Ethical Considerations of Artificial Intelligence Use Abound

Everyone is talking about artificial intelligence (AI) and machine learning (ML) technologies, and many health care systems are adding them to their software. Forward-thinking individuals suggest that using these technologies in health care might improve patient care, streamline clinical workflows, and advance medical research.^1,2 Approximately 80% of clinically relevant health care information is unstructured data, and AI and ML can analyze such data quickly.^3,4 The Table^3-10 lists some areas in which health care is employing AI and ML.

Medical ethicists, however, indicate that the ethical considerations surrounding the use of AI and ML are multifaceted.⁵

The Basics of Health Care Ethics

Three ethical principles should underscore all health care^11,12:

• Beneficence means that the patient’s needs and preferences drive all clinical decisions. All health care providers must do their best to maximize positive outcomes and alleviate suffering to the greatest extent possible.
• Nonmaleficence, simply put, means do no harm. Although medical treatment may have risks or cause adverse events, health care providers need to share decision-making with patients and respect patient autonomy.
• Justice means distributing resources fairly and addressing disparities.

Ethical Concerns

Ethical concerns with AI and ML emanate from the aforementioned principles. First and foremost, ethicists are concerned about patient privacy.^13,14 Because AI and ML can access the electronic health record (EHR), imaging data, and genomic data, data privacy and breaches are possible. The data security protocols used in the pre-AI era are insufficient once AI and ML are employed. Organizations will need airtight encryption techniques, access controls, and authentication mechanisms. When health care providers use AI, they must also tell patients that they are using it and explain the specific ways in which it is employed.^13,14

Next, bias and fairness must be addressed proactively. Although we tend to associate bias with humans and their beliefs, AI and ML algorithms can be biased, too.¹⁵ For example, if an algorithm uses data with an insufficient number of people from a specific demographic or too many people from a specific socioeconomic group, the actions it proposes will be biased. Applying the proposed actions could delay diagnosis or start a treatment cascade that is incorrect for people in minority populations.¹⁶ This violates the justice principle.

Adverse Drug Reactions and Adherence

Current EHR systems already use AI for adverse drug reaction prediction and detection and notify staff if a prescriber tries to order 2 drugs known to interact. Newer AI-assisted systems may recommend adjusting doses or switching medications.¹⁷ Clinicians will need to be aware that false positives and negatives can occur regardless, and should avoid relying solely on these alerts.

AI can also craft patient-specific message alerts, such as medication renewal reminders for both the pharmacist and the patient. Wearable devices (eg, smartwatches and smartphones) also integrate AI technology that may suggest behavioral changes (like a message that it is time to stand up and move) and enhance adherence.² Few pharmacy employees would object to using AI technology to request and process prior authorizations, manage the supply chain, optimize pharmacy revenue cycles, or track financial performance.¹⁸

AI and the Pharmacy

Many pharmacy personnel worry that AI may replace them. However, the cost of automation technologies, labor market dynamics, and regulatory and social acceptance are major barriers to the widespread adoption of AI. They may mitigate actual job loss.² AI integration should help pharmacists expand their scope of practice.^18,19 AI can mimic certain human actions, but it is not human. Pharmacists and technicians will continue to use their interpersonal skills and build relationships. Ultimately, AI will complement pharmacists by streamlining repetitive tasks, addressing workforce shortages, and enabling them to use their unique human intelligence abilities.^8,18

Conclusion

Will AI technologies revolutionize health care? Will they enhance clinical decision-making, improve patient outcomes, and streamline workflows? In many ways, they already have. As they continue to evolve, all health care providers need to be aware of significant barriers. They need to understand the algorithm’s transparency (or lack thereof) and appreciate bias, cost, and accountability concerns. Of utmost importance will be collaboration among health care providers, policymakers, and AI developers. Establishing clear guidelines and validation procedures will help ensure AI technologies are safe and used properly. With proper implementation and education, AI is a powerful tool that eliminates some busywork and enhances health care professionals’ abilities.

REFERENCES

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17. Drug interactions between amiodarone and warfarin. Drugs.com. Accessed September 30, 2025. https://www.drugs.com/drug-interactions/amiodarone-with-warfarin-167-0-2311-0.html?professional=1

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