AI, robotics, and nanotechnology are making great strides in the medical field. (Credit: whyframeshot/AdobeStock)

A new study provides interesting insights into the public's perception and acceptance of AI, robots, and nanotech in the healthcare industry, shedding light on the potential future direction of healthcare advancements.

For this survey, Innerbody Research  considered the latest forerunners in the medical technology space — artificial intelligence (AI), robotics, and nanotechnology. These technologies have already held a place in healthcare, but it appears their greatest contributions are yet to come. The research firm surveyed over 1,000 people across four generations (Baby Boomers through Gen Z) to see how they felt about these new advancements in medical technology.

Key takeaways

  • 64 percent of people surveyed would trust a diagnosis made by AI over that of a human doctor.
  • The older the generation, the more unlikely they are to support the use of AI in healthcare.
  • People are most comfortable with AI in the medical imaging analysis aspect of healthcare.
  • The more complicated a medical procedure is, the less comfortable people are with a robot performing it.
  • 69 percent of respondents said they were concerned with the long-term effects of nanotechnology on the human body.


Innerbody surveyed 1,027 people to understand the public's level of comfort with different types of technology being used in healthcare. AI, robotics, and nanotechnology are making great strides in the medical field, and the survey was designed to understand how each generation views these advances.

Respondents were asked not only how they felt about the concept of each technology but also how they felt about specific medical fields and procedures utilizing these new techniques. For example, the survey sought to determine not just whether people are comfortable with AI but what exactly they are agreeable with, whether it’s medical imaging analysis or drug discovery. The results showed that it was clear that people might be open to up-and-coming technology but not for all types of procedures.

When analyzing the data, Innerbody considered the generation of the survey participants — including Baby Boomers (people born 1946–1964), Gen X (1965–1980), Millennials (1981–1996), and Gen Z (1997–2012). The differences in attitude toward the new technologies were telling; the younger generations were generally more open and comfortable with AI, robotics, and nanotechnology.

Artificial intelligence in healthcare

AI is a technology that uses machines to mimic human cognitive functions. Some types of AI include:1

  • Machine Learning (ML): Uses an algorithm to examine data and draw inferences.
  • Natural Language Processing (NLP): Understands and interprets language and text.
  • Deep Learning (DL): Complex ML based on the human brain neural network.

Some examples of AI already at work in the healthcare sector include disease prediction (through machine learning), clinical documentation (with natural language processing), and medical imaging analysis (using deep learning).

How comfortable are Americans with AI in different healthcare contexts, and how do comfort levels differ across generations?

How comfortable are Americans with AI in different healthcare contexts? (Credit: Innerbody Research)

According to our survey, the older the generation, the more unlikely a person is to support the use of AI in healthcare. This result likely aligns with your expectations; with younger generations growing up alongside technology, their comfort level is bound to be higher than those introduced to it later in life. To further illustrate this, we found that 6.8% of Baby Boomers were not comfortable with any AI in medicine at all.

When we asked about the different ways AI could be used in healthcare, medical imaging analysis was the most accepted application across all generations. In fact, three out of five people reported being comfortable with this aspect of AI involvement in the healthcare system. The survey participants' observations hold merit, as numerous studies have been published demonstrating the ability of Deep Learning technology to identify cancer in radiology images.

A 2018 study revealed that a DL tool outperformed dermatologists in identifying melanoma from dermoscopic images.² A separate 2022 research study demonstrated that radiologists and AI were more successful in diagnosing breast cancer when used together than alone.³ But while the statistics look promising, it’s also clear that many AI studies have design flaws, highlighting the need for more research to back up these findings.4,5

The most remarkable takeaway from the survey was that 64 percent of respondents said they would trust a diagnosis made by AI over a human doctor. This percentage grows even more with Gen Z, with four out of five in this generation stating they’d trust AI over a physician. This result indicates a significant shift in public perception and trust toward technology. Talk of AI developments has become ubiquitous in the last few years, and more people are becoming informed about the science behind it across all generations.

Overall, two out of three survey respondents said they were comfortable with the use of AI in healthcare, with men (67 percent) being slightly more comfortable than women (64 percent). When asked what the most concerning aspect of AI is in regard to healthcare, every generation except Gen X reported the accuracy of diagnosis — this generation was slightly more concerned with data and privacy.

the survey also found that 78 percent of people would be comfortable with an AI algorithm creating a personalized treatment plan for them. Interestingly, survey participants reported that legal and regulatory issues were the least concerning aspect of AI in the healthcare system. This could be due to the public perception that the FDA will tightly regulate AI.

Along those lines, the World Health Organization recently released a statement calling for caution to be used with some AI programs (large language model tools) in the healthcare sector.⁶ They expressed concern over professionals using untested systems of AI, which could lead to diagnostic errors and ultimately harm patients. WHO has released a guide on the ethics and governance of AI in health for those developing this technology.⁷

Robotics in healthcare

Robotics in healthcare. (Credit: Innerbody Research)

Robots in the medical field have come a long way since their emergence in the 1980s. Robotics is a class of AI that has applications in research labs, operating rooms, and clinical settings. They can complete diverse tasks, from assisting in surgery to aiding in a physical therapy session.

When asked if they would pay more for medical treatment if it meant that robots were used to improve the quality of care, 39 percent of people said they would, 41 percent said maybe, and 20 percent responded that they would not. Overall, 65 percent of survey respondents reported that they were comfortable with robots in the medical field, with men (66 percent) slightly more agreeable to the idea than women (62 percent).

The survey found that, in total, only 4 percent of respondents would not feel comfortable at all with robots involved in their medical care. However, the Baby Boomers were the least accepting, with 9 percent uncomfortable with all of it. When considering the different aspects of medicine that robots could assist with, each generation had differences in what they were the most comfortable with:

  • Gen Z: Diagnosis
  • Millennials: Rehabilitation and diagnosis (tied)
  • Gen X: Assistance with daily tasks
  • Baby Boomers: Rehabilitation

For medical procedures performed or assisted by robots, all generations found x-rays and CT scans to be in their top three in terms of comfort. It appears that medical imaging feels the least risky to people when it comes to robotic assistance. In contrast, all generations were the least comfortable with a robot in the following procedures:

  • Hip replacement surgery
  • Heart bypass surgery
  • Cesarean deliveries

The takeaway here appears to be that the more serious or complex the procedure, the less comfortable people might be with a machine performing it.

Nanotechnology in healthcare

Nanotechnology in healthcare. (Credit: Innerbody Research)

Nanotechnology is the science and application of microscopic particles (like individual atoms and molecules) and is used in medicine for the prevention and treatment of diseases.⁸ For example, nanofibers can be used in wound dressings and nanomedicine “smart pills” have several functions, including sensors that serve as promising diagnostic tools.

The survey found that, similar to most of the trends in our data, the younger the generation, the more likely they are to have confidence in this technology (only 2 percent of Gen Z did not like the idea of nanotechnology at all). Accordingly, the older generations were less comfortable with the idea of using nanotechnology in medicine — only 24 percent of Baby Boomers felt confident in its effectiveness and safety.

When investigating the uses of nanotechnology, the older generations were most comfortable with the idea of imaging applications, while Gen Z was more open to using it for diagnostic purposes. The areas where each generation was the least comfortable with nanotechnology were:

  • Gen Z: Wound healing
  • Millennials: Immunotherapy
  • Gen X: Immunotherapy
  • Baby Boomers: Tissue engineering

Part of the reason for this could be a lack of understanding of exactly how nanotechnology is used in these fields or uncertainty on how much research has been performed to back them up. Studies researching the use of nanotechnology in cancer-fighting immunotherapy are promising, but this science is relatively new.⁹ The same can be said for wound healing and tissue engineering; both of these fields are complex and offer significant challenges to medical professionals, and nanotechnology shows potential as a solution.10,11 However, the technology has yet to be widely used, possibly leading the public to hesitate to accept its usage in these types of applications.

Overall, 67 percent of respondents were likely to undergo a medical procedure involving nanotechnology if their healthcare provider recommended it; men were more likely to do this (69 percent than women (63 percent). Perhaps most interestingly, 69 percent of respondents said they were concerned about the long-term effects of nanotechnology on the human body. This underscores the idea that while most accept the concept of new, innovative technology, there are still concerns across all generations about its safety.


Innerbody surveyed 1,027 respondents spanning four generations — Baby Boomers, Gen X, Millennials, and Gen Z — and asked questions regarding their comfort levels, expectations, and concerns about various types of technology (AI, robotics, and nanotechnology) that are being used or introduced to medicine and the healthcare industry today.


1. Brown, S. (2021). Machine learning , explained. MIT.

2. Haenssle, H., Fink, C., & Schneiderbauer, R. (2018). Man against machine: Diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists . Annals of Oncology, 29(8), 1836-1842

3. Leibig, C., Brehmer, M., Bunk, S., Byng, D., Pinker, K., & Umutlu, L. (2022). Combining the strengths of radiologists and AI for breast cancer screening: A retrospective analysis.  The Lancet Digital Health, 4(7), e507-e519

4. Liu, X., Faes, L., Kale, A. U., Wagner, S. K., Fu, D. J., Bruynseels, A., Mahendiran, T., Moraes, G., Shamdas, M., Kern, C., Ledsam, J. R., Schmid, M. K., Balaskas, K., Topol, E. J., Bachmann, L. M., Keane, P. A., & Denniston, A. K. (2019). A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: A systematic review and meta-analysis. The Lancet Digital Health, 1(6), e271-e297.

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6. World Health Organization. (2023). WHO calls for safe and ethical AI for health. WHO.

7. World Health Organization. (2021). Ethics and governance of artificial intelligence for health.  WHO.

8. Ventola, C. L. (2012). The Nanomedicine Revolution: Part 1: Emerging Concepts. Pharmacy and Therapeutics, 37(9), 512.

9. Shams, F., Golchin, A., Azari, A., Amirabad, L. M., Zarein, F., Khosravi, A., & Ardeshirylajimi, A. (2021). Nanotechnology-based products for cancer immunotherapy.  Molecular Biology Reports, 49(2), 1389-1412.

10. Kushwaha, A., Goswami, L., & Kim, B. S. (2022). Nanomaterial-Based Therapy for Wound Healing. Nanomaterials, 12(4).

11. Evelise, C., Barthès, J., Bat, E., Tezcaner, A., & Vrana, N. E. (2019). Use of Nanoparticles in Tissue Engineering and Regenerative Medicine.  Frontiers in Bioengineering and Biotechnology, 7.

12. The Pew Charitable Trusts. (2019). Defining Our Six Generations. Pew Trusts.

This article was written by Heather Schmidt, a contributing writer for Innerbody Research. She holds an MS and BS in Food Science and Technology, with a concentration in Food Microbiology, from Texas A&M University. The original research article can be found here .