The field of artificial intelligence is shifting towards the development of human-centered AI systems that prioritize social interaction, collaboration, and mutual understanding. Recent research has focused on designing AI systems that can facilitate meaningful interactions between humans, such as between parents and children, or between mentors and novices. These systems aim to provide proactive support, scaffolding, and guidance to enhance human collaboration and decision-making. Noteworthy papers in this area include: AI That Helps Us Help Each Other, which presents a human-AI coaching system for entrepreneurship coaching, and From Passive Tool to Socio-cognitive Teammate, which proposes a conceptual framework for agentic AI in human-AI collaborative learning. These innovative approaches highlight the potential of AI to transform various aspects of human life, from education and healthcare to social relationships and economic development.
Human-Centered AI Systems for Social Interaction and Collaboration
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Designing for Engaging Communication Between Parents and Young Adult Children Through Shared Music Experiences
Human-AI collaboration or obedient and often clueless AI in instruct, serve, repeat dynamics?
Families' Vision of Generative AI Agents for Household Safety Against Digital and Physical Threats
AI That Helps Us Help Each Other: A Proactive System for Scaffolding Mentor-Novice Collaboration in Entrepreneurship Coaching
Intergenerational Support for Deepfake Scams Targeting Older Adults
A Comprehensive Review of AI Agents: Transforming Possibilities in Technology and Beyond
Several Issues Regarding Data Governance in AGI
The Agent Behavior: Model, Governance and Challenges in the AI Digital Age
Challenges and Opportunities for Participatory Design of Conversational Agents for Young People's Wellbeing
From Passive Tool to Socio-cognitive Teammate: A Conceptual Framework for Agentic AI in Human-AI Collaborative Learning
Multilateralism in the Global Governance of Artificial Intelligence
Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems