AI in Healthcare: Diagnosis Liability and Mandatory Disclosures

The law is starting to catch up to artificial intelligence in healthcare, but it has not settled on a single approach. State laws on AI in healthcare are beginning to define two critical issues:

1. Who is liable for a misdiagnosis?
2. Must patients be told when artificial intelligence is involved in their care?

While traditional malpractice rules still place responsibility on physicians, new legislation is adding layers of compliance that affect hospitals, developers, and patient rights. If you believe an AI-related error affected your care, consider reaching out to a medical malpractice lawyer for guidance.

Growing Role of AI in Medical Diagnosis

AI now impacts many industries, including healthcare, where its usage has gone far beyond chatbots. For example, AI models can be trained using algorithms to identify patterns in medical imaging.

Pathology also benefits from AI technology by identifying anomalies. During medical diagnosis, AI can assist in analyzing patient symptoms and lab results, then provide a list of viable diagnoses and a possible treatment plan.

While there are many benefits to using AI, it also has limitations. AI systems should be treated as tools, not as replacements for human doctors. There is a risk that medical professionals will rely solely on AI output. This can create medical and legal risks for the patient, medical staff, and facility.

Traditional Medical Liability Applied to AI

There are several common claims in traditional medical liability, including medical malpractice, product liability, and institutional liability. These laws hold healthcare professionals and companies accountable and still apply even if AI tools are used during treatment.

Medical Malpractice

A medical malpractice claim focuses on whether a doctor or other healthcare provider complied with the appropriate medical standard of care. This becomes more complicated when AI tools are used.

The legal analysis must ask whether the doctor’s reliance on AI was reasonable. For example:

• Should they have relied on the AI’s clinical decision or overridden it?
• Were the AI decisions relied upon in alignment with what other medical professionals would have done?

Courts are likely to treat AI as part of the clinical process, not a replacement for independent judgment. A diagnostic error may still constitute negligence if the physician deferred to AI without appropriate scrutiny.

Product Liability

A typical product liability claim focuses on how a medical device or tool malfunctioned and caused harm to the patient.

AI is technically a software product, which means AI developers could face a medical product liability claim. Plaintiffs may argue that the algorithm was defectively designed or trained on flawed data. Failure-to-warn claims may arise if risks or limitations of AI were not included as disclaimers to providers.

Institutional Liability

Sometimes malpractice extends beyond individuals to the medical institution or facility. These claims typically center on policy failures, medication protocols, negligent hiring, supervision failures, or emergency room negligence.

With the rise of AI, hospitals and health systems could be liable for selecting, implementing, and overseeing AI tools. This could result in claims that assert the facility failed to properly vet and monitor a chosen AI system or failed to properly train staff on AI systems. There could also be vicarious liability when employees misuse AI during patient care.

Who Is Liable for AI-Assisted Misdiagnosis?

The use of AI brings up the question of who is actually liable for a misdiagnosis. Ultimately, state medical boards and regulatory agencies have made it clear that AI is a tool. AI recommendations should be treated as just that. Physicians will always remain ultimately responsible for the healthcare services they provide.

However, there may be shared liability, resulting in multiple defendants, depending on the facts of the case. This has led to the emergence of new legal theories based on AI. Negligent reliance on AI-generated datasets, failure to supervise AI tools, and defective algorithm design are all being seen.

The problem with AI and finding liability is proving a connection. The injured person must show that the harm was caused by the physician’s judgment and not the AI. They must also show that their reliance on the AI was not reasonable.

Federal AI Laws

There is no single federal AI healthcare law. Instead, AI is governed by existing healthcare, privacy, and device regulations, as well as newer policy initiatives.

For example, the Health Insurance Portability and Accountability Act (HIPAA) protects patient health information. AI tools must comply with HIPAA’s privacy regulations.

The U.S. Food and Drug Administration (FDA) governs AI tools since they can be classified as “software as a medical device” (SaMD).

State-Level AI Laws Affecting Healthcare Liability

States have enacted new laws to address challenges and risks posed by AI in healthcare, filling gaps in federal law. Generally, state AI laws focus on patient safety, professional licensing, and consumer protection.

California

California’s AI legislation, A.B. 3030, focuses on transparency in patient communications. The law applies to covered entities such as healthcare providers, clinics, and medical practices. These entities must notify patients when generative AI is involved in communications about their health, unless the content is reviewed by a licensed provider before it is shared.

While the law does not prohibit the use of AI as a decision-support tool, it underscores that human oversight remains central to patient care and communication.

Texas

Texas passed S.B. 1188, which mandates that electronic health records be stored within the United States. Access must be limited to individuals who need it for treatment, payment, or operations. AI use must be under the human review of a licensed healthcare practitioner.

Providers must review AI-generated outputs before relying on them. Providers must inform patients when AI is used in diagnosis or treatment. The civil penalties for violations are harsh. They include $5,000 per negligent violation and $25,000 per knowing violation.

Illinois

Lawmakers in Illinois passed the Wellness and Oversight for Psychological Resources (WOPR) Act (HB 1806). The law aims to set parameters around the use of AI during therapy services. It creates a clear distinction between allowed use during administrative support and disallowed use in clinical decision-making.

Mental health therapy cannot be used to generate a treatment plan, interact with patients, or make diagnostic decisions.

Mandatory Disclosure and Informed Consent

There is a strong push for transparency with disclosure requirements. It’s common for patients to not realize that AI is being used during their diagnosis. The goal is to increase awareness and ensure patients give fully informed consent.

Some new laws focus on AI disclosures that warn of the limitations and risks of using AI in diagnosis. The goal is to prevent the use of AI during treatment without the patient knowing. Lawmakers do not want AI-driven systems impersonating licensed professionals.

Regulatory Oversight of Healthcare AI

Oversight of AI in healthcare also comes from regulatory bodies that already govern medical practice and consumer protection. State medical boards continue to regulate physician conduct, regardless of the tools used in patient care. Even without AI-specific statutes, boards can take action when technology contributes to unsafe or improper treatment decisions.

State attorneys general are also playing a role by applying consumer protection laws to AI in healthcare. They can pursue legal accountability for misleading claims about the accuracy and reliability of AI tools, improper handling of patient data when using AI, and discriminatory treatment stemming from algorithmic bias.

Legal Risks for Healthcare Providers

Healthcare providers face several risks as they adopt AI-powered protocols. Being overly reliant on AI outputs and failing to validate AI recommendations creates risk. Failing to implement human oversight and proper documentation puts a facility and its staff at risk.

Additionally, failing to provide proper patient disclosures regarding use and data privacy raises legal issues.

Speak With a Lawyer

As AI becomes more integrated into medical decision-making, the legal system is working to define where responsibility begins and ends. State laws on liability and disclosure are developing quickly, but they do not always provide clear answers in individual cases.

If you believe an AI-assisted diagnosis contributed to harm, speaking with an attorney can help clarify your position and protect your interests. Use the Super Lawyers directory to connect with an experienced medical malpractice lawyer who can guide you through the process.