When combinations of humans and AI are useful: A systematic review and meta-analysis
Inspired by the increasing use of artificial intelligence (AI) to augment humans, researchers
have studied human–AI systems involving different tasks, systems and populations. Despite …
have studied human–AI systems involving different tasks, systems and populations. Despite …
[PDF][PDF] Human-AI Complementarity in Hybrid Intelligence Systems: A Structured Literature Review.
Hybrid Intelligence is an emerging concept that emphasizes the complementary nature of
human intelligence and artificial intelligence (AI). One key requirement for collaboration …
human intelligence and artificial intelligence (AI). One key requirement for collaboration …
Sparks of artificial general intelligence: Early experiments with gpt-4
S Bubeck, V Chandrasekaran, R Eldan… - ar** and refining large language
models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks …
models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks …
Capabilities of gpt-4 on medical challenge problems
Large language models (LLMs) have demonstrated remarkable capabilities in natural
language understanding and generation across various domains, including medicine. We …
language understanding and generation across various domains, including medicine. We …
Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians
Predictive artificial intelligence (AI) systems based on deep learning have been shown to
achieve expert-level identification of diseases in multiple medical imaging settings, but can …
achieve expert-level identification of diseases in multiple medical imaging settings, but can …
Does the whole exceed its parts? the effect of ai explanations on complementary team performance
Many researchers motivate explainable AI with studies showing that human-AI team
performance on decision-making tasks improves when the AI explains its recommendations …
performance on decision-making tasks improves when the AI explains its recommendations …
Who should i trust: Ai or myself? leveraging human and ai correctness likelihood to promote appropriate trust in ai-assisted decision-making
In AI-assisted decision-making, it is critical for human decision-makers to know when to trust
AI and when to trust themselves. However, prior studies calibrated human trust only based …
AI and when to trust themselves. However, prior studies calibrated human trust only based …
Two-stage learning to defer with multiple experts
We study a two-stage scenario for learning to defer with multiple experts, which is crucial in
practice for many applications. In this scenario, a predictor is derived in a first stage by …
practice for many applications. In this scenario, a predictor is derived in a first stage by …
Card: Classification and regression diffusion models
Learning the distribution of a continuous or categorical response variable y given its
covariates x is a fundamental problem in statistics and machine learning. Deep neural …
covariates x is a fundamental problem in statistics and machine learning. Deep neural …
Human-ai collaboration via conditional delegation: A case study of content moderation
Despite impressive performance in many benchmark datasets, AI models can still make
mistakes, especially among out-of-distribution examples. It remains an open question how …
mistakes, especially among out-of-distribution examples. It remains an open question how …