Beyond Deception: Exploiting Deepfake Technology for Ethical Innovation in Healthcare
Pages 70 - 78
Abstract
The significant growth in deepfake technology has triggered concerns over its potential for misuse and ethical consequences. While current literature primarily highlights these risks, this paper offers a unique perspective by exploring the beneficial applications of deepfakes in healthcare. We aim to shift the focus from negative to positive uses, demonstrating how deepfakes can promote ethical innovation and make substantial contributions to the healthcare sector. This study presents the possibilities of deepfake technology as an opportunity to promote ethical innovation that can substantially impact healthcare. Specifically, we examine how deepfakes can facilitate the creation of realistic patient personas to enhance the efficacy of communication and empathy training for healthcare professionals. Furthermore, we evaluate the technology's potential to generate realistic simulations for medical training, diagnosis, and treatment planning. We also explore the creative application of deepfakes in anonymising video records of patients. By altering the facial features of individuals in images or videos while preserving their expressions, this technology ensures patient privacy while capitalising on facial cues for diagnostic and therapeutic purposes. The integration of deepfakes in health care requires a thoughtful and ethical approach. It is essential to establish regulatory frameworks to ensure the responsible use of deepfakes in these critical domains. This paper addresses these ethical considerations, emphasising the importance of transparency and informed consent when employing deepfake technology in sensitive healthcare environments.
References
[1]
Sarwar Adeel. 2023. Replika: A Friend, Therapist, or Just an AI? The Pros and Cons of Mental Health and Companionship.
[2]
Aiden. 2024. The Best AI-Generated Fashion Show of Popular Leaders by Elon Musk.
[3]
John W Ayers, Adam Poliak, Mark Dredze, Eric C Leas, Zechariah Zhu, Jessica B Kelley, Dennis J Faix, Aaron M Goodman, Christopher A Longhurst, Michael Hogarth, et al. 2023. Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum. JAMA internal medicine, Vol. 183, 6 (2023), 589--596.
[4]
BBC Bitesize. 2019. Deepfakes: What are they and why would I make one? BBC Bitesize Articles (2019).
[5]
Nicholas Caporusso. 2021. Deepfakes for the good: A beneficial application of contentious artificial intelligence technology. In Advances in Artificial Intelligence, Software and Systems Engineering: Proceedings of the AHFE 2020 Virtual Conferences on Software and Systems Engineering, and Artificial Intelligence and Social Computing, July 16--20, 2020, USA. Springer, 235--241.
[6]
Anupama Chadha, Vaibhav Kumar, Sonu Kashyap, and Mayank Gupta. 2021. Deepfake: an overview. In Proceedings of second international conference on computing, communications, and cyber-security: IC4S 2020. Springer, 557--566.
[7]
Kiran Chandrappa and Krupa K Shankar. 2023. Combating deep fakes by the power of artificial intelligence and block chain in healthcare applications. In Unleashing the Potentials of Blockchain Technology for Healthcare Industries. Elsevier, 253--271.
[8]
Jee Charlotte. 2020. An Indian politician is using deepfake technology to win new voters.
[9]
Yash Chellani. 2021. A deep dive into Replika: My AI friend.
[10]
Bobby Chesney and Danielle Citron. 2019. Deep fakes: A looming challenge for privacy, democracy, and national security. Calif. L. Rev., Vol. 107 (2019), 1753.
[11]
Plaban Nath Chowdhury, Abhishek Vaish, Bipin Puri, and Raju Vaishya. 2024. Medical Education Technology: Past, Present and Future. Apollo Medicine (2024), 09760016241256202.
[12]
Justin D Cochran and Stuart A Napshin. 2021. Deepfakes: awareness, concerns, and platform accountability. Cyberpsychology, Behavior, and Social Networking, Vol. 24, 3 (2021), 164--172.
[13]
Dustin T Crystal, Nicholas G Cuccolo, Ahmed MS Ibrahim, Heather Furnas, and Samuel J Lin. 2020. Photographic and video deepfakes have arrived: how machine learning may influence plastic surgery. Plastic and reconstructive surgery, Vol. 145, 4 (2020), 1079--1086.
[14]
Sanja Dacic, William D Travis, Jennifer Margaret Giltnane, John Abel, Filip Kos, Stephanie Hilz, Stephanie Hennek, Junya Fujimoto, Lynette M Sholl, Farah Khalil, et al. 2021. Artificial intelligence (AI)--powered pathologic response (PathR) assessment of resection specimens after neoadjuvant atezolizumab in patients with non-small cell lung cancer: Results from the LCMC3 study. Journal of Clinical Oncology, Vol. 39, 15 (2021), 106 -- 106. https://doi.org/10.1200/jco.2021.39.15_suppl.106.
[15]
The Dali. 2023. dal ´ lives (via artificial intelligence). https://thedali.org/exhibit/ask-dali/ > [Accessed: 3 July 2024]
[16]
Lee Dami. 2019. Deepfake Salvador Dalí takes selfies with museum visitors. <https://www.theverge.com/2019/5/10/18540953/salvador-dali-lives-deepfakemuseum> [Accessed: 30 November 2023]
[17]
Adrienne De Ruiter. 2021. The distinct wrong of deepfakes. Philosophy & Technology, Vol. 34, 4 (2021), 1311--1332.
[18]
Beate Dejaco, Lex D de Jong, Harry Van Goor, J Bart Staal, Niki Stolwijk, and Jeremy Lewis. 2023. The concurrent validity and reliability of virtual reality to measure shoulder flexion and scaption range of motion. Physiotherapy, Vol. 120 (2023), 95--102.
[19]
Yogesh K Dwivedi, Laurie Hughes, Elvira Ismagilova, Gert Aarts, Crispin Coombs, Tom Crick, Yanqing Duan, Rohita Dwivedi, John Edwards, Aled Eirug, et al. 2021. Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International journal of information management, Vol. 57 (2021), 101994.
[20]
Alexander Godulla, Christian P Hoffmann, and Daniel Seibert. 2021. Dealing with deepfakes--an interdisciplinary examination of the state of research and implications for communication studies. SCM Studies in Communication and Media, Vol. 10, 1 (2021), 72--96.
[21]
Neil Greenberg, Mary Docherty, Sam Gnanapragasam, and Simon Wessely. 2020. Managing mental health challenges faced by healthcare workers during covid-19 pandemic. BMJ, Vol. 368 (2020).
[22]
David Güera and Edward J Delp. 2018. Deepfake video detection using recurrent neural networks. In 2018 15th IEEE international conference on advanced video and signal based surveillance (AVSS). IEEE, 1--6.
[23]
Jeffrey T Hancock and Jeremy N Bailenson. 2021. The social impact of deepfakes. Cyberpsychology, behaviour, and social networking, Vol. 24, 3 (2021), 149--152.
[24]
Saar Hoek, Suzanne Metselaar, Corrette Ploem, and Marieke Bak. 2024. Promising for patients or deeply disturbing? The ethical and legal aspects of deepfake therapy. Journal of Medical Ethics (2024).
[25]
Á Horváth and P Molnár. 2022. A review of patient safety communication in multicultural and multilingual healthcare settings with special attention to the US and Canada. Developments in Health Sciences, Vol. 4, 3 (2022), 49--57.
[26]
Ignas Kalpokas and Julija Kalpokiene. 2022. Deepfakes: a realistic assessment of potentials, risks, and policy regulation. Springer.
[27]
Achhardeep Kaur, Azadeh Noori Hoshyar, Vidya Saikrishna, Selena Firmin, and Feng Xia. 2024. Deepfake video detection: challenges and opportunities. Artificial Intelligence Review, Vol. 57, 6 (2024), 1--47.
[28]
Ihtiram Raza Khan, Veena Grover, Iram Fatima, Mehtab Alam, and Naved Ahmad. 2024. The Application of AI in Drug Discovery: Challenges, Opportunities, and Strategies. Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry (2024), 181--198.
[29]
Zahra Khanjani, Gabrielle Watson, and Vandana P Janeja. 2021. How deep are the fakes? focusing on audio deepfake: A survey. arXiv preprint arXiv:2111.14203 (2021).
[30]
Abhirup Khanna, May El Barachi, Sapna Jain, Manoj Kumar, and Anand Nayyar. 2024. Artificial Intelligence and Machine Learning in Drug Design and Development. John Wiley & Sons.
[31]
Jan Kietzmann, Linda W Lee, Ian P McCarthy, and Tim C Kietzmann. 2020. Deepfakes: Trick or treat? Business Horizons, Vol. 63, 2 (2020), 135--146.
[32]
Lorraine Kisselburgh and Jonathan Beever. 2022. The ethics of privacy in research and design: Principles, practices, and potential. In Modern socio-technical perspectives on privacy. Springer International Publishing Cham, 395--426.
[33]
Usha Kosarkar and Gopal Sakarkar. 2023. Unmasking Deepfakes Advancements, Challenges, and Ethical Considerations. In International Conference on Electrical and Electronics Engineering. Springer, 249--262.
[34]
Andrei OJ Kwok and Sharon GM Koh. 2021. Deepfake: a social construction of technology perspective. Current Issues in Tourism, Vol. 24, 13 (2021), 1798--1802.
[35]
Hao-Ping Lee, Yu-Ju Yang, Thomas Serban Von Davier, Jodi Forlizzi, and Sauvik Das. 2024. Deepfakes, Phrenology, Surveillance, and More! A Taxonomy of AI Privacy Risks. In Proceedings of the CHI Conference on Human Factors in Computing Systems. 1--19.
[36]
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen Awm Van Der Laak, Bram Van Ginneken, and Clara I Sánchez. 2017. A survey on deep learning in medical image analysis. Medical image analysis, Vol. 42 (2017), 60--88.
[37]
Bahar Uddin Mahmud and Afsana Sharmin. [n.,d.]. Deep insights of deepfake technology: A review. arXiv preprint arXiv:2105.00192 ( [n.,d.]).
[38]
Timothy D Malouff, Sarvam P TerKonda, Dacre Knight, Adam I Perlman, Bala Munipalli, Daniel V Dudenkov, Michael G Heckman, Launia J White, Katey M Wert, Jorge M Pascual, et al. 2021. Physician satisfaction with telemedicine during the COVID-19 pandemic: the Mayo Clinic Florida experience. Mayo Clinic Proceedings: Innovations, Quality & Outcomes, Vol. 5, 4 (2021), 771--782.
[39]
Mónica Vieira Martins, Luís Baptista, Henrique Luís, Victor Assuncc ao, Mário-Rui Araújo, and Valentim Realinho. 2023. Machine Learning in X-ray Diagnosis for Oral Health: A Review of Recent Progress. Computation, Vol. 11, 6 (2023), 115.
[40]
Malhi Mehhma. 2022. To see no longer means to believe: The harms and benefits of deepfake. <https://ethics.org.au/to-see-no-longer-means-to-believe-the-harms-and-benefits-of-deepfake/> [Accessed 1 January 2024].
[41]
Edvinas Meskys, Julija Kalpokiene, Paul Jurcys, and Aidas Liaudanskas. 2020. Regulating deep fakes: legal and ethical considerations. Journal of Intellectual Property Law & Practice, Vol. 15, 1 (2020), 24--31.
[42]
Arjun Panesar and Harkrishan Panesar. 2021. Artificial intelligence and machine learning in global healthcare. In Handbook of Global Health. Springer, 1775--1813.
[43]
Margot Paul, Kim Bullock, and Jeremy Bailenson. 2020. Virtual reality behavioral activation as an intervention for major depressive disorder: case report. JMIR mental health, Vol. 7, 11 (2020), e24331.
[44]
Ciyuan Peng, Tianqi Guo, Chengyao Xie, Xiaomei Bai, Jingjing Zhou, Xiaohui Zhao, Estrid He, and Feng Xia. 2024. mBGT: Encoding Brain Signals With Multimodal Brain Graph Transformer. IEEE Transactions on Consumer Electronics (2024). https://doi.org/10.1109/TCE.2024.3425478
[45]
Fabi Prezja, Juha Paloneva, Ilkka Pölönen, Esko Niinimäki, and Sami Äyrämö. 2022. DeepFake knee osteoarthritis X-rays from generative adversarial neural networks deceive medical experts and offer augmentation potential to automatic classification. Scientific Reports, Vol. 12, 1 (2022), 18573.
[46]
PrimaFelicitas. 2023. The Ethical Dilemma of Deepfake: Balancing Innovation and Misuse.
[47]
Jamshir Qureshi and Samina Khan. 2024. Artificial Intelligence (AI) Deepfakes in Healthcare Systems: A Double-Edged Sword? Balancing Opportunities and Navigating Risks. Preprints (February 2024). https://doi.org/10.20944/preprints202402.0176.v1
[48]
Retrace. [n.,d.]. Synthetic Medical Imaging: How Deepfakes Could Improve Healthcare. https://www.dentistrytoday.com/synthetic-medical-imaging-how-deepfakes-could-improve-healthcare/ [Accessed 7 January 2024].
[49]
Albert A Rizzo, Joann Difede, Barbara O Rothbaum, Scott Johnston, Robert N McLAY, Greg Reger, Greg Gahm, Thomas Parsons, Ken Graap, and Jarrell Pair. 2009. VR PTSD exposure therapy results with active duty OIF/OEF combatants. In Medicine Meets Virtual Reality 17. IOS Press, 277--282.
[50]
FEITELBERG ROSEMARY. 2024. Elon Musk Shares Super Fakes With AI-powered Fashion Show With World Leaders.
[51]
Kwashie Selasi. 2023. Artificial intelligence needs legislation, standards and society-wide education.
[52]
Hashim JF Shaikh, Sayyida S Hasan, Joshua J Woo, Ophelie Lavoie-Gagne, William J Long, and Prem N Ramkumar. 2023. Exposure to extended reality and artificial intelligence-based manifestations: a primer on the future of hip and knee arthroplasty. The Journal of Arthroplasty, Vol. 38, 10 (2023), 2096--2104.
[53]
Tawseef Ayoub Shaikh, Tabasum Rasool Dar, and Shabir Sofi. 2022. A data-centric artificial intelligent and extended reality technology in smart healthcare systems. Social Network Analysis and Mining, Vol. 12, 1 (2022), 122.
[54]
Beverley J Shea, Barnaby C Reeves, George Wells, Micere Thuku, Candyce Hamel, Julian Moran, David Moher, Peter Tugwell, Vivian Welch, Elizabeth Kristjansson, et al. 2017. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. BMJ, Vol. 358 (2017).
[55]
Jessica Silbey and Woodrow Hartzog. 2018. The upside of deep fakes. Md. L. Rev., Vol. 78 (2018), 960.
[56]
Christine A Sinsky, James T Jerzak, and Kevin D Hopkins. 2021. Telemedicine and team-based care: the perils and the promise. In Mayo Clinic Proceedings, Vol. 96. Elsevier, 429--437.
[57]
P Swathi and Saritha Sk. 2021. Deepfake creation and detection: A survey. In 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA). IEEE, 584--588.
[58]
Shima Tabatabai. 2020. Simulations and virtual learning supporting clinical education during the COVID 19 pandemic [response to letter]. Advances in Medical Education and Practice (2020), 669--671.
[59]
Rashid Tahir, Brishna Batool, Hira Jamshed, Mahnoor Jameel, Mubashir Anwar, Faizan Ahmed, Muhammad Adeel Zaffar, and Muhammad Fareed Zaffar. 2021. Seeing is believing: Exploring perceptual differences in deepfake videos. In Proceedings of the 2021 CHI conference on human factors in computing systems. 1--16.
[60]
Zec Kie Tan, Shao Zheng Chong, Chee Ying Kuek, and Eng Siang Tay. 2023. Individual legal protection in the deepfake technology era. In Proceedings of the 3rd International Conference on Law and Digitalization 2023 (ICLD 2023), Vol. 791. Springer Nature, 119.
[61]
Diana P Tobon, M Shamim Hossain, Ghulam Muhammad, Josu Bilbao, and Abdulmotaleb El Saddik. 2022. Deep learning in multimedia healthcare applications: a review. Multimedia systems, Vol. 28, 4 (2022), 1465--1479.
[62]
Huiling Tu, Shuo Yu, Vidya Saikrishna, Feng Xia, and Karin Verspoor. 2023. Deep Outdated Fact Detection in Knowledge Graphs. In IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, Shanghai, China, 1443--1452.
[63]
Luisa Verdoliva. 2020. Media forensics and deepfakes: an overview. IEEE journal of selected topics in signal processing, Vol. 14, 5 (2020), 910--932.
[64]
Gain Vish. 2022. How deepfakes and AI are being used to find new ways to treat diseases. https://www.siliconrepublic.com/innovation/deepfake-ai-healthcare-diseases-insilico-medicine-pharma [Accessed 1 January 2024]
[65]
Ge Wang, Andreu Badal, Xun Jia, Jonathan S Maltz, Klaus Mueller, Kyle J Myers, Chuang Niu, Michael Vannier, Pingkun Yan, Zhou Yu, et al. 2022. Development of metaverse for intelligent healthcare. Nature Machine Intelligence, Vol. 4, 11 (2022), 922--929.
[66]
Mika Westerlund. 2019. The emergence of deepfake technology: A review. Technology innovation management review, Vol. 9, 11 (2019).
[67]
Lucas Whittaker, Rory Mulcahy, Kate Letheren, Jan Kietzmann, and Rebekah Russell-Bennett. 2023. Mapping the deepfake landscape for innovation: A multidisciplinary systematic review and future research agenda. Technovation, Vol. 125 (2023), 102784.
[68]
Shen Xinmei. 2020. Professor's online students prefer when he teaches classes as anime girl. https://www.scmp.com/abacus/news-bites/article/3074961/professors-online-students-prefer-when-he-teaches-classes-anime [Accessed: 30 November 2023]
[69]
Felix Juefei Xu, Run Wang, Yihao Huang, Qing Guo, Lei Ma, and Yang Liu. 2022. Countering malicious deepfakes: Survey, battleground, and horizon. International Journal of Computer Vision (2022), 1--57.
[70]
Digvijay Yadav and Sakina Salmani. 2019. Deepfake: A survey on facial forgery technique using generative adversarial network. In 2019 International conference on intelligent computing and control systems (ICCS). IEEE, 852--857.
[71]
Hsuan-Chia Yang, Annisa Ristya Rahmanti, Chih-Wei Huang, and Yu-Chuan Jack Li. 2022. How can research on artificial empathy be enhanced by applying deepfakes? Journal of Medical Internet Research, Vol. 24, 3 (2022), e29506.
[72]
Sujin Yang, Kee-Deog Kim, Eiichiro Ariji, and Yoshitaka Kise. 2024. Generative adversarial networks in dental imaging: a systematic review. Oral Radiology, Vol. 40, 2 (2024), 93--108.
[73]
Hussain A Younis, Taiseer Abdalla Elfadil Eisa, Maged Nasser, Thaeer Mueen Sahib, Ameen A Noor, Osamah Mohammed Alyasiri, Sani Salisu, Israa M Hayder, and Hameed AbdulKareem Younis. 2024. A systematic review and meta-analysis of artificial intelligence tools in medicine and healthcare: applications, considerations, limitations, motivation and challenges. Diagnostics, Vol. 14, 1 (2024), 109.
[74]
Peipeng Yu, Zhihua Xia, Jianwei Fei, and Yujiang Lu. 2021. A survey on deepfake video detection. Iet Biometrics, Vol. 10, 6 (2021), 607--624.
[75]
Mohan Zalake. 2023. Doctors? perceptions of using their digital twins in patient care. Scientific Reports, Vol. 13, 1 (2023), 21693.
Index Terms
- Beyond Deception: Exploiting Deepfake Technology for Ethical Innovation in Healthcare
Recommendations
Mapping research strands of ethics of artificial intelligence in healthcare: A bibliometric and content analysis
AbstractThe growth of artificial intelligence in promoting healthcare is rapidly progressing. Notwithstanding its promising nature, however, AI in healthcare embodies certain ethical challenges as well. This research aims to delineate the most ...
Highlights- This paper analyses scientific articles on the ethics of AI in healthcare domain.
- This analysis detects the hottest ethical challenges in the domain.
- It identifies the most influential elements such as authors and documents.
- ...
Barriers to adoption of information technology in healthcare
CASCON '17: Proceedings of the 27th Annual International Conference on Computer Science and Software EngineeringHealthcare is an important pillar of society, critical for effectively responding to public health emergencies, and addressing disease, ill health, and poverty brought on by communicable disease and non communicable disease and cancer [7]. The ...
Comments
Information & Contributors
Information
Published In
October 2024
85 pages
ISBN:9798400711954
DOI:10.1145/3688868
- Program Chairs:
- Xuequan Lu,
- Wenxi Yue,
- Imran Razzak,
- Kun Hu,
- Jinglei Lv,
- Sen Zhang,
- Junhui Hou,
- Zhiyong Wang,
- Jiebo Luo,
- Wei Xiang
Copyright © 2024 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 31 October 2024
Check for updates
Author Tags
Qualifiers
- Research-article
Conference
MM '24
Sponsor:
MM '24: The 32nd ACM International Conference on Multimedia
October 28 - November 1, 2024
Melbourne VIC, Australia
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 160Total Downloads
- Downloads (Last 12 months)160
- Downloads (Last 6 weeks)30
Reflects downloads up to 27 Jan 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in