When any new technology emerges for the first time, promise of innovation must be counterbalanced with the need for responsible and ethical implementation. Technologies powered by artificial intelligence hold significant promise to transform the health care landscape, offering unprecedented opportunities for improving patient outcomes and streamlining clinical workflows.
However, the integration of AI in health care also raises unique ethical considerations that must be addressed to ensure responsible use.
Premedical students are entering the medical field at the dawn of this new era, in which familiarity with the benefits and challenges of AI will soon become prerequisite.
Here is some practical advice to help premed students best understand, evaluate and ethically use AI throughout their education and career in health care, as well as strategies for students to learn about and navigate the ethical implications of AI-powered technologies.
Perhaps the next generation of students can even work to address such challenges in the near future.
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Data Privacy and Patient Confidentiality
Among the ethical concerns surrounding integration of AI in health care, data privacy concerns are paramount. AI-enabled systems require vast amounts of data on which to be trained and thus function effectively, placing sensitive patient information at risk of exposure if proper regulatory framework is not put into place.
Such legal and bureaucratic framework often lags behind technological advancement, presenting quandaries that should be recognized and assessed.
Ensuring compliance with existing regulations like HIPAA is critical to protecting patient data, and developing new methodologies to protect such data and confidentiality from AI-specific threats is a critical near-term objective. As a premedical student, involving yourself in such projects may prove particularly fruitful as this technology matures.
Bias in AI Algorithms
AI algorithms are only as strong as the datasets on which they are trained, so they can perpetuate biases in existing health care datasets, leading to unfair treatment of certain patient groups.
While AI-driven diagnostic tools trained on data from one subset of the population may be beneficial in a similar patient group, they may be markedly less accurate in minority populations, for example, particularly if the original dataset is based on a relatively small or homogenous study population. Such biased training data may lead to less-accurate diagnoses, less-effective treatments and/or worse patient care.
Striving for increased equity in AI-driven clinical algorithms will reduce risk of bias, decrease health disparities and improve health care outcomes.
[Read: Why Mentors Are Important for Premedical Students]
Accountability in AI Decision-Making
When the clinical decision-making process relies on an AI-powered algorithm, ensuring accountability and transparency is crucial. As these algorithms proliferate across the medical decision-making landscape, the framework for accountability must be quickly designed and implemented. Otherwise, patients or family members may not know who is ultimately responsible for their care, eroding trust between patient and provider.
Health care providers must understand how AI-driven systems reach their conclusions and be able to explain this process in simple terms to patients.
Determining who is ultimately responsible for clinical decisions made with AI assistance is critical so that all parties — patients, families, physicians, insurers and hospital employers — are aware of the appropriate consequences for mistakes. Shunting responsibility to an amorphous algorithm will not suffice, even as it may become easier to do so in the future as algorithms evolve and expand their role within health care.
Designing and using easily interpretable AI models can help demystify the decision-making process for all involved, and is a promising direction for future innovation.
Ethical Use of AI-Driven Technology in Medical Education
AI can offer personalized learning experiences through adaptive learning platforms that adjust to a student’s unique strengths and weaknesses. Such platforms will soon become available for premedical education, particularly for exams such as the MCAT and USMLE step exams.
Taking advantage of an AI-based tutor to clarify difficult concepts is beneficial, particularly for concepts that are difficult to look up in textbooks. However, students should avoid relying on it entirely for coursework. Care should be taken, and information should be double checked to be sure it is coming from a reliable, peer-reviewed source.
It is never too early for premedical students to learn to balance the advantages of personalized AI-driven tools with the need to maintain academic honesty and integrity.
[READ: How to Get Clinical Experience as a Premedical Student]
AI Assistance in Med School Application Preparation
AI-powered tools like writing assistants and interview simulators can help premed students prepare strong applications, but extreme care must be taken. Students must ensure that their applications genuinely reflect their abilities and experiences. The final submission needs to be their own work.
Admissions committees will read applicants’ materials closely, and suspicion of undeclared AI-generated content could reflect poorly on an applicant. However, tools to develop ideas, brainstorm, edit and/or proofread written materials are allowed.
Other AI-driven tools, such as interview simulators or test prep services, can also be a big help if used efficiently.
How Students Can Learn About the Ethical Implications of AI
Many institutions offer courses that explore the ethical dimensions of AI-driven technology in health care, providing a foundation for understanding these issues. Students may also engage in workshops or attend seminars on AI and ethics, which provide practical insights and help to foster discussions on real-world ethical applications of such technology.
Better yet, working directly with professionals from various fields — such as computer science, law and medicine — who are focused on ethically implementing AI-powered tools into their work can offer a broader perspective on the ethical implications and real-world utility of AI. Specifically, working with data scientists can help students understand on a more profound level the technical limitations and ethical considerations of AI algorithms.
Integration of AI into health care presents both opportunities and ethical challenges that aspiring doctors must learn to navigate responsibly. Premed students can prepare by understanding how to use AI-powered tools ethically and actively engaging in educational opportunities focused on ethical use of such innovative technologies.
By embracing these practices, future physicians can ensure that such AI-enabled tools are used to enhance patient care, not detract from it.
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Premeds: Learn to Navigate Ethical Challenges of AI in Medicine originally appeared on usnews.com
