The field of human-AI collaboration and decision making is rapidly evolving, with a growing focus on developing more effective and responsible ways to integrate AI systems into human decision-making processes. Recent research has highlighted the importance of considering the social and cultural contexts in which AI systems are used, as well as the need to develop more nuanced and contextualized understandings of human-AI interaction. One key area of innovation is in the development of adaptive visualization systems that can respond to users' cognitive states and provide more effective support for decision making. Another area of advancement is in the development of more sophisticated models of human-AI collaboration, including the use of personality-based pairing and bidirectional fit to improve teamwork quality and productivity. Noteworthy papers in this area include 'Person-AI Bidirectional Fit' and 'Personality Pairing Improves Human-AI Collaboration', which demonstrate the potential for AI systems to be designed and optimized to work more effectively with human partners.
Advancements in Human-AI Collaboration and Decision Making
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Ethical conundrums: Hacked data in the study of far-right violent extremism
C2Views: Knowledge-based Colormap Design for Multiple-View Consistency
Context-aware Adaptive Visualizations for Critical Decision Making
Decision-Making Amid Information-Based Threats in Sociotechnical Systems: A Review
Rethinking the filter bubble? Developing a research agenda for the protective filter bubble
Person-AI Bidirectional Fit - A Proof-Of-Concept Case Study Of Augmented Human-Ai Symbiosis In Management Decision-Making Process
What's in a Software Engineering Job Posting?
Human-Centered Threat Modeling in Practice: Lessons, Challenges, and Paths Forward
Personality Pairing Improves Human-AI Collaboration
Affective Color Scales for Colormap Data Visualizations
Algorithmic Management and the Future of Human Work: Implications for Autonomy, Collaboration, and Innovation
How Does Cognitive Capability and Personality Influence Problem-Solving in Coding Interview Puzzles?
Biased Minds Meet Biased AI: How Class Imbalance Shapes Appropriate Reliance and Interacts with Human Base Rate Neglect
Why Do We Code? A Theory on Motivations and Challenges in Software Engineering from Education to Practice
Understanding the Complexities of Responsibly Sharing NSFW Content Online
Future-Back Threat Modeling: A Foresight-Driven Security Framework