REVIEW 2 cited by
Human-AI Symbiosis: A Survey of Current Approaches
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
In this paper, we aim at providing a comprehensive outline of the different threads of work in human-AI collaboration. By highlighting various aspects of works on the human-AI team such as the flow of complementing, task horizon, model representation, knowledge level, and teaming goal, we make a taxonomy of recent works according to these dimensions. We hope that the survey will provide a more clear connection between the works in the human-AI team and guidance to new researchers in this area.
Forward citations
Cited by 2 Pith papers
-
Enhancing Joint Human-AI Inference in Robot Missions: A Confidence-Based Approach
In a simulated robot teleoperation task, choosing the inference with higher confidence between human and AI improves team accuracy when the AI's confidence is well calibrated, and hurts when it is poorly calibrated.
-
The Morality of Probability: How Implicit Moral Biases in LLMs May Shape the Future of Human-AI Symbiosis
Six large language models consistently rated care and virtue outcomes as most moral and libertarian outcomes as least moral across 54 AI-generated dilemma variants, with reasoning models more context-sensitive but les...
Discussion (0). Sign in to comment.