The field of artificial intelligence is moving towards a more human-centered approach, with a focus on designing AI systems that prioritize human relationships, empathy, and values. Researchers are exploring ways to leverage AI to facilitate human connection, rather than replacing or obscuring it. This shift is driven by the need to address the risks and challenges associated with AI, such as empathy fog, misinformation, and job displacement. Noteworthy papers in this area include: Toward Needs-Conscious Design, which introduces a human-centered framework for AI-mediated communication, and The AI Risk Spectrum, which maps the full spectrum of AI risks, from current harms to existential threats. These papers demonstrate the potential of AI to enhance human collaboration, improve learning outcomes, and promote AI literacy, while also highlighting the need for responsible AI development and deployment.
Human-Centered AI Developments
Sources
Toward Needs-Conscious Design: Co-Designing a Human-Centered Framework for AI-Mediated Communication
Generative AI in Training and Coaching: Redefining the Design Process of Learning Materials
Future progress in artificial intelligence: A survey of expert opinion
Are AI Machines Making Humans Obsolete?
The Stories We Govern By: AI, Risk, and the Power of Imaginaries
Sketchar: Supporting Character Design and Illustration Prototyping Using Generative AI
The Role of AI in Facilitating Interdisciplinary Collaboration: Evidence from AlphaFold
CAI Fluency: A Framework for Cybersecurity AI Fluency
The AI Risk Spectrum: From Dangerous Capabilities to Existential Threats
Sociotechnical Imaginaries of ChatGPT in Higher Education: The Evolving Media Discourse
Designing an Interdisciplinary Artificial Intelligence Curriculum for Engineering: Evaluation and Insights from Experts
Systematic Review Of Collaborative Learning Activities For Promoting AI Literacy
Mapping Students' AI Literacy Framing and Learning through Reflective Journals
GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Design