The rise of powerful large language models (LLMs) brings about tremendou...
The recent development of generative and large language models (LLMs) po...
We address the fundamental challenge in Natural Language Generation (NLG...
Data storytelling plays an important role in data workers' daily jobs si...
Qualitative analysis of textual contents unpacks rich and valuable
infor...
With the heightened digitization of the workplace, alongside the rise of...
To design with AI models, user experience (UX) designers must assess the...
Despite the widespread use of artificial intelligence (AI), designing us...
In recent years, the CHI community has seen significant growth in resear...
Large-scale generative models enabled the development of AI-powered code...
During a public health crisis like the COVID-19 pandemic, a credible and...
While a vast collection of explainable AI (XAI) algorithms have been
dev...
AI explanations are often mentioned as a way to improve human-AI
decisio...
Mistakes in AI systems are inevitable, arising from both technical
limit...
Recent years have seen a surge of interest in the field of explainable A...
Current literature and public discourse on "trust in AI" are often focus...
Despite impressive performance in many benchmark datasets, AI models can...
What does it mean for a generative AI model to be explainable? The emerg...
As AI systems demonstrate increasingly strong predictive performance, th...
As a technical sub-field of artificial intelligence (AI), explainable AI...
As artificial intelligence and machine learning algorithms become
increa...
Explainability of AI systems is critical for users to take informed acti...
In this paper, we describe an open source Python toolkit named Uncertain...
Automated Machine Learning (AutoML) is a rapidly growing set of technolo...
A pervasive design issue of AI systems is their explainability–how to
pr...
Given that there are a variety of stakeholders involved in, and affected...
Data scientists face a steep learning curve in understanding a new domai...
As AI-powered systems increasingly mediate consequential decision-making...
Data science and machine learning (DS/ML) are at the heart of the recent...
Transparency of algorithmic systems entails exposing system properties t...
We propose a new active learning (AL) framework, Active Learning++, whic...
Social biases based on gender, race, etc. have been shown to pollute mac...
Active Learning (AL) is a human-in-the-loop Machine Learning paradigm fa...
A surge of interest in explainable AI (XAI) has led to a vast collection...
Today, AI is being increasingly used to help human experts make decision...
Two general routes have been followed to develop artificial agents that ...
As artificial intelligence and machine learning algorithms make further
...
The rise of increasingly more powerful chatbots offers a new way to coll...
Ensuring fairness of machine learning systems is a human-in-the-loop pro...
Many conversational agents in the market today follow a standard bot
dev...
Dialog is a natural modality for interaction between customers and busin...