Explainable AI (XAI) is widely viewed as a sine qua non for ever-expanding AI research. A
better understanding of the needs of XAI users, as well as human-centered evaluations of …

The paper aims at establishing a common ground and understanding of collaborative
learning approaches between humans and computers to encourage Hybrid Intelligence …

Data scientists face a steep learning curve in understanding a new domain for which they
want to build machine learning (ML) models. While input from domain experts could offer …

Explainable AI is growing in importance as AI pervades modern society, but few have
studied how explainable AI can directly support people trying to assess an AI agent. Without …

Public sector institutions that consult citizens to inform decision-making face the challenge of
evaluating the contributions made by citizens. This evaluation has important democratic …

Since the advent of Artificial Intelligence (AI) and Machine Learning (ML), researchers have
asked how intelligent computing systems could interact with and relate to their users and …

The embodiment of Artificial Intelligence (AI) in everyday use products is raising challenges
and opportunities for HCI and design research, such as human understandings of AI's …

Chatbots have become an important part of the financial services ecosystem. To
accommodate their rise, many financial firms have turned to button-input interfaces that …

Human adoption of artificial intelligence (AI) technique is largely hampered because of the
increasing complexity and opacity of AI development. Explainable AI (XAI) techniques with …

Recent advancements in general-purpose AI have highlighted the importance of guiding AI
systems towards the intended goals, ethical principles, and values of individuals and …