POTENTIAL BENEFITS OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TO OVERCOME HEALTH CONSEQUENCES OF SEXUAL VIOLENCE: THE CASE OF THAILAND AND INDIA
DOI:
https://doi.org/10.14456/acsr.2024.16Keywords:
Sexual Violence, Artificial Intelligence, Machine Learning, Thailand, IndiaAbstract
Sexual violence has become a significant global issue that can result in everlasting and life-threatening consequences that directly impact women's health. Also, Sexual violence is considered perhaps the most severe form of violence, often taking place among other forms of violence. The exact prevalence appears to be challenging to figure out, however, it probably impacts a minimum of one-third of women at least once in their lifespan. This paper will examine whether the integration of modern techniques can be a game-changer for dealing with the health outcomes of sexual assault survivors, Artificial Intelligence and machine learning will involve significant change, particularly in countries like Thailand and India where there is societal stigma around sexual violence along with massively underreported cases. In this research, we discuss the potential benefits of AI and ML in alleviating health effects on sexual assault survivors by discussing technological advancements including data-driven insights to influence healthcare delivery.
References
Daniel, C. (2023). Socio-Economic Determinants of Gender-Based Violence [GBV]: SDG Analytics on the Global GBV Scenario with Special Reference to Technology Facilitated Gender-Based Violence and Adolescent Birth Rates. Doctor of Public Health Thesis, New York Medical College.
Harbishettar, V., & Math, S. (2014). Violence against women in India: Comprehensive care for survivors. Indian Journal of Medical Research, 140(2), 157-159.
Julián, R., & Acevedo, D. (2022). The Banality of (Automated) Evil: Critical Reflections on the Concept of Forbidden Knowledge in Machine Learning Research. RECERCA. Revista De Pensament I Anàlisi, 27(2), 1-26.
Muneer, A., & Fati, S. (2020). A Comparative Analysis of Machine Learning Techniques for Cyberbullying Detection on Twitter. Future Internet, 12(11), 187.
Nascimento, F. (2021). Contributions of Machine Learning to Knowledge Acquisition in the Field of Social Sciences. Master of Computer Science Thesis, Universidade Federal do Rio Grande do Sul.
Pathak, S., Solanki, V., & Linh, N. (2024). Gender Biasness – A Victim of Artificial Intelligence-Based Development. In D. Mishra, A. Ngoc Le, & Z. McDowell. (eds.). Communication Technology and Gender Violence (pp. 81-98). Cham: Springer.
Promchertchoo, P. (2020). Alleged sex attacks on schoolgirls in Thailand prompt national reckoning on patriarchy, gender bias. Retrieved from www.channelnewsasia.com/asia/thailand-rape-patriarchy-power-gender-933231.
Raj, A., Dehingia, N., Singh, A., McAuley, J., & McDougal, L. (2021). Machine learning analysis of non-marital sexual violence in India. eClinicalMedicine, 39, 101046.
Saaliq, S. (2024). Gang Rape of a Tourist in India Highlights Culture of Downplaying Sexual Violence. Retrieved from https://thediplomat.com/2024/03/gang-rape-of-a-tourist-in-india-highlights-culture-of-downplaying-sexual-violence/.
Sharma, S., Singh, G., & Sharma, M. (2021). A comprehensive review and analysis of supervised-learning and soft computing techniques for stress diagnosis in humans. Computers in Biology and Medicine, 134, 104450.
Shikhila, T., & Kanth, B. (2023). Intimate partner violence among married couples in India: A systematic review. The Open Psychology Journal, 16, e187435012309110.
Singh, B. (2024). Social Cognition of Incarcerated Women and Children: Addressing Exposure to Infectious Diseases and Legal Outcomes. In K. Reddy. (ed.). Principles and Clinical Interventions in Social Cognition (pp. 236-251). Pennsylvania: IGI Global.
Singh, B., Jain, V., Kaunert, C., Dutta, P., & Singh, G. (2024). Privacy Matters: Espousing Blockchain and Artificial Intelligence (AI) for Consumer Data Protection on E-Commerce Platforms in Ethical Marketing. In S. Saluja, V. Nayyar, K. Rojhe, & S. Sharma. (eds.). Ethical Marketing Through Data Governance Standards and Effective Technology (pp. 167-184). Pennsylvania: IGI Global.
Socatiyanurak, V., Klangpornkun, N., Munthuli, A., Phienphanich, P., Kovudhikulrungsri, L., Saksakulkunakorn, N., Chairaungsri, P., & Tantibundhit, C. (2021). LAW-U: Legal Guidance through Artificial Intelligence Chatbot for Sexual Violence Victims and Survivors. IEEE Access, 9, 131440-131461.
Somhar, T. (2023). Thailand ranks among top 10 countries for violence against women and girls. Retrieved from www.nationthailand.com/thailand/general/40031638.
Statista. (2022). Number of reported rape cases in India 2005-2021. Retrieved from www.statista.com/statistics/632493/reported-rape-cases-india/.
Sumano, B. (2020). Abuse against women still prevalent. Retrieved from https://tdri.or.th/en/2020/11/abuse-against-women-still-prevalent/.
UNFPA. (2024). Technical Consultative Meeting on Universal Health Coverage (UHC) Package for Gender-Based Violence (GBV) Cases in Thailand. Retrieved from https://thailand.unfpa.org/en/Consultative-Meeting-UHC-GBV-package.
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