise of putting a human in the loop is that they should be able to complement the AI system by adhering to its correct and overriding its mistaken recommendations. In practice, however, we often see … Continued
User trust in Artificial Intelligence (AI) enabled systems has been increasingly recognized and proven as a key element to fostering adoption. It has been suggested that AI-enabled systems must go beyond technical-centric approaches and towards embracing a more human centric … Continued
Data storytelling plays an important role in data workers’ daily jobs since it boosts team collaboration and public communication. However, to make an appealing data story, data workers spend tremendous efforts on various tasks, including outlining and styling the story. … Continued
HTC PhD Candidate, Jessa Henderson and 1st author, and HTC faculty Natalie Milman (along w/ 2 other colleagues at other universities) were awarded the 2023 American Educational Research Association Technology as an Agent of Change in Teaching and Learning SIG’s … Continued
cims.nyu.edu The widespread public deployment of large language models (LLMs) in recent months has prompted a wave of new attention and engagement from advocates, policymakers, and scholars from many fields. This attention is a timely response to the many urgent … Continued
Intersectionality is a critical framework that, through inquiry and praxis, allows us to examine how social inequalities persist through domains of structure and discipline. Given AI fairness’ raison d’être of “fairness,” we argue that adopting intersectionality as an analytical framework … Continued
Computer science research has led to many breakthrough innovations but has also been scrutinized for enabling technology that has negative, unintended consequences for society. Given the increasing discussions of ethics in the news and among researchers, we interviewed 20 researchers … Continued
The rapid proliferation of advanced AI chatbots and large language models (LLMs), such as ChatGPT, have coincided with increased calls to use psychological tools to understand how people perceive interactions with these AI systems. Decades of research into how people … Continued