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 …
Human-AI collaboration: the effect of AI delegation on human task performance and task satisfaction
Recent work has proposed artificial intelligence (AI) models that can learn to decide whether
to make a prediction for an instance of a task or to delegate it to a human by considering …
to make a prediction for an instance of a task or to delegate it to a human by considering …
Human uncertainty in concept-based ai systems
Placing a human in the loop may help abate the risks of deploying AI systems in safety-
critical settings (eg, a clinician working with a medical AI system). However, mitigating risks …
critical settings (eg, a clinician working with a medical AI system). However, mitigating risks …
Regulating government AI and the challenge of sociotechnical design
Artificial intelligence (AI) is transforming how governments work, from distribution of public
benefits, to identifying enforcement targets, to meting out sanctions. But given AI's twin …
benefits, to identifying enforcement targets, to meting out sanctions. But given AI's twin …
On the utility of prediction sets in human-ai teams
Research on human-AI teams usually provides experts with a single label, which ignores the
uncertainty in a model's recommendation. Conformal prediction (CP) is a well established …
uncertainty in a model's recommendation. Conformal prediction (CP) is a well established …
Learning personalized decision support policies
Individual human decision-makers may benefit from different forms of support to improve
decision outcomes. However, a key question is which form of support will lead to accurate …
decision outcomes. However, a key question is which form of support will lead to accurate …
Trust Your Gut: Comparing Human and Machine Inference from Noisy Visualizations
People commonly utilize visualizations not only to examine a given dataset, but also to draw
generalizable conclusions about the underlying models or phenomena. Prior research has …
generalizable conclusions about the underlying models or phenomena. Prior research has …
Deep neural network benchmarks for selective classification
With the increasing deployment of machine learning models in many socially-sensitive
tasks, there is a growing demand for reliable and trustworthy predictions. One way to …
tasks, there is a growing demand for reliable and trustworthy predictions. One way to …
Reflections from the Workshop on AI-Assisted Decision Making for Conservation
In this white paper, we synthesize key points made during presentations and discussions
from the AI-Assisted Decision Making for Conservation workshop, hosted by the Center for …
from the AI-Assisted Decision Making for Conservation workshop, hosted by the Center for …
[HTML][HTML] Automated speech analysis for risk detection of depression, anxiety, insomnia, and fatigue: Algorithm Development and Validation Study
Background While speech analysis holds promise for mental health assessment, research
often focuses on single symptoms, despite symptom co-occurrences and interactions. In …
often focuses on single symptoms, despite symptom co-occurrences and interactions. In …