Oops? Interdisciplinary Stories of Sociotechnical Error| When Faulty AI Falls Into the Wrong Hands: The Risks of Erroneous AI-Driven Healthcare Decisions

This article investigates the consequences and implications of using artificial intelligence (AI) models in healthcare decision making. Specifically, it discusses a lawsuit in which a private healthcare company (UnitedHealthcare) allegedly used an erroneous AI model to deny coverage for its patients’ medical services. While previous studies have found that AI can unintentionally produce biased outputs due to inadequate training data or statistical logics, this example is notable, as the insurer was accused of intentionally using a faulty AI model to their advantage. Furthermore, the victims in this case are elderly individuals who are particularly vulnerable to the negative impacts of AI biases. Although there has been a long history of health insurance companies rejecting medical payouts, the implementation of AI in decision-making processes has accelerated this trend and created loopholes for fraudulent practices. This article illustrates the detrimental consequences of erroneous AI-based healthcare decisions through a specific example, discusses how AI complicates the issue of liability and responsibility, and calls to the need for improved transparency and accountability in AI regulation.

Institutions

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-04-01
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Oops? Interdisciplinary Stories of Sociotechnical Error| When Faulty AI Falls Into the Wrong Hands: The Risks of Erroneous AI-Driven Healthcare Decisions

SHILAP Revista de lepidopterología
Artificial Intelligence in Healthcare and Education
article

Oops? Interdisciplinary Stories of Sociotechnical Error| When Faulty AI Falls Into the Wrong Hands: The Risks of Erroneous AI-Driven Healthcare Decisions

article en

Abstract

This article investigates the consequences and implications of using artificial intelligence (AI) models in healthcare decision making. Specifically, it discusses a lawsuit in which a private healthcare company (UnitedHealthcare) allegedly used an erroneous AI model to deny coverage for its patients’ medical services. While previous studies have found that AI can unintentionally produce biased outputs due to inadequate training data or statistical logics, this example is notable, as the insurer was accused of intentionally using a faulty AI model to their advantage. Furthermore, the victims in this case are elderly individuals who are particularly vulnerable to the negative impacts of AI biases. Although there has been a long history of health insurance companies rejecting medical payouts, the implementation of AI in decision-making processes has accelerated this trend and created loopholes for fraudulent practices. This article illustrates the detrimental consequences of erroneous AI-based healthcare decisions through a specific example, discusses how AI complicates the issue of liability and responsibility, and calls to the need for improved transparency and accountability in AI regulation.

SHILAP Revista de lepidopterología
University of Southern California (US), California Southern University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 51%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Oops? Interdisciplinary Stories of Sociotechnical Error| When Faulty AI Falls Into the Wrong Hands: The Risks of Erroneous AI-Driven Healthcare Decisions · SHILAP Revista de lepidopterología (2025) | TGRS Research Map | TGRS