Views of veterinary faculty students on the concept of Artificial Intelligence and its use in Veterinary Medicine practices: An example of Ankara University Faculty of Veterinary Medicine

Abstract

The study was carried out to determine the knowledge levels of the students of Ankara University Faculty of Veterinary Medicine, on the concept of artificial intelligence and its use in veterinary practices. For this purpose, an online questionnaire was applied to a total of 529 students in the study, covering all grades of the faculty. The questionnaire consists of two parts. In the first part, there are 10 questions including demographics, knowledge about the concept of artificial intelligence, etc. The second part consists of 26 5-point Likert-type questions to determine students' thoughts on artificial intelligence applications. Data were analyzed using statistical tests. Consequently, the students participating in the study are partially knowledgeable about artificial intelligence (52.9%). They know the importance of following the developments in artificial intelligence for the profession (45.2%). They think that artificial intelligence applications will improve their professional skills (53.5%). They have the opinion that a robot cannot replace a veterinary surgeon (36.7%) and artificial intelligence cannot cause unemployment in veterinary medicine in the future (35.3%). In addition, they believe that artificial intelligence can cause ethical problems (39.3%) and that applications made with this technology should be developed in an ethical sense (42.4%). As a result, while the students think that artificial intelligence will have positive effects in the field of veterinary medicine, they also think that artificial intelligence can bring negative ethical implications. It can be concluded that including elective courses on artificial intelligence applications in veterinary faculties and conducting further research on the subject would be beneficial.

Keywords

• Ankara University
• Artificial Intelligence
• Türkiye
• Veterinary Faculty

References

1. Adalı, E (2017): İnsanlaşan Makineler ve Yapay Zekâ. İTÜ Vakfı Dergisi, 75, 14-17.
2. Akyüz HÖ, Alkan S, Yücebaş SC (2021): Sağlık Hizmetleri Meslek Yüksek Okulu Öğrencilerinin Yapay Zeka Hakkında Bilgi Düzeylerinin İncelenmesi. Medical Research Reports, 4, 28-35.
3. Anonymous (2022). Artificial intelligence in veterinary medicine leads to efficiency and superior accuracy. Available at https://www.idexx.com. (Accessed July 27, 2022).
4. Anonymous (2022): Veteriner Hekimlikte Yapay Zeka ve Dijitalizasyon Eğitim Programı Başarıyla Gerçekleştirildi. Available at http://www.veterinary.ankara.edu.tr/2021/04/ 06/veteriner-hekimlikte-yapay-zeka-ve-dijitalizasyon-egitim-programi-basariyla-gerceklestirildi/. (Accessed July 29, 2022).
5. Attila AŞ (2022): Yapay Zekâ Teknolojisi ve Uygulamaları, Dikeyeksen Yayıncılık, İstanbul.
6. Bardot F (2022): Artificial intelligence, robots and unemployment: evidence from OECD countries. JIE&M, 1, 117-138.
7. Bostrom N, Yudkowsky E (2011): The ethics of artificial intelligence. 1-20. Cambridge Handbook of Artificial Intelligence, Cambridge University Press.
8. Chen L, Chen P, Lin Z (2020): Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264-75278.

9. Chiacchio F, Petropoulos G, Pichler D (2018): The impact of industrial robots on EU employment and wages: A local labour market approach. Bruegel Working Paper, 2, 1-35.
10. Choudhury A, Asan O (2020): Role of Artificial Intelligence in Patient Safety Outcomes. Systematic Literature Review. JMIR Med Inform, 8, 1-30.
11. Coşkun F, Gülleroğlu HD (2021): Yapay Zekanın Tarih İçindeki Gelişimi ve Eğitimde Kullanılması. AÜEBFD, 54, 947-966.
12. Çalık D, Çınar ÖP (2009): Geçmişten Günümüze Bilgi Yaklaşımları Bilgi Toplumu ve İnternet. XIV. Türkiye’de İnternet Konferansı Bildirileri. 77-88. İstanbul, Türkiye.
13. Çam MB, Çelik N, Göktepe ET, et al (2021): Öğretmen Adaylarının Yapay Zekâ Teknolojileri ile İlgili Farkındalıklarının Belirlenmesi. M Kemal Üni Sosyal Bilimler Enstitüsü Dergisi, 18, 263-285.
14. Doğaner A (2021): The approaches and Expectations of the Health Sciences Students towards Artificial Intelligence. Karya J of Health Sci, 2, 5-11.
15. Deng B (2015): Artificial intelligence joins hunt for human–animal diseases. Nature News, 1-2.
16. Dick S (2019): Artificial intelligence. HDSR, 1, 1-8.
17. Dos Santos DP, Giese D, Brodehl S, et al (2019): Medical Students' attitude towards Artificial İntelligence: A Multicentre Survey. Eur Radiol, 29, 1640-1646.
18. ECCVT (2018): Report of The ECCVT Expert Working Group on The Impact of Digital Technologies & Artifıcial Intelligence in Veterinary Education and Practice.
19. ECCVT (2020): Report of The ECCVT Expert Working Group on The Impact of Digital Technologies & Artifıcial Intelligence in Veterinary Education and Practice, Final Report.
20. Gökçen H, Gökçen İ (2021): Yapay zeka teknolojilerinin hayvan yetiştiriciliğindeki yeri ve önemi. Rum Vet Hek Derg, 93, 56-64.
21. Hamet P, Tremblay J (2017): Artificial intelligence in medicine. Metabolism Clinical and Experimental, 69, 36-40.
22. Keskinbora KH (2019): Medical ethics considerations on artificial intelligence. Journal of Clinical Neuroscience, 64, 277- 282.
23. Kour S, Agrawa R, Sharma N, et al (2022): Artificial Intelligence and its Application in Animal Disease Diagnosis. J Anim Res, 12, 1-10.
24. McCarthy J (2007): What is Artificial Intelligence? Available at https://www-formal.stanford.edu/jmc/ whatisai.pdf (Accessed July 20, 2022).
25. Morone G, Pirrera A, Meli P, et al (2022): Ethics and Automated Systems in the Health Domain: Design and Submission of a Survey on Rehabilitation and Assistance Robotics to Collect. Healthcare, 1-13.
26. Mutascu M (2021): Artificial intelligence and unemployment: New insights. Economic Analysis and Policy, 69, 653-667.
27. Nabiyev V, Erümit AK (2020): Eğitimde Yapay Zeka Kuramdan Uygulamaya. Pegem Akademi Yayınları, Ankara.
28. Öztürk K, Şahin Ergin M (2018): Yapay Sinir Ağları ve Yapay Zekaya Genel Bir Bakış. Takvim-i Vekayi, 6, 25-36.
29. Park SH, Do KH, Kim S, et al (2019): What should medical students know about artificial intelligence in medicine? J Educ Eval Health Prof, 1-6.
30. Reddy S, Fox J, Purohit MP (2019): Artificial intelligence-enabled healthcare delivery. J R Soc Med, 112, 22-28.
31. Rigby M (2019): Ethical dimensions of using artificial intelligence in health care. AMA Journal of Ethics, 21, 121-124.
32. Russell S, Dewey D, Tegmark M (2015): Research Priorities for Robust and Beneficial Artificial Intelligence. AI Magazine, 36, 105-114.
33. Shabbir J, Anwer T (2015): Artificial Intelligence and its Role in Near Future. Journal of Latex Class Files, 14, 1-11.
34. Silva MD, Badaro R, Santos A, et al (2019): Use of Artificial Intelligence on the Control of Vector-Borne Diseases. Vectors and Vector-Borne Zoonotic Diseases. Published February 20th, 2019.
35. Sit C, Srinivasan R, Amlani A, et al (2020): Attitudes and Perceptions of UK Medical Students towards Artificial İntelligence and Radiology: a Multicentre Survey. Insights Into Imaging, 11, 1-6.
36. Tamer HY, Övgün B (2020): Yapay Zeka Bağlamında Dijital Dönüşüm Ofisi. Ankara Üniversitesi SBF Dergisi, 75, 775-803.
37. Ural DA (2016): The use of new practices for assessment of body condition score. Rev MVZ Córdoba, 21, 5154-5162.
38. Wartman SA, Combs CD (2018): Medical Education Must Move From the Information Age to the Age of Artificial Intelligence. Academic Medicine, 93, 1107-1109.
39. Yılmaz Y, Uzelli Yılmaz D, Yıldırım D, et al (2021): Yapay Zeka ve Sağlıkta Yapay Zekanın Kullanımına Yönelik Sağlık Bilimleri Fakültesi Öğrencilerinin Görüşleri. SDÜ Sağlık Bilimleri Dergisi, 12, 297-308.