Skip to content
  • About
  • Contact
  • Contribute
  • Book
  • Careers
  • Podcast
  • Recommended
  • Speaking
  • All
  • Physician
  • Practice
  • Policy
  • Finance
  • Conditions
  • .edu
  • Patient
  • Meds
  • Tech
  • Social
  • Video
    • All
    • Physician
    • Practice
    • Policy
    • Finance
    • Conditions
    • .edu
    • Patient
    • Meds
    • Tech
    • Social
    • Video
    • About
    • Contact
    • Contribute
    • Book
    • Careers
    • Podcast
    • Recommended
    • Speaking

How AI could widen health disparities without stronger policies

Fadi Masoud and Sami Alahmadi
Tech
September 15, 2024
Share
Tweet
Share

In the realm of health care, artificial intelligence (AI) stands as a beacon of transformative potential. With its ability to process vast amounts of data, AI promises to streamline diagnostic processes, enhance treatment precision, and revolutionize patient care. Yet, it’s overshadowed by various ethical concerns about perpetuating existing biases and systemic discrimination.

AI development is ultimately influenced by the datasets it’s trained on, making it vulnerable to biases present in that dataset. Take, for example, “race-based GFR” — a metric for determining kidney function–where equations incorporating a race coefficient inaccurately suggested higher function in Black Americans. This adjustment, based on unproven assumptions about muscle mass differences, overlooked social factors or other comorbidities. As a result, it failed to consider the diversity within and across racial groups, leading to disparities in such health care as underdiagnosis, delayed treatment of kidney disease in Black patients, and even postponing Black patients from receiving kidney transplants they desperately needed. The misuse of data in cases such as this results in poorer outcomes in the populations these innovations were ostensibly designed to serve, further propagating mistrust among people of color towards the institution of medicine.

We see this already taking place with AI use in skin cancer detection. A study conducted at the University of Oxford showed that in a repository of 2,436 pictures of patient skin used to develop the AI algorithm, only 0.4 percent were of brown skin, and 0.04 percent were of dark brown or black skin. People of color are already at a higher risk of being underdiagnosed for skin cancer due to misconceptions about their lower susceptibility based on skin color, even without the influence of artificial intelligence. AI developed with such flawed datasets potentially puts patients of darker skin color at greater risk for a missed diagnosis of skin cancer.

Failure to address these biases in our data comprehensively may hinder progress toward a more just and equitable health care system. These trained AI could further institutionalize these prejudices under the guise of objective, evidence-based decision-making. It begs the question: what policies or guidelines are in place to prevent this?

At the federal level, recent efforts by the Biden Administration include issuing an executive order “to ensure that America leads the way in seizing the promise and managing the risks of artificial intelligence” and a “blueprint for an AI Bill of Rights.” Within these documents there is mention of AI being a source of potential harm in health care. Yet, the vague language used and suggested “safety program” fail to describe what this looks like and what explicitly are some of the administration’s most pertinent concerns. The AI Bill of Rights states, “Designers, developers, and deployers of automated systems should take proactive and continuous measures to protect individuals and communities from algorithmic discrimination and to use and design systems in an equitable way.” Essentially, they are asking for a voluntary commitment from AI developers, which is ultimately non-binding and ineffectual. While leaders in AI development like Google, Bing, and others are ideally positioned to be at the forefront of positive change, they are fixated more on surpassing each other’s technological achievements than on grappling with the ethical stakes of deploying these technologies, overlooking the profound societal impacts. A stronger policy would mandate that AI tools used in health care were built with data that is representative of the population it intends to serve based on Federal estimates and census representations of both demography and geography.

Mitigating bias in AI extends beyond improving efficacy; it necessitates a comprehensive approach that reduces the risk of inheriting biases. Establishing clear-cut and thorough policies to ensure the use of inclusive datasets and creating guidelines are crucial steps. As we navigate the integration of AI in health care, we face tremendous potential for beneficence as well as ethical challenges. Proceeding with a conscientious commitment to equity is essential to harness AI’s potential to mitigate, rather than exacerbate, health care disparities.

Fadi Masoud and Sami Alahmadi are medical students.

Prev

How delayed gratification in medical school can make or break your career [PODCAST]

September 14, 2024 Kevin 0
…
Next

Nurse practitioner reveals startling flaws in APRN education: Is patient safety at risk?

September 15, 2024 Kevin 10
…

Tagged as: Health IT

Post navigation

< Previous Post
How delayed gratification in medical school can make or break your career [PODCAST]
Next Post >
Nurse practitioner reveals startling flaws in APRN education: Is patient safety at risk?

ADVERTISEMENT

ADVERTISEMENT

ADVERTISEMENT

Related Posts

  • Expanding health care access and equity through telehealth

    Gjanje L. Smith, MD, MPH, Wanneh A. Dixon, and Maria Phillips, JD
  • Medicare’s cobra effect: How a well-intentioned policy spiraled into a health care crisis

    Robert Pearl, MD
  • Are negative news cycles and social media injurious to our health?

    Rabia Jalal, MD
  • The surprising risks of long-term proton pump inhibitor use

    Christopher Medrano, MD
  • Health care workers should not be targets

    Lori E. Johnson
  • Why eliminating health care disparities is easier said than done

    Martin Lustick, MD

More in Tech

  • 9 domains that will define the future of medical education

    Harvey Castro, MD, MBA
  • Key strategies for smooth EHR transitions in health care

    Sandra Johnson
  • Why flashy AI tools won’t fix health care without real infrastructure

    David Carmouche, MD
  • Why innovation in health care starts with bold thinking

    Miguel Villagra, MD
  • How self-improving AI systems are redefining intelligence and what it means for health care

    Harvey Castro, MD, MBA
  • How blockchain could rescue nursing home patients from deadly miscommunication

    Adwait Chafale
  • Most Popular

  • Past Week

    • What the world must learn from the life and death of Hind Rajab

      Saba Qaiser, RN | Conditions
    • How medical culture hides burnout in plain sight

      Marco Benítez | Conditions
    • How the 10th Apple Effect is stealing your joy in medicine

      Neil Baum, MD | Physician
    • Why flashy AI tools won’t fix health care without real infrastructure

      David Carmouche, MD | Tech
    • Why Medicaid cuts should alarm every doctor

      Ilan Shapiro, MD | Policy
    • Key strategies for smooth EHR transitions in health care

      Sandra Johnson | Tech
  • Past 6 Months

    • Why tracking cognitive load could save doctors and patients

      Hiba Fatima Hamid | Education
    • How dismantling DEI endangers the future of medical care

      Shashank Madhu and Christian Tallo | Education
    • What the world must learn from the life and death of Hind Rajab

      Saba Qaiser, RN | Conditions
    • How scales of justice saved a doctor-patient relationship

      Neil Baum, MD | Physician
    • The broken health care system doesn’t have to break you

      Jessie Mahoney, MD | Physician
    • The silent toll of ICE raids on U.S. patient care

      Carlin Lockwood | Policy
  • Recent Posts

    • Earwax could hold secrets to cancer, Alzheimer’s, and heart disease

      Sandra Vamos, EdD and Domenic Alaim | Conditions
    • Why male fertility needs to be part of every health conversation

      Hoag Memorial Hospital Presbyterian | Conditions
    • Why health care must adapt to meet the needs of older adults with disabilities

      Lynn A. Schaefer, PhD | Conditions
    • How doctors took back control from hospital executives

      Gene Uzawa Dorio, MD | Physician
    • Improving patient encounters: time-saving strategies for physicians [PODCAST]

      The Podcast by KevinMD | Podcast
    • How art and science fueled one woman’s path to medicine

      Amy Avakian, MD | Physician

Subscribe to KevinMD and never miss a story!

Get free updates delivered free to your inbox.


Find jobs at
Careers by KevinMD.com

Search thousands of physician, PA, NP, and CRNA jobs now.

Learn more

View 1 Comments >

Founded in 2004 by Kevin Pho, MD, KevinMD.com is the web’s leading platform where physicians, advanced practitioners, nurses, medical students, and patients share their insight and tell their stories.

Social

  • Like on Facebook
  • Follow on Twitter
  • Connect on Linkedin
  • Subscribe on Youtube
  • Instagram

ADVERTISEMENT

ADVERTISEMENT

ADVERTISEMENT

ADVERTISEMENT

  • Most Popular

  • Past Week

    • What the world must learn from the life and death of Hind Rajab

      Saba Qaiser, RN | Conditions
    • How medical culture hides burnout in plain sight

      Marco Benítez | Conditions
    • How the 10th Apple Effect is stealing your joy in medicine

      Neil Baum, MD | Physician
    • Why flashy AI tools won’t fix health care without real infrastructure

      David Carmouche, MD | Tech
    • Why Medicaid cuts should alarm every doctor

      Ilan Shapiro, MD | Policy
    • Key strategies for smooth EHR transitions in health care

      Sandra Johnson | Tech
  • Past 6 Months

    • Why tracking cognitive load could save doctors and patients

      Hiba Fatima Hamid | Education
    • How dismantling DEI endangers the future of medical care

      Shashank Madhu and Christian Tallo | Education
    • What the world must learn from the life and death of Hind Rajab

      Saba Qaiser, RN | Conditions
    • How scales of justice saved a doctor-patient relationship

      Neil Baum, MD | Physician
    • The broken health care system doesn’t have to break you

      Jessie Mahoney, MD | Physician
    • The silent toll of ICE raids on U.S. patient care

      Carlin Lockwood | Policy
  • Recent Posts

    • Earwax could hold secrets to cancer, Alzheimer’s, and heart disease

      Sandra Vamos, EdD and Domenic Alaim | Conditions
    • Why male fertility needs to be part of every health conversation

      Hoag Memorial Hospital Presbyterian | Conditions
    • Why health care must adapt to meet the needs of older adults with disabilities

      Lynn A. Schaefer, PhD | Conditions
    • How doctors took back control from hospital executives

      Gene Uzawa Dorio, MD | Physician
    • Improving patient encounters: time-saving strategies for physicians [PODCAST]

      The Podcast by KevinMD | Podcast
    • How art and science fueled one woman’s path to medicine

      Amy Avakian, MD | Physician

MedPage Today Professional

An Everyday Health Property Medpage Today
  • Terms of Use | Disclaimer
  • Privacy Policy
  • DMCA Policy
All Content © KevinMD, LLC
Site by Outthink Group

How AI could widen health disparities without stronger policies
1 comments

Comments are moderated before they are published. Please read the comment policy.

Loading Comments...