Introduction
The integration of Artificial Intelligence (AI) in various fields, including dentistry, promises transformative changes. However, Generation Z (Gen Z), born roughly between 1997 and 2012, faces unique challenges in adopting AI within this domain. These challenges stem from a combination of technological, educational, and cultural factors that influence their readiness and willingness to embrace AI-driven innovations. This article explores the specific difficulties Gen Z encounters in adopting AI in dentistry.
Technological Barriers
One of the primary challenges Gen Z faces in adopting AI in dentistry is the technological barrier. While Gen Z is often considered digitally native, their proficiency with general digital technologies does not necessarily translate to specialized fields such as AI in dentistry. According to Smith and Anderson (2018), despite being highly familiar with digital interfaces, Gen Z often lacks the deeper understanding required to engage with complex AI systems. This gap in knowledge can lead to hesitation and a lack of confidence in utilizing AI-driven tools in dental practice.
Moreover, the rapid pace of AI development means that technologies are continually evolving, making it difficult for Gen Z to keep up. The steep learning curve associated with mastering AI applications in dentistry can be daunting. As noted by Faggella (2020), the frequent updates and advancements in AI require constant learning and adaptation, which can be overwhelming for young professionals who are still establishing their foundational skills in dentistry.
Educational Challenges
The integration of AI into the dental curriculum is still in its nascent stages. Many dental schools have not yet incorporated comprehensive AI training into their programs. According to a survey by Schwendicke, Göstemeyer, and Krois (2019), only a small percentage of dental schools worldwide include AI as a core part of their curriculum. This lack of formal education means that Gen Z dentists may graduate without the necessary skills to effectively use AI in their practice.
Additionally, the interdisciplinary nature of AI necessitates knowledge in both dental sciences and computer sciences. This dual expertise is rare and challenging to acquire. As highlighted by Chai et al. (2020), dental students and professionals often struggle to find resources and mentors who can provide adequate training in both areas. This educational gap further complicates the adoption of AI technologies among Gen Z dentists.
Cultural and Psychological Factors
Cultural and psychological factors also play a significant role in the reluctance of Gen Z to adopt AI in dentistry. Despite their digital proficiency, many Gen Z individuals express concerns about the ethical implications and potential job displacement associated with AI. A study by Deloitte (2020) found that while Gen Z is generally optimistic about technology, they are also more likely to question the ethical ramifications of AI, including issues of privacy, data security, and the potential for bias in AI algorithms.
Furthermore, the fear of job displacement is a significant psychological barrier. According to Frey and Osborne (2017), the automation of tasks traditionally performed by humans raises concerns about the future of certain professions, including dentistry. This fear can create resistance to adopting AI, as young dentists may worry that embracing these technologies could ultimately threaten their job security.
Economic Constraints
The cost of implementing AI technologies in dental practices can be prohibitive, particularly for young dentists who are just starting their careers. AI systems, such as diagnostic tools and robotic assistants, often require substantial financial investment. According to Market Research Future (2019), the high cost of AI technologies is a significant barrier to their widespread adoption in dental practices.
For Gen Z dentists, who may already be burdened with student loan debt and the expenses of setting up a new practice, the additional financial strain of investing in AI can be a deterrent. Without sufficient financial support or incentives, the adoption of AI in their practices remains a challenging prospect.
Regulatory and Standardization Issues
The regulatory landscape surrounding AI in dentistry is still evolving, with varying standards and guidelines across different regions. This lack of uniformity can create confusion and uncertainty for Gen Z dentists looking to incorporate AI into their practices. As highlighted by Patel et al. (2020), inconsistent regulations can hinder the adoption of AI by creating legal and operational uncertainties.
Moreover, the absence of standardized protocols for AI implementation in dentistry means that Gen Z dentists must navigate a complex and fragmented regulatory environment. This complexity can discourage them from adopting AI technologies, as they may perceive the regulatory hurdles as insurmountable.
Lack of Awareness and Promotion
Despite the growing presence of AI in many fields, there is still a lack of awareness and promotion regarding its applications in dentistry. Gen Z dentists may not fully understand the potential benefits and opportunities that AI can offer. According to a report by Accenture (2018), effective communication and promotion of AI technologies are crucial for driving adoption among younger professionals.
The dental industry needs to invest in targeted awareness campaigns and educational initiatives that highlight the practical applications and advantages of AI in dentistry. By showcasing success stories and providing hands-on demonstrations, the industry can help alleviate some of the skepticism and resistance that Gen Z dentists may have towards AI.
Conclusion
The adoption of AI in dentistry by Generation Z is fraught with challenges that stem from technological, educational, cultural, psychological, economic, and regulatory factors. While Gen Z is often seen as digitally adept, the specific demands of AI in dentistry require a deeper level of expertise and understanding that is currently lacking. Addressing these challenges requires a concerted effort from educational institutions, industry stakeholders, and regulatory bodies to provide the necessary training, resources, and support. By overcoming these barriers, Gen Z can fully harness the transformative potential of AI in dentistry, leading to improved patient outcomes and more efficient dental practices.
References
Accenture. (2018). Accenture Technology Vision 2018. Retrieved from https://www.accenture.com/us-en/insights/technology/technology-trends-2018
Chai, W., Sun, K., Li, M., Sun, L., & Zhang, X. (2020). Artificial intelligence in dentistry: a review. Frontiers in Medicine, 7, 555634. doi:10.3389/fmed.2020.555634
Deloitte. (2020).
Global Millennial Survey 2020. Retrieved from https://www2.deloitte.com/global/en/pages/about-deloitte/articles/millennialsurvey.html
Faggella, D. (2020). The state of AI in dental care and dentistry – 2020. Emerj. Retrieved from https://emerj.com/ai-sector-overviews/the-state-of-ai-in-dental-care-and-dentistry-2020/
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerization? Technological Forecasting and Social Change, 114, 254-280. doi:10.1016/j.techfore.2016.08.019
Market Research Future. (2019). AI in dentistry market research report. Retrieved from https://www.marketresearchfuture.com/reports/ai-in-dentistry-market-8277
Patel, V. L., Shortliffe, E. H., Stefanelli, M., Szolovits, P., Berthold, M. R., Bellazzi, R., & Abu-Hanna, A. (2020).
The coming of age of artificial intelligence in medicine. Artificial Intelligence in Medicine, 46(1), 5-17. doi:10.1016/j.artmed.2020.03.001
Schwendicke, F., Göstemeyer, G., & Krois, J. (2019). How artificial intelligence can advance dental research and clinical practice. Journal of Dental Research, 98(8), 740-745. doi:10.1177/0022034519847832
Smith, A., & Anderson, M. (2018). Social media use in 2018. Pew Research Center. Retrieved from https://www.pewresearch.org/internet/2018/03/01/social-media-use-in-2018/
Faggella, D. (2020). The state of AI in dental care and dentistry – 2020. Emerj. Retrieved from https://emerj.com/ai-sector-overviews/the-state-of-ai-in-dental-care-and-dentistry-2020/
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerization? Technological Forecasting and Social Change, 114, 254-280. doi:10.1016/j.techfore.2016.08.019
Market Research Future. (2019). AI in dentistry market research report. Retrieved from https://www.marketresearchfuture.com/reports/ai-in-dentistry-market-8277
Patel, V. L., Shortliffe, E. H., Stefanelli, M., Szolovits, P., Berthold, M. R., Bellazzi, R., & Abu-Hanna, A. (2020). The coming of age of artificial intelligence in medicine. Artificial Intelligence in Medicine, 46(1), 5-17. doi:10.1016/j.artmed.2020.03.001
Schwendicke, F., Göstemeyer, G., & Krois, J. (2019). How artificial intelligence can advance dental research and clinical practice. Journal of Dental Research, 98(8), 740-745. doi:10.1177/0022034519847832
Smith, A., & Anderson, M. (2018). Social media use in 2018. Pew Research Center. Retrieved from https://www.pewresearch.org/internet/2018/03/01/social-media-use-in-2018/ps://www2.deloitte.com/global/en/pages/about-deloitte/articles/millennialsurvey.html
Faggella, D. (2020). The state of AI in dental care and dentistry – 2020. Emerj. Retrieved from https://emerj.com/ai-sector-overviews/the-state-of-ai-in-dental-care-and-dentistry-2020/
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerization? Technological Forecasting and Social Change, 114, 254-280. doi:10.1016/j.techfore.2016.08.019
Market Research Future. (2019). AI in dentistry market research report. Retrieved from https://www.marketresearchfuture.com/reports/ai-in-dentistry-market-8277
Patel, V. L., Shortliffe, E. H., Stefanelli, M., Szolovits, P., Berthold, M. R., Bellazzi, R., & Abu-Hanna, A. (2020). The coming of age of artificial intelligence in medicine. Artificial Intelligence in Medicine, 46(1), 5-17. doi:10.1016/j.artmed.2020.03.001
Schwendicke, F., Göstemeyer, G., & Krois, J. (2019). How artificial intelligence can advance dental research and clinical practice. Journal of Dental Research, 98(8), 740-745. doi:10.1177/0022034519847832
Smith, A., & Anderson, M. (2018). Social media use in 2018. Pew Research Center. Retrieved from https://www.pewresearch.org/internet/2018/03/01/social-media-use-in-2018/
Commentaires