Transparency is usually seen as an important part of good communication and ethical behavior, especially in healthcare. Patients expect to know everything about their care, including the tools or people involved. But research by Schilke and Reimann shows that telling patients AI is being used—such as for answering phones or making appointments—can actually lower their confidence in the people or organizations involved.
The researchers ran thirteen experiments with different professionals, like supervisors, analysts, and doctors. They found that those who said they used AI were trusted less than those who did not mention it. This happened no matter how complex the task was, from talking to patients to analyzing data.
In healthcare, this means patients might trust the provider less if they learn AI is handling parts of their care once done only by humans. This happens because patients see the provider as less legitimate or real when AI is involved in important communication. They may wonder if the care is as genuine or trustworthy.
Surprisingly, this drop in trust happened whether the AI use was shared by choice or because it was required. It also did not matter how the information was given. If someone outside the practice revealed the AI use, trust dropped even more.
The reason for this trust gap comes from micro-institutional theory, which looks at how people see others as proper and rightful in their roles. The research suggests that when patients hear AI is involved, they see the providers as less legitimate. This is because they think AI is not as real or as proper as a human professional.
Disclosure makes people pay more attention and doubt the process. It is not just that they dislike algorithms. They start to question decisions or messages made with AI help. Even those who normally liked technology or trusted AI had some loss of trust, though less than others.
For healthcare managers in the U.S., it is important to understand legitimacy. Patient trust is fragile. It affects not just satisfaction but also health results, whether people follow treatment, and the reputation of the practice.
Medical managers and owners in the U.S. have to think carefully about using AI for front-office tasks like phone calls. The U.S. healthcare market is very competitive and patients want honesty from providers. But these findings suggest that clearly telling patients AI is involved might lower trust.
Doctors and managers should look at common outpatient settings. These places use phones to make appointments, refill prescriptions, and answer health questions. If patients know AI is doing much of this, some might feel the care is less personal or less safe.
This concern is bigger in sensitive cases where trust is very important—for instance, mental health visits, chronic illness checkups, or sharing important test results. Patients may feel unsure or less willing to get care if they think AI lowers the quality or empathy of the service.
There is also a risk if AI use is revealed by others, like online reviews or social media. This can cause even more harm to trust. Medical offices should try to control how they talk about AI inside the practice and to patients, so they avoid surprises from outside sources.
Even with trust challenges, automation helps make work easier, reduces staff load, and helps patients get care faster. Companies like Simbo AI create systems where AI answers phones 24/7, handles calls quickly, and keeps patient info accurate. This can improve how busy medical offices run.
But adding AI must come with careful communication plans. Healthcare teams can focus on these points:
Including AI in work processes without losing trust is hard, but possible. It means balancing better operation with the social and emotional parts of patient care.
Healthcare managers and IT teams in the U.S. also need to think about rules when using AI. Laws like HIPAA protect patient privacy and require careful handling of personal data, especially when AI communicates sensitive information. Being clear about data use, privacy, and AI limits should go with any AI disclosure to patients.
Practice owners should also work to build trust by showing the skills and experience of their clinicians along with the AI systems. This can help reduce the trust lost when AI use is shared. Good communication by leaders about tech use supports trust in the practice’s focus on patients.
For IT teams, working well with AI providers like Simbo AI means making sure calls are handled correctly and no mistakes harm patient care. If AI makes errors, especially after telling patients AI is used, trust can drop even more. So, keeping AI reliable and managing mistakes carefully is very important to keep patients’ trust.
Research shows that rules requiring AI use to be disclosed do not stop trust from dropping. Whether sharing AI use is voluntary or forced, the trust problem stays. This puts U.S. healthcare providers in a tough spot since many places are moving toward requiring full transparency about AI in care and administration.
In the U.S., where people worry about privacy and ethics in technology, being open about AI has both good and bad effects. Just telling patients about AI does not make providers seem honest or ethical automatically. Trust also needs providers to build legitimacy strongly.
For example, medical leaders might choose to reveal AI use slowly and in ways that show how AI helps patient care without losing the human part. They could run education campaigns that explain what AI is, what it does, and its limits to help patients go from being suspicious to being more open.
AI systems, like those from Simbo AI, can help U.S. medical offices by automating routine jobs such as answering phones and scheduling. These tools can make offices work better, reduce staff burden, and serve patients faster.
Still, the paradox found by Schilke and Reimann shows that telling patients about AI use is not a simple way to build trust. Healthcare managers, owners, and IT workers need to carefully plan how they communicate about AI. They must balance the need to be honest with the need to keep patients’ trust and respect.
By understanding how trust works with AI and using good communication and technology plans, U.S. healthcare providers can get the benefits of AI without hurting trust. This balance is key to making sure AI helps patient care instead of harming it.
The article investigates whether disclosing the use of AI agents in tasks, including healthcare, affects trust in the user, exploring the implications of transparency on social perceptions and legitimacy.
Disclosing AI usage consistently reduces trust in users across various tasks and roles, indicating that transparency about AI involvement can erode confidence rather than build it.
Micro-institutional theory explains the trust erosion through reduced perceptions of legitimacy, suggesting that users who disclose AI usage are seen as less legitimate actors.
No, different disclosure framings, prior knowledge of AI involvement, and whether disclosure is voluntary or mandatory do not prevent the trust erosion effect caused by AI disclosure.
The negative impact on trust is stronger when AI usage is exposed by third parties rather than when users voluntarily self-disclose their AI involvement.
No, the AI disclosure effect is distinct from basic algorithm aversion as it specifically raises attention and produces doubt about legitimacy rather than mere discomfort with algorithms.
Yes, favorable technology attitudes and perceptions of AI accuracy lessen the negative trust impact but do not fully eliminate the trust erosion caused by disclosure.
The study assessed diverse tasks ranging from communication, analytics to creative tasks and included varied actors such as supervisors, subordinates, professors, analysts, creatives, and organizational entities.
The article highlights that transparency in AI usage is not simply beneficial; it can harm social perceptions and legitimacy, thus complicating the role of transparency in trust formation.
Healthcare organizations should carefully consider how and when to disclose AI usage, as mandatory or voluntary transparency may reduce patient or stakeholder trust, stressing the need for strategies that build legitimacy alongside transparency.
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