Artificial Intelligence-Generated Information and Public Trust: Exploring Filipino Voters' Perceptions of Flood Control Projects

Main Article Content

Maria Cristina S. Dela Cerna
Evelyn Torsino Bagood
Roselyn G. Malong
Chealbert B. Gasis

Abstract

Artificial Intelligence (AI)-generated information has transformed the way citizens access, interpret, and evaluate public information, influencing public trust in government communication and infrastructure initiatives. Despite the increasing use of AI-generated content, limited qualitative studies have examined its role in shaping public trust within the context of government projects. This study explored how Artificial Intelligence-generated information shapes public trust in relation to Filipino voters' perceptions of flood control projects. Guided by Social Support Theory and Trust Theory, the study employed an exploratory qualitative research design. Eighteen (18) purposively selected Filipino registered voters participated in semi-structured interviews, and the collected narratives were analyzed using Narrative Discourse Analysis. The findings revealed that AI-generated information enhances public understanding by improving access to governance information and encouraging information verification through credible sources. It also promotes greater awareness of government transparency and accountability while fostering critical evaluation of public infrastructure projects. However, participants emphasized that public trust remains dependent on the credibility, consistency, and reliability of official information rather than on AI-generated content alone. The study concludes that Artificial Intelligence serves as a complementary informational resource that supports informed civic engagement without replacing the need for transparent government communication. The findings highlight the importance of responsible AI use and credible public communication in strengthening public trust and promoting informed participation in governance

Article Details

How to Cite
Dela Cerna, M. C. S., Bagood, E. T., G. Malong, R., & B. Gasis, C. (2026). Artificial Intelligence-Generated Information and Public Trust: Exploring Filipino Voters’ Perceptions of Flood Control Projects. CINEFORUM, 66(S2), 8–15. Retrieved from https://revistadecineforum.com/index.php/cf/article/view/909
Section
Original Articles

References

Colì, E., Paciello, M., Lamponi, E., Calella, R., & Falcone, R. (2023). Adolescents and trust in online social interactions: A qualitative exploratory study. Children, 10(8), 1408.

Corrado, G., Corrado, L., De Michele, G., & Salustri, F. (2023). Are perceptions of corruption matching experience? Evidence from microdata. The British Journal of Criminology, 63(3), 687–708. https://doi.org/10.1093/bjc/azac071

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (2023). Opinion Paper:“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International journal of information management, 71, 102642.

Elsner, C. (2024). Shifting discussions to the supranational level: a narrative discourse analysis on nuclear energy sustainability and the EU Taxonomy. Energy, Sustainability and Society, 14(1), 69.

Gebrihet, H. G. (2024). The effects of the perception of corruption on public trust in government in Africa: A comparative analysis. Politikon, 51(1–2), 18–39. https://doi.org/10.1080/02589346.2023.2293517

Gebrihet, H. G., & Mwale, M. L. (2024). The effects of polarisation on trust in government: Evidence from Ethiopia. Transforming Government: People, Process and Policy, 18(2), 193–216. https://doi.org/10.1108/TG-08-2023-0115

GMA Network News. (2025). The corruption of Philippine flood control projects. https://www.gmanetwork.com/news/topstories/specialreports/967723/the-corruption-of-philippine-flood-control-projects/story/

Jimoh, A. L., Abdulrasaq, S., & Olawale, Y. A. (2025). Perceived corruption and political trust: The role of social media use. Transforming Government: People, Process and Policy, 19(1), 183–202.

Luo, J., Liu, X. B., Yao, Q., Qu, Y., Yang, J., Lin, K., ... & Yang, Z. (2024). The relationship between social support and professional identity of health professional students from a two-way social support theory perspective: Chain mediating effects of achievement motivation and meaning in life. BMC Medical Education, 24(1), 473. https://doi.org/10.1186/s12909-024-05410-2

Nasrolahi Vosta, L., & Jalilvand, M. R. (2024). How do technological media accelerate sustainable development? Mediating role of good governance and empowerment. Transforming Government: People, Process and Policy, 18(4), 529–554. https://doi.org/10.1108/TG-10-2023-0185

Noviaty, E. (2026). The effect of social support on relationship quality and social commerce intention. Jurnal Ilmiah Multidisiplin Indonesia (JIM-ID), 5(1), 16–24.

Okafor, O. N., Adebisi, F. A., Opara, M., & Okafor, C. B. (2020). Deployment of whistleblowing as an accountability mechanism to curb corruption and fraud in a developing democracy. Accounting, Auditing & Accountability Journal, 33(6), 1335–1366. https://doi.org/10.1108/AAAJ-12-2018-3792

Organisation for Economic Co-operation and Development (OECD). (2024). OECD framework for the classification of AI systems: A tool for effective AI policies. OECD Publishing. https://doi.org/10.1787/cb6d9eca-en

Suaib, S. (2024). Dynamics of social interaction, social support, and psychological well-being in urban communities: Social support theory perspective. International Journal of Religion, 5(11), 4786–4803.

UNESCO (2023). Guidance for Generative AI in Education and Research.https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research.