📄 social science

Stakeholder perceptions of ethical considerations, inclusivity and societal impact of artificial intelligence in Philippine higher education

This exploratory study of 290 stakeholders at a Philippine public university reveals that while ethical considerations are viewed similarly across groups, students, faculty, and administrators hold divergent perspectives on AI's inclusivity and societal impact, with both ethical and inclusivity factors independently predicting perceived societal benefits.

Original authors: John Jr. G., Vanjoreeh A. Madale, Victor S. Rosales, Monera A. Salic-Hairulla, Glay Vhincent Sumaylo, Adelfa C. Silor

Published 2026-10-16

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: John Jr. G., Vanjoreeh A. Madale, Victor S. Rosales, Monera A. Salic-Hairulla, Glay Vhincent Sumaylo, Adelfa C. Silor

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Artificial intelligence is no longer a distant concept confined to science fiction; it is quietly reshaping how universities teach, learn, and make decisions. From tools that grade essays to systems that predict which students might struggle, these technologies promise to make education more efficient and personalized. Yet, as these digital assistants enter the classroom, a critical question arises: do they actually help everyone, or do they widen the gap between those who have access and those who do not? This is not just a technical problem but a human one. It involves ethics, which concerns whether these tools are fair and safe; inclusivity, which asks if they work for people with different backgrounds and abilities; and societal impact, which looks at the broader consequences for the future of learning. In the Philippines, where rapid technological adoption meets uneven infrastructure, understanding these dynamics is vital. If a university embraces artificial intelligence without considering how it feels to the people using it, the technology risks becoming a source of division rather than a bridge to opportunity.

To explore these tensions, researchers at Mindanao State University–Iligan Institute of Technology turned to the people who live with these systems every day. They gathered 290 individuals, including students, teachers, and university administrators, to ask a simple but profound question: how do you feel about the role of artificial intelligence in your education? The researchers did not just ask if the technology worked; they asked three specific things. First, they asked about ethics: do people trust that the system is fair and protects their privacy? Second, they asked about inclusivity: does the technology make learning easier for everyone, or does it create new barriers? Finally, they asked about the bigger picture: does this technology improve society and the future of education? By comparing the answers from these three distinct groups, the team hoped to see if there was a shared vision or a deep divide in how the university community viewed the digital future.

The results revealed a landscape of cautious optimism mixed with distinct perspectives. Overall, the participants viewed artificial intelligence in a moderately positive light. They generally believed it could be used ethically and that it held promise for society. However, when the researchers looked closer at who was answering, clear differences emerged. The students, who are the primary users of these tools in the classroom, felt more confident that the technology was inclusive. They believed it helped them participate more fully. The teachers, or faculty members, were more reserved. They rated inclusivity lower than the students did, perhaps because they see the daily struggles of students who lack reliable internet, suitable devices, or the necessary skills to use these tools effectively. The teachers are the ones who must integrate these new systems into their lessons, and they are acutely aware of the practical hurdles that can leave some learners behind.

The administrators, the leaders who set policy and strategy, held the most positive view of all, but specifically regarding the societal impact. They were more likely to believe that artificial intelligence would benefit society as a whole compared to both the students and the teachers. This suggests a gap between the strategic vision of the institution and the lived experience of the classroom. While leaders see the potential for broad innovation and efficiency, the people in the trenches—teachers and students—are more focused on whether the tools actually work for everyone in their specific context. The study found that when people felt a system was ethical, they also tended to feel it was inclusive. Furthermore, when people felt a system was both ethical and inclusive, they were much more likely to believe it would have a positive impact on society. This connection implies that trust is built on a foundation of fairness and access; without those, the promise of a better future feels distant.

Despite these positive correlations, the researchers were careful to note the limits of their findings. The study was conducted at a single university, and the group of people surveyed was not a perfect mirror of the entire country. The measure used to gauge ethical concerns was also a bit shaky, meaning the numbers related to ethics should be seen as a starting point for discussion rather than a final verdict. The researchers did not prove that one factor causes another; they simply observed that these ideas are linked in the minds of the people they surveyed. They also could not determine if the teachers' lower ratings were due to anxiety about the technology or simply a realistic assessment of resource shortages. What remains clear is that the vision for artificial intelligence in education cannot be dictated from the top down alone. If the goal is to create a system that truly serves everyone, institutions must listen to the concerns of teachers who see the inequalities and the students who feel the barriers. The path forward requires a partnership where ethical safeguards, accessible design, and infrastructure readiness are developed together, ensuring that the future of learning is not just smart, but also fair for all.

Technical Summary: Stakeholder Perceptions of Ethical Considerations, Inclusivity, and Societal Impact of AI in Philippine Higher Education

Problem Statement
While artificial intelligence (AI) is rapidly reshaping higher education through generative tools, learning analytics, and automated decision support, empirical research often focuses on adoption intentions or technical performance rather than the lived experiences of diverse institutional stakeholders. A critical gap exists in understanding how students, faculty, and administrators within the same institution differentially evaluate the ethical considerations, inclusivity, and perceived societal impact of AI. This is particularly consequential in the Philippine context, where rapid AI uptake occurs alongside uneven infrastructure, digital literacy, and institutional readiness. Existing literature suggests that role-based judgments may reveal significant gaps between institutional strategy and classroom reality, yet few studies compare these perspectives across stakeholder groups within a single institution to inform participatory governance.

Methodology
This study employed a quantitative, cross-sectional survey design at Mindanao State University-Iligan Institute of Technology (MSU-IIT), a public higher education institution in the southern Philippines.

Participants: The sample consisted of 290 purposively recruited stakeholders: 185 students (63.8%), 65 faculty members (22.4%), and 40 administrators (13.8%).
Instrument: A questionnaire included 14 closed-ended items rated on a five-point scale, organized a priori into three composite indices:
1. Ethical Considerations (4 items): Focusing on autonomy, harm prevention, fairness, and accountability.
2. Inclusivity (5 items): Assessing accessibility, usability across diverse abilities, and meaningful participation.
3. Perceived Societal Impact (5 items): Evaluating contributions to educational equity, public trust, and the future of teaching.
Reliability and Validity: Internal consistency was assessed via Cronbach's alpha. The Inclusivity ( $\alpha = .829$ ) and Societal Impact ( $\alpha = .803$ ) indices demonstrated good consistency. The Ethical Considerations index showed low internal consistency ( $\alpha = .581$ ); consequently, the authors treated this index as an exploratory descriptive composite rather than a validated latent scale.
Statistical Analysis: Analyses utilized Welch's heteroskedasticity-robust omnibus tests and Games-Howell pairwise comparisons to account for unequal variances. Pearson correlations and role-adjusted ordinary least-squares (OLS) regressions with HC3 heteroskedasticity-robust standard errors were computed to examine associations between indices while controlling for stakeholder role.

Key Results

Descriptive Statistics: Overall perceptions were moderately positive across all three indices (Ethical: $M=3.47$ , Inclusivity: $M=3.62$ , Societal Impact: $M=3.73$ ).
Stakeholder Differences:
- Ethical Considerations: No statistically significant differences were found among students, faculty, and administrators ( $p = .135$ ). The authors note that the low reliability of this index may have reduced statistical precision.
- Inclusivity: Significant differences were observed ( $p = .004$ ). Students rated inclusivity significantly higher than faculty members (mean difference = 0.41, $p = .002$ ). Administrators did not differ significantly from either group.
- Perceived Societal Impact: Significant differences were found ( $p = .003$ ). Administrators reported significantly more positive ratings than both students ( $p = .008$ ) and faculty members ( $p = .004$ ). Students and faculty did not differ significantly.
Associations and Regression:
- All three indices were positively correlated ( $p < .001$ ). Ethical considerations correlated with inclusivity ( $r = .539$ ) and societal impact ( $r = .459$ ).
- In the role-adjusted regression model for Inclusivity, ethical considerations were a significant positive predictor ( $\beta = .517, p < .001$ ). Faculty members had significantly lower inclusivity ratings than students ( $\beta = -.165, p = .002$ ).
- In the model for Perceived Societal Impact, both inclusivity ( $\beta = .466, p < .001$ ) and ethical considerations ( $\beta = .213, p = .001$ ) remained independently associated with the outcome. The model explained 39.3% of the variance ( $R^2 = .393$ ). Administrators maintained higher societal impact ratings than students even after controlling for the other indices ( $\beta = .192, p < .001$ ).

Key Contributions
The study provides empirical evidence of a divergence between strategic and classroom perspectives regarding AI in a Philippine public university. It highlights that:

Role-Based Divergence: Administrators hold more optimistic views regarding the societal impact of AI, while faculty members express more reservation regarding inclusivity, potentially reflecting direct awareness of access barriers, variable AI literacy, and assessment challenges.
Interdependence of Dimensions: Ethical considerations and inclusivity are distinct but related dimensions that jointly influence perceptions of societal impact. The findings suggest that stakeholders who view AI as ethically responsible also tend to view it as more inclusive.
Contextual Relevance: The results underscore that in the Philippine setting, inclusivity is inseparable from infrastructure and institutional capacity, as benefits are uneven when learners differ in connectivity, devices, and digital literacy.

Significance and Claims
The authors position this work as an exploratory study rather than a source of validated, nationally representative estimates. They explicitly caution against interpreting the findings as causal evidence due to the cross-sectional design and the single-institution, purposive sample.

The paper claims that its primary significance lies in supporting participatory institutional governance. The findings suggest that effective AI integration requires moving beyond technical performance metrics to integrate ethical safeguards, accessibility, infrastructure readiness, and stakeholder consultation. Specifically, the authors argue that institutional AI policy should not be based on a single stakeholder viewpoint (e.g., administrative strategy alone) but must align with the lived educational experiences of faculty and students. The study advocates for an iterative approach where ethical safeguards, inclusive implementation, and empirical evaluation develop together, particularly in contexts facing resource constraints.

The authors conclude that while the ethical-considerations index requires further development and validation, the observed patterns support the need for governance mechanisms that translate broad ethical principles into concrete, context-sensitive educational technology decisions.

Technical Summary: Stakeholder Perceptions of Ethical Considerations, Inclusivity, and Societal Impact of AI in Philippine Higher Education

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