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In 2016, the Arkansas Department of Human Services implemented an algorithmic tool designed by InterRAI to allocate home care hours for Medicaid beneficiaries. The system, implemented by a third-party vendor, contained significant coding errors regarding diabetes and cerebral palsy, leading to drastic and unexplained reductions in care hours for hundreds of disabled individuals. A federal lawsuit revealed these flaws, highlighting the lack of transparency and the inability of beneficiaries to effectively challenge automated decisions.
Beneficiaries of the Arkansas Department of Human Services (DHS)'s Medicaid waiver program were allocated excessively fewer hours of caretaker visit via an algorithm deployed to boost efficiency, which reportedly contained errors and whose outputs varied wildly despite small input changes.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
Delegating by humans of key decisions to AI systems, or AI systems that make decisions that diminish human control and autonomy, potentially leading to humans feeling disempowered, losing the ability to shape a fulfilling life trajectory, or becoming cognitively enfeebled.
Also classified as
The software errors selectively and unfairly reduced care hours for individuals with specific disabilities like cerebral palsy and diabetes.
The algorithmic tool failed to perform reliably due to significant coding errors regarding diabetes and cerebral palsy.
The state delegated critical care allocation decisions to an automated system, removing human decision authority and leaving beneficiaries without a meaningful way to appeal or understand the decisions.
AI system
Due to a decision or action made by an AI system
Unintentional
Due to an unexpected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed
The harm was caused by the post-deployment execution of an algorithmic tool that produced unintended and erroneous care cuts due to software bugs.
Added categories peak at 2: Minor (Psychological Harm, Indirect)
A state-level Medicaid administrative algorithm in Arkansas contained coding errors that inappropriately reduced home care hours for disabled individuals. While causing localized physical distress and violating constitutional due process rights for hundreds of citizens, the incident remains a domestic administrative and legal issue with negligible national security implications.
The AI system operates as a deterministic mathematical formula that takes specific inputs (60 health descriptions and symptoms) and outputs a care hour allocation category. It does not exhibit planning, goal-directed behavior, or context retention, fitting the definition of a Tool.
High Risk: The report describes an AI system used in healthcare and public assistance benefits allocation, which has significant implications for safety, fundamental rights, and public interests.
The primary function of the algorithm was to allocate home care hours (resources) to Medicaid beneficiaries based on their health assessments.
The reports provide detailed, consistent accounts of the algorithmic system's implementation, the specific coding errors (cerebral palsy and diabetes), the legal challenges, and the direct impacts on beneficiaries. The roles of the developer (InterRAI) and the vendor (Center for Information Management) are explicitly documented.
None. The causal link between the algorithmic errors and the reduction of care hours is clear and legally established.
Technology
Cerebral Palsy Coding Error
Software error incorrectly calculated hours for cerebral palsy patients.
Diabetes Omission in Algorithm
The algorithm version used failed to account for diabetes issues.
High Algorithmic Complexity
The system's complexity made it impossible for average users to understand.
Data Inputs
Use of Deeply Flawed Data
Idaho's system relied on flawed data and discarded most of it.
Lack of Training Data Diversity
AI tools were approved without diverse demographic training data.
Human Factors
Overreliance on Automation
Assessors deferred to the computer, saying 'it is the computer'.
Lack of Formula Comprehension
Beneficiaries and assessors could not understand the complex formula.
Process and Methods
Lack of Technological Due Process
No meaningful ways were provided for individuals to challenge decisions.
Inadequate Testing by Vendor
The third-party vendor implemented incorrect versions of the algorithm.
Inadequate Notification Process
The state implemented the algorithm without properly notifying beneficiaries.
Management
Prioritizing Cost Containment
States adopted algorithms to contain costs rather than prioritize care.
Ignoring Expert Advice
Arkansas officials ignored advice to grandfather in existing patients.
Lack of Transparency
Management refused to disclose formulas, citing trade secrets.
Regulatory Environment
Lack of Regulatory Oversight
In-home care allocation algorithms are not required to be regulated.
No Mandatory Bias Testing
Manufacturers are not required to test tools for demographic biases.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
