ChatGPT and other artificial intelligence tools are transforming the globe, and the healthcare field is no exception.
Artificial intelligence is a multi-faceted concept encompassing machine learning, deep learning, neural networks, natural language processing (NLP), data science, predictive analytics, and even robotics. Ultimately, these can all benefit healthcare systems and patient health outcomes.
Some also question the ethics of certain AI practices, and rightly so — this area can get very complicated, very fast. Patient permission and AI accountability are other ethical questions that need answering as we integrate the use of this powerful tool in our field.
ChatGPT has the ability to write medical school applications. Future patient behaviors can often be predicted by medical records.
Below, we’ll discuss applications of AI in healthcare, its benefits, and the potential downsides.
If you want a highly-qualified human to look over your AMCAS application and suggest meaningful edits, check out MedSchoolCoach’s AMCAS Editing service.
The world of AI is evolving quickly, so it’s unclear to what extent we’ll see it used in our day-to-day professional lives in the future. However, research is booming and gives us many ideas for what this will look like very soon.
As artificial intelligence gets more and more advanced, AI will be useful in healthcare to:
Conversely, AI in its current form can make provider communications feel less human and individualized. Medical students who use AI to write content for their med school or residency applications may be perceived as robotic or lacking passion. AI may weaken trust between payers and healthcare professionals.
There are many potential benefits of AI solutions in healthcare, including:
There are risks and downsides to the adoption of AI in healthcare, including:
A growing issue in the healthcare sector is medical students who don’t put in the work that future doctors have done for decades. More and more med school students are using ChatGPT and similar NLP tools to fill out applications, write personal statements, and compose essays.
AI recognition software will continue to improve and weed out students who do not submit their own work — med schools are not looking for what a chatbot would say about you. Until then, students should be cautious in using AI tools to write for them.
Should you use ChatGPT to help with your medical school application? Here are the arguments for both answers.
Here’s the reality: Beyond just impressive test scores, compelling human writing is the best way to stand out as a med school applicant. Physician advisors and writing advisors can help brainstorm, draft, or enhance your personal statement (on AMCAS, TMDSAS, or AACOMAS applications).
Without question, artificial intelligence will benefit the future of healthcare, especially if we implement these tools with great care. Human error and human inefficiency will decrease while data collection and processing will better serve both patients and medical professionals.
However, humans and organizations using AI tools need to be more transparent and very conscious of the ethics of AI.
AI will not make healthcare perfect. Though AI will most likely improve the healthcare industry and patient care, everyone should be wary of big tech companies, startup companies, healthcare organizations, regulatory bodies, and policymakers promising perfection instead of simply a new status quo.
Need admission consulting or application prep? Check out the Admission Consulting Service by our friends at MedSchoolCoach. Their expert advisors help you identify your application’s strengths and weaknesses, write and edit a killer personal statement, practice interviewing for medical schools, and support you whenever you’re feeling under pressure.
PS: Just in case you were wondering, this article was, in fact, written by a human being and not a chatbot.
Dr. Mehta is the founder of MedSchoolCoach and has guided thousands of successful medical school applicants. He is also a practicing physician in Boston where he specializes in vascular and interventional radiology.