ISSN (Online): 2321-3418
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Engineering and Computer Science
Open Access

Integrating Legal, Ethical, and Technological Strategies to Mitigate AI Deepfake Risks through Strategic Communication.

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DOI: 10.18535/ijsrm/v11i08.ec02· Pages: 914-928· Vol. 11, No. 08, (2023)· Published: August 29, 2023
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Abstract

This study explores the critical role of legal education in addressing the challenges posed by AI deepfakes, with a focus on integrating deepfake-related topics into the curriculum to better prepare legal professionals. The primary objective is to examine how legal education can be enhanced to equip future lawyers with the necessary skills to navigate the ethical, legal, and technological implications of AI deepfakes. The study employs a theoretical approach, analyzing existing literature, case studies, and current legal frameworks to identify gaps in legal education and propose strategies for integrating AI deepfake topics into both foundational and continuing legal education (CLE) programs. The findings suggest that incorporating AI deepfake education into legal training can significantly enhance legal professionals' ability to address the complex challenges posed by this technology. Key strategies include developing specialized modules, implementing scenario-based learning, and fostering interdisciplinary collaboration. The study highlights the broader implications of these findings for future research and practice, emphasizing the need for ongoing updates to legal curricula and the importance of continuous professional development. The integration of AI deepfake education is not only necessary for legal practice but also for shaping ethical and legal standards in the digital age.

Keywords

AI deepfakeslegal educationethical implicationsinterdisciplinary collaborationcontinuing legal educationlegal frameworkstechnological challenges

References

  1. Agarwal, S., Farid, H., Gu, Y., He, M., Nagano, K., & Li, H. (2019). Protecting World Leaders Against Deep Fakes. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (pp. 38-45).Google Scholar ↗
  2. Bambauer, D. (2021). The Trouble with Fake News. Brooklyn Law Review, 86(2), 451-498.Google Scholar ↗
  3. Boland, J. (2008). Doe v. Boland, 698 F.3d 877 (6th Cir. 2012).Google Scholar ↗
  4. Calo, R. (2020). Artificial Intelligence Policy: A Primer and Roadmap. UCLA Law Review, 66(4), 1802-1846.Google Scholar ↗
  5. Chandler, A. (2022). Communicating AI Risks: Strategies for Engaging Non-Technical Audiences. Journal of Risk Research, 25(3), 285-303.Google Scholar ↗
  6. Chesney, R., & Citron, D. K. (2019). Deepfakes and the New Disinformation War: The Coming Age of Post-Truth Geopolitics. Foreign Affairs, 98(3), 147-155.Google Scholar ↗
  7. Chesney, R., & Citron, D. K. (2020). Deep Fakes: A Looming Challenge for Privacy, Democracy, and National Security. California Law Review, 108(5), 1753-1819.Google Scholar ↗
  8. Citron, D. K., & Chesney, R. (2020). Deep Fakes: A Looming Challenge for Privacy, Democracy, and National Security. California Law Review, 108(5), 1753-1819.Google Scholar ↗
  9. Crawford, K., Dobbe, R., Dryer, T., Fried, G., Green, B., Kaziunas, E., ... & Whittaker, M. (2022). AI Now 2022 Report. AI Now Institute.Google Scholar ↗
  10. Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., ... & Schafer, B. (2018). AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689-707.Google Scholar ↗
  11. Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., ... & Schafer, B. (2022). Ethics of Artificial Intelligence: Nature, Importance, and Complexity. Minds and Machines, 32(2), 365-391.Google Scholar ↗
  12. Garg, S., & Badr, Y. (2023). The Role of Public Awareness Campaigns in Combating AI Deepfakes. Journal of Communication Management, 27(1), 23-36.Google Scholar ↗
  13. Goodman, E. P., & Chen, S. L. (2021). Teaching Cyberlaw and the Governance of Emerging Technologies: Artificial Intelligence as a Lens. Journal of Legal Education, 70(2), 239-258.Google Scholar ↗
  14. Hagey, L. (2022). Training Lawyers for the AI Age: The Importance of Incorporating Technology in Legal Education. Harvard Journal of Law & Technology, 35(1), 321-345.Google Scholar ↗
  15. Hallahan, K., Holtzhausen, D., van Ruler, B., Vercic, D., & Sriramesh, K. (2007). Defining Strategic Communication. International Journal of Strategic Communication, 1(1), 3-35.Google Scholar ↗
  16. Hao, K. (2022). "How the Ukrainian government is using tech to fight Russian deepfakes." MIT Technology Review. Retrieved from https://www.technologyreview.com.Google Scholar ↗
  17. Henry, N., & Flynn, A. (2019). Image-based sexual abuse: The extent, nature, and responses to non-consensual pornography in Australia. Women’s Studies International Forum, 77, 105-114.Google Scholar ↗
  18. Jobin, A., Ienca, M., & Vayena, E. (2019). The Global Landscape of AI Ethics Guidelines. Nature Machine Intelligence, 1(9), 389-399.Google Scholar ↗
  19. Keller, D. (2019). The Malicious Use of AI: Forecasting, Prevention, and Mitigation. The Journal of Artificial Intelligence Research, 67, 409-415.Google Scholar ↗
  20. Kietzmann, J., Lee, L. W., McCarthy, I. P., & Kietzmann, T. C. (2020). Deepfakes: Trick or treat? Business Horizons, 63(2), 135-146.Google Scholar ↗
  21. Langvardt, K. (2020). Regulating the Deadliest Technology of All: Deepfakes, Free Speech, and the Long Road Ahead. Georgetown Law Technology Review, 5(2), 204-231.Google Scholar ↗
  22. Li, Y., Chang, M. C., & Lyu, S. (2020). In Ictu Oculi: Exposing AI Created Fake Videos by Detecting Eye Blinking. IEEE Transactions on Information Forensics and Security, 14(5), 980-988.Google Scholar ↗
  23. Ramos, L., Bautista, S., & Bonett, M. C. (2021, September). SwiftFace: Real-Time Face Detection: SwitFace. In Proceedings of the XXI International Conference on Human Computer Interaction (pp. 1-5).Google Scholar ↗
  24. Patibandla, K. R. (2024). Automate Amazon Aurora Global Database Using Cloud Formation. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 2(1), 262-270.Google Scholar ↗
  25. Patibandla, K. R. (2024). Design and Create VPC in AWS. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 1(1), 273-282.Google Scholar ↗
  26. Esfahani, M. N. Breaking Language Barriers: How Multilingualism Can Address Gender Disparities in US STEM Fields.Google Scholar ↗
  27. Thatoi, P. Strategizing P2P Investments using Socio-Economic Factors.Google Scholar ↗
  28. Khalili, A., Naeimi, F., & Rostamian, M. Manufacture and characterization of three-component nano-composites Hydroxyapatite Using Polarization Method.Google Scholar ↗
  29. Braimoh, J. (2020). The impact of texting language on Nigerian students: a case study of final year linguistics students. Per Linguam: a Journal of Language Learning= Per Linguam: Tydskrif vir Taalaanleer, 36(1), 15-31.Google Scholar ↗
  30. Braimoh, J. J. (2006). Examining the Difficulties of Acquiring the Past Subjunctive in L2 French. Hypothesis, 2008, 2013.Google Scholar ↗
  31. Braimoh, J. J. (2022). Linguistic Expressions of Pidgin in Nigerian Stand-up Comedy (Doctoral dissertation, The University of Mississippi).Google Scholar ↗
  32. Akpotoghogho, A., & Braimoh, J. J. (2024). The Phonetic Challenges of Vowel Elision for Nigerian Students of French for Specific Purpose (FOS). Valley International Journal Digital Library, 3488-3493.Google Scholar ↗
  33. BRAIMOH, J. J., & IGBENEGHU, B. Une Etude Syntaxique des Problèmes del’appropriation du Subjonctif Présent par les Apprenants de l’University of Benin au Nigéria.Google Scholar ↗
  34. OGUNTOLA, L. O., ANTHONY, H. M., & OYEWUMI, M. B. (2020). E-learning en période de la covid-19: les écoles nigérianes à la loupe. Akofena: Revue scientifique des Sciences du Langage, Lettres, Langues et Communication,(en ligne), consulté le, 22(01), 2022.Google Scholar ↗
  35. Erude, Adesuwa & Saeed, M. & Ondracek, James & Bertsch, Andy. (2024). Preventing Concussions and Head Injuries in College Football: A Case Study of Sports Management. Effulgence-AManagement Journal. 22. 57 - 73. 10.33601/effulgence.rdias/v22/i1/2024/57-73.DOI ↗Google Scholar ↗
  36. Nasr Esfahani, Mahshad. (2023). Breaking Language Barriers: How Multilingualism Can Address Gender Disparities in US STEM Fields. International Journal of All Research Education & Scientific Methods. 11. 2090-2100. 10.56025/IJARESM.2024.1108232090.DOI ↗Google Scholar ↗
  37. Amoako, K., Pusey, R. F., Haddad, W. A., Majin, S., Wheba, A., Okwuogori, C., ... & Sanisetty, V. H. (2023). PULM3: The Effects of a Two-step Coating Process and Flow on Artificial Lung Fiber Fouling. ASAIO Journal, 69(Supplement 2), 88.Google Scholar ↗
  38. CHOUDHARY, R., THATOI, P., & ROUT, S. S. (2024). Enhanced Prognostic Assessment of Glioblastoma Multiforme Using Machine Learning: Integrating Multimodal Imaging and Treatment Features: A review.Google Scholar ↗
  39. Thatoi, P., Choudhary, R., Shiwlani, A., Qureshi, H. A., & Kumar, S. (2023). Natural Language Processing (NLP) in the Extraction of Clinical Information from Electronic Health Records (EHRs) for Cancer Prognosis. International Journal, 10(4), 2676-2694.Google Scholar ↗
  40. Dahiya, S. (2024). Developing AI-Powered Java Applications in the Cloud Harnessing Machine Learning for Innovative Solutions. Innovative Computer Sciences Journal, 10(1).Google Scholar ↗
  41. Dahiya, S. (2024). Cloud Security Essentials for Java Developers Protecting Data and Applications in a Connected World. Advances in Computer Sciences, 7(1).Google Scholar ↗
  42. Dahiya, S. (2023). Safe and Robust Reinforcement Learning: Strategies and Applications. Journal of Innovative Technologies, 6(1).Google Scholar ↗
  43. Dave, A. (2013). PCIE configuration for data transfer at rate of 2.5-Giga Bytes per Second (GBPS): for data acquisition system.Google Scholar ↗
  44. Dave, A. (2021). A Survey of AI-based smart chiplets and interconnects for vehicles. North American Journal of Engineering Research, 2(4).Google Scholar ↗
  45. Dave, A., Banerjee, N., & Patel, C. (2023). FVCARE: Formal Verification of Security Primitives in Resilient Embedded SoCs. arXiv preprint arXiv:2304.11489.Google Scholar ↗
  46. Dave, A. (2021). Distributed Sensors Based In-Vehicle Monitoring and Security. North American Journal of Engineering Research, 2(4).Google Scholar ↗
  47. Gurjar, S., Chauhan, V., Suthar, M., Desai, D., Luhar, H., Patel, V., ... & Dave, N. (2022). Digital Eye for Visually Impaired—DEVI. In Intelligent Infrastructure in Transportation and Management: Proceedings of i-TRAM 2021 (pp. 131-139). Springer Singapore.Google Scholar ↗
  48. Patel, A. D. N. B. C. (2023). RARES: Runtime Attack Resilient Embedded System Design Using Verified Proof-of-Execution. arXiv preprint arXiv:2305.03266.Google Scholar ↗
  49. Dave, A., Banerjee, N., & Patel, C. (2021). Care: Lightweight attack resilient secure boot architecturewith onboard recovery for risc-v based soc. arXiv preprint arXiv:2101.06300.Google Scholar ↗
  50. Majid, M. E. (2018). Role of ICT in promoting sustainable consumption and production patterns-a guideline in the context of Bangladesh. Journal of Environmental Sustainability, 6(1), 1-14.Google Scholar ↗
  51. Kashem, S. B. A., Hasan-Zia, M., Nashbat, M., Kunju, A., Esmaeili, A., Ashraf, A., ... & Chowdhury, M. E. (2021). A review and feasibility study of geothermal energy in Indonesia. International Journal of Technology, Volume2, (1), 19-34.Google Scholar ↗
  52. bin Abul Kashem, S., Majid, M. E., Tabassum, M., Ashraf, A., Guziński, J., & Łuksza, K. (2020). A preliminary study and analysis of tidal stream generators. Acta Energetica, 6-22.Google Scholar ↗
  53. Kashem, S. B. A., Chowdhury, M. E. H., Majid, M. E., Ashraf, A., Hasan-Zia, M., Nashbat, M., ... & Esmaeili, A. (2021). A Comprehensive Review and the Efficiency Analysis of Horizontal and Vertical Axis Wind Turbines. European Journal of Sustainable Development Research, 5(3).Google Scholar ↗
  54. bin Abul Kashem, S., Majid, M. E., Tabassum, M., Iqbal, A., Pandav, K., & Abdellah, K. (2020). A Comprehensive Study and Analysis of Kinetic Energy Floor. Acta Energetica, (02), 6-13.Google Scholar ↗
  55. Abul, S. B., Forces, Q. A., Muhammad, E. H., Tabassum, M., Muscat, O., Molla, M. E., ... & Khandakar, A. A Comprehensive Study on Biomass Power Plant and Comparison Between Sugarcane and Palm Oil Waste.Google Scholar ↗
  56. Arefin, S., Chowdhury, M., Parvez, R., Ahmed, T., Abrar, A. S., & Sumaiya, F. (2024, May). Understanding APT detection using Machine learning algorithms: Is superior accuracy a thing?. In 2024 IEEE International Conference on Electro Information Technology (eIT) (pp. 532-537). IEEE.Google Scholar ↗
Author details
Samuel Ohizoyare Esezoobo
University of Arizona
✉ Corresponding Author
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Jimoh Junior Braimoh
University of Mississippi
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