Ethical Considerations of Artificial Intelligence (AI) in Healthcare Use

Introduction

AI the term of this era, is slowly becoming omnipresent by showing its presence in every sector of life. AI is a system that appropriately interprets and learns from external data, and uses the same to complete commanded specific tasks and goals. AI activities are based on complicated computer algorithms imitating human brain power and possess exponential capabilities to analyze endless data pools.

AI and healthcare service transformations

A glimpse of the increasing AI presence in the healthcare industry- progressively AI-based tools and techniques have been used in the field of healthcare to enhance service quality, accessibility, and affordability.

1. Disease diagnosis

It offers a promising hope to reduce the diagnosis and screening burden and human error occurrence. Concomitantly may help improve accuracy, treatment implementation, forecasting outcomes, spotting gaps in health networks, and establishing wellness. 

2. Drug research and development

AI can be used for developing cost-effective drugs and vaccines. AI presents a scope to arrange and deliver patient characteristic and genetic nature-based customized personalized treatment options and predicting disease outcomes.

3. Clinical guidance

AI has been used significantly in telemedicine and patient self-care management initiatives through interactive chatbots, applications, and digital devices monitoring nutritional intake, physical activity, blood pressure, glucose level, and lipid profile. AI also assists in determining and monitoring early disease symptoms and signs.

4. Disease Prevention

AI-based decision support systems provide healthcare solutions through image interpretation, data scrutinization, and medical record databases that can help develop individual patient care or plan large-scale preventive measures.

5. Mental healthcare

AI increases behavioral and mental health treatment opportunities by establishing better psychology and psychiatric procedures, handholding patients in getting timely diagnoses, expanding their self-awareness, and carefully managing symptoms.

6. Efficient health management

AI tools and technology offer a lot of scope for effective scheduling and administration of in-patients and out-patients. Also helps plan patient visit rotations as per their health history, diagnosis, and treatment recommendations. AI aids in maintaining smooth interdepartmental communication and coordination in the hospital.

Ethical AI usage in healthcare

Good quality patient care comprises correct disease diagnosis, appropriate treatment, and favorable aftercare. AI is being used in every aspect of patient wellness handling, hence like conventional medical services AI usage also needs to be based on basic moral principles of healthcare and biomedical principles. There should be a nonstop evaluation, monitoring, and updating of AI technology and systems to ensure the ethical and responsible use of AI in healthcare.

Importance of abiding by AI ethics

Adherence to ethical norms is mandatory to minimize malpractices and offensive activities. Not meeting ethics may lead to concerns related to potential biases, improper data handling, sharing and interpretation, low professional competence, and lack of confidentiality. A patient’s life can directly be affected by AI-based healthcare malfunction and erroneous activities. Routine application of AI algorithms in the healthcare sector demands a vigilant, unhampered, and ethical attitude. In all AI-linked health data development stages, safety, confidentiality, and watchful ethical regulations should be adhered to.

10 Essentials of AI-based healthcare ethics

1. Patient’s choice

AI usage in healthcare does not expect complete human control including all small and big decision-making. Patient autonomy should never be interfered with by AI technology. While using AI-driven healthcare provisions such as diagnosis, therapies, treatments, and research data collection, patient’s consent over the same should always be checked. They should be informed about the benefits and possible risks associated with AI techniques. At any point in time, the patient must have the full choice to select or reject the AI methods.

AI technology-focused clinical decisions may differ from the physician, in that case, confusion among the patient should be addressed and handled carefully. Patient and healthcare professional relationships can be affected by the overdependency of AI, hence patients’ self-determination towards healthcare method choice should always be respected.

2. Ensuring Safety and Lessening Risk

The widespread use of AI in healthcare demands affirmation regarding the safety and reliability of the system. Patient safety is the foremost responsibility of healthcare professionals developing and using AI technology. It is of the highest priority to protect the dignity, rights, safety, and well-being of patients/ participants. Deliberate misuse and unintended flaws can be prevented by a strong control mechanism. Multidisciplinary risk factors associated with AI should be identified so that unfavorable consequences can be averted.

Patient data should be anonymized and offline delinked before final use to reduce the cyber attack threat. All the AI algorithms should be in line with scientific research and critically satisfactorily evaluated in varied conditions. A stringent mechanism or team should be in place to monitor the performance, vulnerabilities, and safety standards of AI technology. Regulatory bodies must review the AI risk minimization measures and strategies from time to time.

3. Credibility

AI diagnostic tools require a lot of trustworthiness and confidence from physicians using them. A hassle-free systematic step should be provided to test the reliability and validity of the AI technology. All AI-based healthcare solutions should be as per the law and regulation of the country, community, and ethnicity. Awareness regarding the same needs to be created among the population. Results and interpretations obtained through AI technology should be backed up by scientific knowledge. Transparency should be made regarding conflicts of interest arising at any stage of development.

4. Healthcare data seclusion

Primarily loss or modification of personal data and unauthorized access should be prohibited by ensuring a strong data privacy system. Patient data including “metadata” and “on-image data” must be anonymized before being them for AI algorithms. User control over their data should be provided and end users should be made aware of the ensured protection of their data privateness. Patient's biometric data should be preserved carefully and with the highest security measures to prevent accidental data leak-driven unpredicted consequences.

5. Answerability and legal responsibility

AI service providers catering to healthcare need to go through scrutiny by authorities, always be ready to take accountability for their actions and activities, and transparently disclose everything. Advice from healthcare representatives should always be taken while developing AI-based health solutions. The right kind of supervision should always be provided by the healthcare professional when they use AI tools to avoid malfunction, underperform, and erroneous decision-making risks. AI technology developers, designers, and healthcare professionals involved in utilizing AI technology should work as a team and focus towards minimizing the harm factors and damage.

6 Data perfection

Skewed data may be prone to threats such as bias, errors, and discrimination. Data verification is mandatory to ensure its bias-free quality and large target population size in which the data is intended to be used. Data collection and AI algorithms should be errorless and clinically and biomedically validated.

7. Convenience, integrity, and comprehensiveness

AI technology should be fairly and equally distributed among the users. Accessibility of AI technology can be enhanced by using local languages in the user interface and taking care of supportive optimum functioning infrastructure. Individuals or groups from whom data is collected should have access to AI technologies. Also, it should be ensured that different applications can work seamlessly on different platforms to promote wider accessibility options for user groups.

8. Teamwork

Collaboration at every stage ensures meaningful usage of data-driven AI in the healthcare sector. A strong multifaced partnership is required between AI researchers and health professionals throughout the process of development and approval of AI. Data sharing should be done under the supervision and guidance of authorities abiding by the regulations and laws.

9. Impartial and honest fundamentals

Every AI data used should be accurate and authentic and should not be used as an exclusion tool. AI technology should be developed for universal usage and offer equal rights and advantages to all groups of users. There should be a proper AI protecting mechanism and in case of any malfunction, the issue should be addressed and handled delicately.

10. Lawfulness  

AI technology should undergo strict clinical and biomedical validation and authentication before its usage on patients and research populations. There should be an internal mechanism in place to monitor AI malfunctions as per the clinical overview and convey the same feedback instantly to the developers. Every AI-based health service and tool should adhere to ethical rules and regulations.

Conclusion

AI has the potential to enhance healthcare facilities through its big data based on advanced machine learning techniques along with artificial neural networks. Adequate usage of AI in healthcare needs validity and trustworthiness from the biomedical and clinical science, healthcare professionals, and patients.

New technology development demands new supportive ethical principles. To correctly apply AI benefits in healthcare there is an urgent requirement to build an ethically sound policy framework which is accountable, responsible, and aided by legal and social rules and regulations.

Reference

1. Ethical Guidelines for Application of Artificial Intelligence in Biomedical Research and HealthcareICMR,2023
2. Sci Ed 2019;6(2):91-98