AIMC Topic: Decision Making

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Applying a community-engaged participatory machine learning model.

American journal of community psychology
Although predictive algorithms have been described as the definitive solution to bias in health care, machine learning techniques may also propagate existing health inequities within the community context. However, there may be ways in which machine ...

Is artificial intelligence for medical professionals serving the patients?  : Protocol for a systematic review on patient-relevant benefits and harms of algorithmic decision-making.

Systematic reviews
BACKGROUND: Algorithmic decision-making (ADM) utilises algorithms to collect and process data and develop models to make or support decisions. Advances in artificial intelligence (AI) have led to the development of support systems that can be superio...

Using recurrent neural network to estimate irreducible stochasticity in human choice behavior.

eLife
Theoretical computational models are widely used to describe latent cognitive processes. However, these models do not equally explain data across participants, with some individuals showing a bigger predictive gap than others. In the current study, w...

Overtrust in AI Recommendations About Whether or Not to Kill: Evidence from Two Human-Robot Interaction Studies.

Scientific reports
This research explores prospective determinants of trust in the recommendations of artificial agents regarding decisions to kill, using a novel visual challenge paradigm simulating threat-identification (enemy combatants vs. civilians) under uncertai...

A Novel Evaluation Framework for Medical LLMs: Combining Fuzzy Logic and MCDM for Medical Relation and Clinical Concept Extraction.

Journal of medical systems
Artificial intelligence (AI) has become a crucial element of modern technology, especially in the healthcare sector, which is apparent given the continuous development of large language models (LLMs), which are utilized in various domains, including ...

The existence of manual mode increases human blame for AI mistakes.

Cognition
People are offloading many tasks to artificial intelligence (AI)-including driving, investing decisions, and medical choices-but it is human nature to want to maintain ultimate control. So even when using autonomous machines, people want a "manual mo...

Bio-inspired EEG signal computing using machine learning and fuzzy theory for decision making in future-oriented brain-controlled vehicles.

SLAS technology
One kind of autonomous vehicle that can take instructions from the driver by reading their electroencephalogram (EEG) signals using a Brain-Computer Interface (BCI) is called a Brain-Controlled Vehicle (BCV). The operation of such a vehicle is greatl...

AI generates covertly racist decisions about people based on their dialect.

Nature
Hundreds of millions of people now interact with language models, with uses ranging from help with writing to informing hiring decisions. However, these language models are known to perpetuate systematic racial prejudices, making their judgements bia...

Effects of machine learning errors on human decision-making: manipulations of model accuracy, error types, and error importance.

Cognitive research: principles and implications
This study addressed the cognitive impacts of providing correct and incorrect machine learning (ML) outputs in support of an object detection task. The study consisted of five experiments that manipulated the accuracy and importance of mock ML output...