Artificial Intelligence, Moral Imagination, and Intergenerational Justice in Sustainable Education

Artificial Intelligence, Moral Imagination, and Intergenerational Justice in Sustainable Education | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Artificial Intelligence, Moral Imagination, and Intergenerational Justice in Sustainable Education Ishaq Ibrahim, Ali Nasser Al-Tahitah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9034636/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract This study examines the role of artificial intelligence (AI) on future generation (FG) mediated by sustainable development (SD). The nexus of artificial intelligence and sustainable development moderated by justice and ethics. Current AI revolution threaten the FG in education by higher plagiarism, losing critical skills, inequitable access, bias and discrimination, data privacy, misinformation and reliability issues. Ethics and Justice examined as moderators in relationship between AI and SD. Quantitative method employed and survey distributed amongst two explored perceptions students and lecturers. A sample size of 582 response been collected and analysed via AMOS. Students data resulted as there is a significant direct impact of AI on FG, a significant mediation statistical role of SD on the relationship between AI and FG, influence of AI on SD found to have insignificant statistical moderating role of Ethics & Justice. Lecturers data differently only Ethics were significantly statistically moderating AI and SD. Thus, education sector recommended to enrich the awareness of students in ethical frame importance in AI usage toward SD in the FG. Artificial intelligence Sustainable development Moral imagination Ethics Justice Future generations Intergenerational responsibility Sustainable education Figures Figure 1 Figure 2 1. Introduction The evolving landscape of artificial intelligence (AI) is rapidly transforming the educational sector, offering both unprecedented opportunities and critical challenges for sustainable development (Dissanayake, et al., 2025 ). As societies move towards the Fourth Industrial Revolution, the integration of AI into education is seen not only as a means to enhance learning experiences and administrative efficiency but also as a crucial strategy for preparing future generations to thrive in a world shaped by technological complexity (Al-Zahrani, & Alasmari, 2024 ). The deployment of AI technologies enables personalized learning, supports inclusive practices, and helps educators address diverse learner needs, aligning education with the values of justice and ethical responsibility (Mansour, et al., 2026 ). For future generations, sustainable development in education requires a holistic approach that integrates ethical considerations and justice into AI adoption (Meier, et al., 2026 ). AI-driven platforms are increasingly being used to widen access to quality education, democratize learning opportunities, and facilitate lifelong skill development, all of which are key priorities under the United Nations Sustainable Development Goals (SDGs) (Fu, & Weng, 2024 ; Bisiriyu, & Dhar, 2025 ). In this context, the education sector faces pressing questions about the ethical implications of data-driven decision making (Al-Zu’bi, et al., 2026 ). The education sector faces a critical challenge in preparing future generations for a rapidly changing and technology-driven world. Many young learners continue to experience educational gaps due to insufficient resources, inadequate digital infrastructure, lack of adaptive and personalized learning approaches (James, Malkin, & Nusche, 2025 ). Failure to bridge AI usage will deepen already existing educational inequalities, leaving millions of youth unprepared for labour market demands and lifelong learning in an AI-augmented world (Harry, 2023 ). Mental health challenges, social exclusion, and economic disadvantages are likely to become more pronounced, threatening the cohesive and sustainable development of societies (Schiff, 2022 ). The inability to adapt education to technological and social changes will also hinder progress toward Sustainable Development Goals (SDGs), potentially stalling national and global development efforts (Selwyn, 2022 ). Conversely, ensuring equitable access to technology, implementing inclusive and personalized learning, and supporting teacher training in digital skills that is what future generations are more likely to thrive. Students will gain the competencies needed for digital world, be more resilient to social and environmental change, and contribute meaningfully to sustainable societies (Ng, Chan, & Lo, 2025 ). Addressing these problems will foster innovation, close opportunity gaps, and better equip youth to tackle complex global issues in the decades to come. Table 1 Research Problems Summary Problems Consequences If Unresolved Outcomes If Solved Digital Inequality and Access Widening Achievement Gaps and Educational Inequity Equitable Educational Opportunities Algorithmic Bias and Fairness Reinforced Socio-economic Disparities Robust Ethical Safeguards Data Privacy and Surveillance Privacy Breaches and Loss of Trust Inclusive and Personalized Learning Teacher Preparedness Undermined Social Cohesion Empowered Educators with Digital Skills Loss of Human Touch Poor Development of Critical and Ethical Thinking Balanced Human-AI Interaction Source: Developed by researcher 2026 Table 1 listing certain issues such as inequality and access, bias, data privacy and surveillance, teachers’ preparedness and loss of human touch appears with AI usage in education sector. These issues will be reflected on education sector as achievement gaps and inequity, socio-economic disparities, privacy breaches, lack of trust, poor social cohesion and declining ethical thinking. Nonetheless, this gap shall be filled to ensure the existence of fair educational opportunities, enhance ethical procedures, establish personalized learning, improve teachers’ skills and find Human-AI interaction education base. In education sector issues of students and lecturers are not similar where lecturers interfering with student’s high demand and expectation in term of immediate actions and responses (Browne, & Foss, 2023 ). On the other hand, students believe in disappearing and replacing every existed learning style calling it as “old style” coming to the loud voice and explanations in classrooms to be replaced all by technology and AI (Shi and Ye 2016; Pfeffer 2015 ). 2. Literature Review and Hypotheses Development This section including previous studies discussed AI, FG, SD, ethics and justice in education sector. Based on literature body and hypothesis development concluded in conceptual model to be examined, research questions, research objectives. FG in this study representing future students in schools and universities in term of knowledge and skills. The term defined in education sector as transforming education process to be more suitable for future learners, mindset of future students to be expected and prepared for adaptive and inclusive education system ensuring sustainability, empathy, tolerance and responsibility of lecturers and students (Nur, Zamroni, & Tamam, 2024). In this particular research paper future generation proposed as a gap to be filled by improving the current situation to the targeted situation which is sustainable future generation. Thus, examining artificial intelligence and sustainable development as predictors future generation. Studies including (Shribala, & Jhaneswaran, 2024 ; Wang, et al., 2024 ; Ali, et al., 2024 ) discussed the existed impact of AI on FG for instance in Shribala, & Jhaneswaran, ( 2024 ) that there is negative influence of AI on performance, knowledge and skills of students in education sector. On the other hand, Wang, et al., ( 2024 ) reported AI as promoter of future generation goodness in term of improving learning quality and personalise learning based on student’s needs and situations. Ali, et al., ( 2024 ) confirmed the importance of AI in education systems to be adopted and concerned by policymakers, the study highlighted role of AI in shaping future generation mentality, thinking, perceptions and skills. Jobin, Ienca, & Vayena, ( 2019 ) critically explored AI role in education sector and found that well-structured guideline must be developed for both students and lecturers to understand how, why and when to use AI in education, ethical frame and justice are necessary to be part of the guidelines, adequate implementation for the guidelines to be in full vision as a strategy including diverse ways and solutions in education sector. Taherdoost, & Madanchian, ( 2024 ); Tai, ( 2020 ) emphasizing the transformative effects of AI on social, economic, and industrial aspects, shaping future human activities and capacities. Excessive reliance on AI by future students may impede the development of critical writing, research, and language skills. This dependence risks academic integrity and reduces critical thinking as AI-generated responses may lack depth or nuance. Accordingly the first hypothesis in this paper was developed as: H1: There is a significant positive impact of AI on FG . In addition, Gohr, et al., ( 2025 ); Maghsoudi, Mohammadi, & Bakhtiari, 2025 negotiated that AI is the highest potential and most significant predictor of sustainable development in both developed and developing countries. In construction industry (Regona, et al., 2024 ) finalized the review by confirming the ability of AI in ensuring sustainable development to be conditional with full concern and implementation of ethical frame including privacy and resilience. To examine the effect of AI on SD in education sector this research developed: H2: There is a significant positive impact of AI on SD Table 2 Literature Summary Variable/Relation Literature Artificial Intelligence → Future Generation Shribala, & Jhaneswaran, 2024 ; Wang, et al., 2024 ; Ali, et al., 2024 Artificial Intelligence → Sustainable Development Gohr, et al., 2025 ; Maghsoudi, Mohammadi, & Bakhtiari, 2025 ; Regona, et al., 2024 Sustainable Development → Future Generation Năstasă, Dumitra, & Grigorescu, 2024 ; Abdeldjalil, Mohammed, & Asma, 2024 Sustainable Development Mediating the relationship between artificial intelligence and future generation Gohr, et al., 2025 ; Maghsoudi, Mohammadi, & Bakhtiari, 2025 ; Emina, 2021 Ethics and Justice moderating AI and Sustainable Development Source: Developed by researcher 2026 Emina, ( 2021 ) affirmed the role of SD in developing FG, to manage this role responsibility, skills, knowledge and attitude must be considered as principles of sustainability amongst coming generation, where the research involved fairness, equity and stress minimization as moderators of SD. According to Qadeer, et al., ( 2022 ) attainment of SD threated by several factors such as AI, lecturer’s readiness, rapid changes, technological revolution and population growth, this research proposed AI to be predictor of SD, in the same study Qadeer highlighted SD assurance for well-being of future generations. Thus, this paper proposing: H3: There is a significant positive impact of SD on FG Gohr, et al., ( 2025 ); Maghsoudi, Mohammadi, & Bakhtiari, ( 2025 ) both studies negotiating the effect on artificial intelligence on industrial improvement reflected on potential future generations improvement in term of skills and other. This research proposing: H4: There is a positive mediating role of SD on the relationship between AI and FG UNESCO website stated ethics as factor ensuring AI delivers sustainable development by framing regulations and limitation of using AI such as matters related to discrimination, transparency, bias and privacy where ethics crucially influencing the relationship (Wang, et al., 2025 ). Ethics can amplify or inhibit influence of AI on sustainable development thus sustained future generation (Vinuesa, et al., 2020 ). Based on literature hypothesis developed as: H5: There is a significant positive moderating role of ethics on the relationship between AI and SD Justice prioritizing AI positivity to be reflected on sustainable development goals (Pendyala, 2024; Al-Adwan, 2025 ). At the same time that AI promoting SD in sectors justice is assuring global regulations and rules and policy makers concerning human rights and equitable education system (Javed, & Li, 2025 ). In the same study concluded that for successful AI integration toward SD requires justice existence and consideration to robust global policy coordination, financial support and equitable benefit regulations to be released which is preventing any hard could be caused by AI usage. Following hypothesis was: H6: There is a significant positive moderating role of justice on the relationship between AI and SD The combination oof ethics and justice as moderators in one model based on (Aini, et al., 2025 ; Vinuesa, et al., 2020 ). This research paper examines the proposed model in education sector using the variables as visually presented in Fig. 2 . Meanwhile to support the development of research model theoretical framework was developed as well in Fig. 1 . T-EESST theory support accepting technology with sufficient awareness whenever developing balanced strategy between technological, environmental, economic and social aspects for sustainability in sectors and communities, this theory ensures comprehensive development and sustainable development with minimized negativity and harms. This is crucial for policy makers to concern this theory and serve the purpose of theory existence (Al-Emran, 2023 ). Technology Acceptance Model (TAM) explaining how students and lecturers should adopt AI, policy makers should also understand the mechanism of healthy adoption for targeted future generation. This model contains perceived usefulness which is to what extent users believe that AI is greaten their performance and perceived ease of use which is to what extent users believe that AI won’t be complicated while using and could even learning process for students and teaching process for lecturers (Na, et al., 2022 ; Mogaji, et al., 2024 ). In similar context stakeholder theory has been employed to maintain all beneficiaries interest considering ethics and justice (Matthews, et al., 2025 ; da Costa, Gonçalves, & Montez, 2023 ). Theory of sustainable development developed involved to support the current study model by ensuring sustainable development for the capital of the process, where it is students and future generation in this particular research. This theory allocated here to serve the goodness of future generation based on sustainable development goals set by policy makers toward the prosperity of future generations and the world (Emina, 2021 ). Based on research hypothesis development referring to literature and supportive theories this research proposed the following conceptual mode to be examined Fig. 2 . 3. Methods The paper employed quantitative method to collect the required data for data analysis. The research designed as cross sectional survey as it is more appropriate for unknown population size and geographical limitation existence to be considered as population-based survey (Setia, 2016 ). Furthermore non-probability sampling method, where the data collected from both lecturers and students based on characteristics of being working lecturer and enrolling students both levels undergraduate and graduate levels the particular suitable sampling method is quota sampling method where the sub-groups are students and lecturers (Arrogante, 2022 ). Questionnaires was utilized as measurement tool to collected the targeted data by preparing google form and distribute it amongst lecturers and students from multiple region. Total participants of 582 divided into 217 lecturers and 365 students has been screened and excluded 3 participants due to technical issue to remain total 579 as 217 lecturers and 362 students. The data will be analysed using two software, one is SPSS for descriptive analysis, outliers and multicollinearity and another is AMOS for hypothesis testing. 4. Findings Descriptive Analysis This section contain several sub-sections clarifying data analysis process starting with descriptive analysis and reliability test. The below table contains the questionnaire’s items for all study’s variables and reliability test, mean, standard deviation, critical ratio, average variance extracted and source for all items. The questionnaire’s items adapted from previous studies as stated in the table below, only reliability represented by Cronbach’s Alpha for this validated questionnaire’s statements. Items obtained the scores confirming the reliability as more than 0.7 for each items (Hussey, et al., 2025). Means of FG items obtained scores in range of 3.65 to 4.82, for AI items mean obtained in range of 3.68 to 4.80, for SD items mean obtained in range of 3.94 to 4.86, ethics items obtained means range of 4.03 to 4.95, justice items obtained means in range of 3.70 to 4.91. Table 3: Descriptive analysis, reliability test and sources Items Cronbach’s Alpha Mean Standard Deviation CR AVE Source Future Generation FG1 Future generation’s knowledge can be improved by using AI in education. 0.743 4.29 1.592 .867 .926 Holmes, Bialik, & Fadel, 2019 FG2 To obtain sustained learning outcomes in future generation, ethics should be carefully regulated in education sector. 0.832 4.07 1.083 FG3 There are significant ethical risks on students, involved in using AI technologies in school settings. 0.730 4.59 1.799 Jobin, Ienca, & Vayena, 2019 FG4 None of communities would be left behind if AI employed fairly and inclusively in education. 0.759 4.82 1.037 FG5 Deployment AI in education with tailored ethical frame ensuring sustainable development for future generation skills and value. 0.722 4.72 1.530 FG6 Future generation will benefit from AI deployment in education by easing access to knowledge and information. 0.835 3.98 1.776 Vinuesa et al., 2020 FG7 Several educational and social challenges for future generation will be solved by AI. 0.858 3.85 1.689 FG8 Future generation will benefit most if sustainable development is integrated in curriculum. 0.806 3.65 1.930 Artificial Intelligence AI1 AI potentially accelerate student’s sustainable development. 0.829 3.78 1.847 .809 .941 Kulkov et al., 2024 AI2 AI in education improving the progress, monitor and forecasting future generation development. 0.889 4.31 1.927 AI3 AI usage should follow ethical guidance to prevent discrimination and bias amongst students. 0.902 4.65 1.990 Jobin et al., 2019 AI4 Social equity obtained by AI deployment avoiding unequal sustainable development in education. 0.857 4.80 1.852 AI5 AI is a potential tool to improve education in sustainable way for future generations. 0.871 3.68 1.967 Vinuesa et al., 2020 AI6 In education using AI protects well-being of future generation. 0.890 3.71 1.907 Sustainable Development SD1 Concerning student’s sustainable development requires AI systems training for lecturers. 0.928 4.86 1.932 .873 .884 Kulkov et al., 2024 SD2 In education sector there should be policies and regulations to ensure positive outcomes without harming societies. 0.903 4.06 1.958 Jobin et al., 2019 SD3 AI usage in schools and universities lead to personalized learning then sustainable awareness and creativity. 0.965 4.11 1.950 Michael, et al., 2020 SD4 In education sector students should learn to innovate solutions toward promoting sustainability. 0.900 4.85 1.944 Na-Nan, et al., 2024 SD5 Teaching students about sustainable practice is important for long-term development. 0.894 3.94 1.528 Ethics E1 AI usage in education must prioritize student’s privacy and data protection for sustainable development goals. 0.896 4.03 1.578 .911 .890 Jobin, Ienca, & Vayena, 2019 E2 Transparency is crucial and concerned in AI systems used in sustainable development. 0.892 4.68 1.420 E3 There is accountability on AI users to ensure communities sustainability. 0.911 4.95 1.849 Holmes, Bialik, & Fadel, 2019 E4 Ethical frames concerning bias and discrimination in AI-driven sustainability. 0.942 4.31 1.488 E5 Following ethical standard in AI promotes trust and enhance sustainable development in education sector. 0.903 4.08 1.702 Mittelstadt, et al., 2016 Justice J1 AI in education promotes availability and equal access to resources and opportunity to ensure sustainable development. 0.910 3.70 1.758 .927 .914 Vinuesa et al., 2020 J2 AI tools in education reducing poverty and inequality for sustained societies. 0.893 3.96 1.460 J3 AI should be used against bias and inequalities for sustainability initiatives in education sector. 0.883 4.16 1.932 J4 AI providing chances for neglected communities. 0.899 4.22 1.869 J5 Ethical implementation of AI in education sector ensuring social justice and positively affecting sustainable development. 0.921 4.91 1.499 Note: Prepared by author. Abbreviations: AVE, average variance extracted; CR, composite reliability. KMO 0.938 The standard deviation of FG items scored in range of 1.037 to 1.930, AI items scored standard deviation in range of 1.847 to 1.990, SD items scored standard deviation in range of 1.528 to 1958, ethics items standard deviation scored range of 1.420 to 1.849, justice scored standard deviation in range of 1.460 to 1.932. The critical ratios scored more than 2 which is accepted according to (Collier, 2020) as FG scored .867, AI scored .809, SD scored .873, Ethics scored .911, justice scored .927. Average variance extracted AVE recommended score more than 0.5 according to (Fornell, & Larcker, 1981) FG variable scored .926, AI scored .941, SD scored .884, ethics scored .890, justice scored .914. These results indicating the acceptance descriptive analysis for the items of questionnaires. The measurement analysis included multicollinearity, VIF and tolerance were accepted according to (Sarstedt et al. 2023) in range of 1.299 to 1.427 as usual statistical accepted score, tolerance in range of 0.542 to 0.701as good and accepted scores, CFI above 0.9 to score 0.95, Chi-Square less than 3 as 2.901, SRMR less than 0.05 as very good value of 0.022 (Hu, & Bentler, 1999). RMSEA scored less than 0.08 as 0.009 according to (Henseler, et al., 2016). Table 4: Measurement evaluation Variable VIF Tolerance CFI Chi-Square SRMR RMSEA Future Generation 1.427 0.701 0.95 2.901 0.022 0.009 Artificial Intelligence 1.366 0.542 Sustainable Development 1.394 0.599 Ethics 1.299 0.635 Justice 1.352 0.662 Note: Prepared by author The correlation of all variables on each other was very good which FG-AI correlated at 0.492, FG-SD correlated at 0.550, FG-ethics correlated at 0.438, FG-justice correlated at 0.683, AI-SD correlated at 0.811, AI-ethics correlated at 0.704, AI-justice correlated at 0.658, SD-ethics correlated at 0.483, SD-justice correlated at 0.546, ethics-justice correlated at 0.752, as all of these values accepted according to (Kang, et al., 2021). To provide comprehensive and detailed presentation of hypothesis testing of this research structural model as in (table 3) was necessary to showcasing each of direct and indirect relationships, P value, RMSEA and CFI conducted in structural equation modelling SEM by AMOS. Direct relationships for lecturer’s sample model indicated RMSEA=0.059 and CFI-0.931 where both scores accepted and indicating the goodness of the model. On the other hand, student’s model RMSEA=0.004 and CFI=0.909 as well indicating goodness of the model. This section will elaborate all results of direct relationships for both models (lecturer’s sample model and student’s sample model). First hypothesis H1 examining the positive impact of AI on FG which results reported as path coefficient= 0.564 with significant P value=***, concluded the acceptance of the hypothesis. For student’s model scored path coefficient= 0.477, P value= 0.002 which is less than 0.05 to indicate the significancy of the relationship and accepting the hypothesis in student’s model. Table 3: Direct paths hypothesis testing results Path Path Coefficient Sig RMSEA CFI Result Direct Relationships (Lecturer’s Model) AI à FG 0.564 *** 0.059 0.931 Accepted AI à SD 0.197 *** Accepted SD à FG 0.246 *** Accepted Direct Relationships (Student’s Model) AI à FG 0.477 0.002 0.004 0.909 Accepted AI à SD 0.519 *** Accepted SD à FG 0.638 0.012 Accepted Note: Prepared by author Second hypothesis H2 examining the positive impact of AI on SD, lecturer’s model indicated path coefficient=0.197, P value=***, which indicated accepted hypothesis. Meanwhile, student’s model resulted in path coefficient=0.519, P value=***, indicated accepted hypothesis as well. Third hypothesis H3 examining the positive impact of SD on FG, lecturer’s model found path coefficient=0.246, P value=***, to affirm the acceptance of the hypothesis. On another hand, student’s model found path coefficient=0.638, P value 0.012 which is less than 0.05 to assure the acceptance of the hypothesis. The following tests results as listed in (table 4) for the indirect relationships rolling of the mediator SD in the relationship between AI and FG, the moderators E & J rolling the relationships between AI and SD. Table 4: Indirect paths hypothesis testing results Path Indirect Effects Sig Results Mediation & Moderation (Lecturer’s Model) AI à Me SD à FG 0.248 *** Accepted AI à MoE à SD 0.098 *** Accepted AI à MoJ à SD 0.115 *** Accepted Mediation & Moderation (Student’s Model) AI à Me SD à FG 0.404 *** Accepted AI à MoE à SD -0.006 0.153 Rejected AI à MoJ à SD -0.293 0.071 Rejected Note: Prepared by author MeSD= mediator sustainable development, MoE= Moderator ethics, MoJ= Moderator justice The results in (table 4) obtained from the structural model presented in (figure 3). Hypothesis 4 predicting a positive mediation of SD on the relationship between AI and FG. Results of indirect effect found in lecturer’s model to be 0.248, P value=***, indicating the acceptance of the hypothesis. Whereas, in student’s model for the same hypothesis indicated indirect effect=0.404, P value=***, resulted that there is a positive and significant mediation role of SD on the relationship between AI and FG in both (Lecturer’s and Student’s) models. Hypothesis 5 predicting a positive moderation of E on the relationship between AI and SD. Lecturer’s model examined Hypothesis 5 resulted as indirect effect=0.098, P value***, indicating the acceptance of the hypothesis. Thus, in student’s model hypothesis 5 examined and resulted as indirect effect=-0.006, P value=0.153, indicating rejecting hypothesis 5 due to negative indirect effect and insignificant P value being higher than 0.05. Hypothesis 6 estimating positive moderation role of J on the relationship between AI and SD. Lecturer’s model resulted indirect effect of 0.115, P value=***, indicating the acceptance of the hypothesis. Meanwhile, student’s model resulted indirect effect=-0.293, P value=0.071, indicating reject hypothesis 6 due to the negative effect and P value being higher than 0.05. The results will be discussed in details in the following section. 5. Discussion In term of direct relationships, lecturer’s and student’s models affirmed the positive and significant impact of AI on FG amongst lecturers, the results comes algin with (Thomas, 2022) reported that AI definitely significantly influencing the future generation’s knowledge, skills and personalized learning. Zhang, Zhu, & Su, (2023) sorted critical need for developing a theory to guide and structuralize human behaviours and knowledge through using AI to be safe, reliable, extensible and sophisticated technology toward well prepared FG. Accordingly, the importance of AI for FG is definite, obtaining plenty of advantages and being competitive is mainly sourced by technology utilization toward providing fair chances to everyone to learn and save time, cost and effort in learning process. In sequence, second direct relationship of AI and SD in education sector resulted as significant and positive at the same time confirming results found in previous studies as AI is crucial in education and needed for SD within the acknowledgment of policymakers of pros and cons of AI adaption in this particular industry (Goralski, & Tan, 2020). Additionally, Gohr, et al., (2025) concluded that AI is playing a role to sustain SD in the firms with ensuring balanced contextualization and generalizability in providing knowledge fits towards responsible changes. On the other hand, Vinuesa, et al., (2020) assured that SD carries both possibilities (positive and negative effect) on society, environment and economy needed for government role to maintain it. In other studies conducted by (Kulkov, et al., 2024; Mienye, Sun, & Ileberi, 2024) suggested a conceptual model for AI optimization of SD which includes certain variables such as strategic alignment, infrastructure development, change management, and continuous improvement. The third direct relationship between SD and FG was accepted as positive and significant relationship in both models (lecturers and students). Previous research Emina, (2021) affirmed that sustainable development is reflecting the situation of future generation. Achievement of better future generation led by sustainable development is not easily obtained which countries and governments shall work for it as early as possible (Holden, Linnerud, & Banister, 2014). The indirect relationships starting with SD mediating role in the relationship between AI and FG. Results confirmed the significant positive mediating role of SD in the relationship between AI and FG in both lecturers and students models, where its affirming results stated in (Năstasă, Dumitra, & Grigorescu, 2024). Justice and ethics moderating AI toward critical governance (Taeihagh, 2021), ethics examined in this research and found significantly and positively moderating the relationship between AI and SD in lecturer’s mode. Literature reported significant moderation of ethics on SD (Hai Yen, et al., 2023), in education sector ethics has a significant moderating role with AI (Ahmed, 2024). In student’s model the hypothesis was rejected as ethics got insignificant and negative moderating role on the relationship between AI and SD, which indicates the neglection of students for ethical perception where they only concentrate on how easy the info is afforded. This finding is reflecting the different understanding of both lecturers and students to the concept of education and learning process from being learning skills and adding knowledge and information through discussion, analysis and brain storming from lecturers perception to shortest time to do assignments and easiest way to answers questions in this technology revolution from student’s perception. Here where is the ethical consideration allocated in both perceptions. Finally, justice examined as moderator on the relationship between AI and SD in two different samples. Lecturers sample found justice as significant and positive moderator on the relationship to be aligned with several previous studies employing justice as moderator but in this study its examined for the first time moderating AI and SD in education sector. Student’s model at the same time examined justice as a moderator on the same relationship and found to be rejected. These results embodied in major concern as students shown neglection of ethics and justice in AI usage in education sector. 6. Implications The significant findings of this research enhancing the awareness of people in charge toward further direction and monitoring of AI usage behavior amongst students. Accordingly, policies, rules and regulation should be developed to protect AI daily use of students within ethical frame and guarantee the intergenerational justice. Devoting values amongst students and lecturers could help lecturers to guide and advice students how, when and where is the right time and matter for using AI in their education journey. As well as, students will be able to investigate, ask and gathering information using AI tools with no full relying on it as main and only source but double checking the information before using it by students. This is reflected on future generation knowledge and sustaining the contentious development amongst the intergeneration. 7. Conclusion In conclusion, objectives of this paper embodied in examining direct effect of AI on each of SD and FG, indirect effect of AI on FG mediated by SD and indirect effect on AI on SD moderated by ethics and justice employed in two models (lecturer's and student’s). found to be going in different directions as lecturers reckon than AI is a self and personalized learning tools improving the quality and accuracy of education sector. AI widen student’s sights and expanding knowledge to facilitate and equalize learning opportunities and vacancies hunting. Meanwhile, students' perception to AI is a guaranteed provider for all required knowledge during their study journey. Neglecting ethical consequences and free restrictions allowing them to practice that. Students are not aware about justice importance in learning opportunities and vacancies eligibility. In addition, AI is playing a vital role in maintaining the sustainable development in education sector which surely will be reflected on skills, knowledge and behavior of the future generation ifthe ethical frame is taking a place in learning process. This research recommends authority of education sector to enhancethe awareness amongst students in term of healthy usage, lecturers shall involve tasks critical thinking based on enforce students using their pure skills, qualifying the lecturers to enable them directing the students, using contemporary methods to guide students properly, restricting AI usage in the continuous assessments and exams. Policymakers in education sector should set policies for AI usages to ensure the betterment of FG. 8. Limitation and Future Research This research has been challenging during data collection from lecturers where mostly lecturers don’t have time and shown no interest to fill up the questionnaires. Furthermore, students filling up the questionnaires without responsible sense in their answers. Thus, future researcher recommended to conduct qualitative research for collected data from lecturers where the interview could be more meaningful with reasonable findings. Declarations Funding Declaration There is no fundings for this research Ethical Declarations Ethics, Consent to Participate, and Consent to Publish declarations: not applicable. Consent to Participate This study approached students up to 18 years old and lecturers where as informed consent was obtained from all participants involved in the study. Ethics Approval The protocol was approved by The Human Research Ethics Committee (JKEP) and was conducted in accordance with the USIM/JKEP/2025-107. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Universiti Sains Islam Malaysia. Consent to Publish Not applicable. Data Availability The data been collected in this study is available and could be shared soft copy in excel file whenever is required. But there is no link for the data to be provided and possibility to do so because the data still needed for further research. References Abdeldjalil C, Mohammed K, Asma O. Digitalization and sustainable development: A literature review focused on artificial intelligence (2019–2024). J Law Sustainable Dev. 2024;12(11):e4155–4155. Ahmed H. (2024). Institutional integration of artificial intelligence in higher education: The moderation effect of ethical consideration. Int J Educational Reform, 10567879241247551. Aini Q, Purwanti P, Muti RN, Fletcher E. Developing sustainable technology through ethical ai governance models in business environments. ADI J Recent Innov. 2025;6(2):145–56. Al-Adwan MAS. Harnessing Artificial Intelligence for Environmental Sustainability: Ethical Considerations and Practical Implications in Achieving SDG 9 And SDG 16. 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Artificial intelligence and sustainable development during the pandemic: An overview of the scientific debates. Heliyon, 10(9). Năstasă A, Dumitra TC, Grigorescu A. (2024). Artificial intelligence and sustainable development during the pandemic: An overview of the scientific debates. Heliyon, 10(9). Ng DTK, Chan EKC, Lo CK. Opportunities, challenges and school strategies for integrating generative AI in education. Computers and Education: Artificial Intelligence; 2025. p. 100373. Nur M, Zamroni Z, Tamam B. (2024, December). Transforming Education To Prepare Future Generations To Face Global Challenges. In Proceeding Of International Conference On Education, Society And Humanity (Vol. 2, No. 2, pp. 1539–1545). Pendyala VS. (2024, December). The impact of Artificial Intelligence on Ecojustice and Ethics. In Proceedings of the 8th International Conference on Data Science and Management of Data (12th ACM IKDD CODS and 30th COMAD) (pp. 353–357). Pfeffer J. In: Leadership BS, editor. Fixing Workplaces and Careers One Truth at a Time. New York: Harper Collins; 2015. Qadeer A, Anis M, Ajmal Z, Kirsten KL, Usman M, Khosa RR, Zhao X. Sustainable development goals under threat? Multidimensional impact of COVID-19 on our planet and society outweigh short term global pollution reduction. Sustainable Cities Soc. 2022;83:103962. Regona M, Yigitcanlar T, Hon C, Teo M. Artificial intelligence and sustainable development goals: Systematic literature review of the construction industry. Sustainable Cities Soc. 2024;108:105499. Sarstedt M, Hair JF Jr., Ringle CM. 2023. PLS-SEM: Indeed a Silver Bullet – Retrospective Observations and Recent Advances. Journal of Marketing Theory and Practice 31, no. 3: 261–275. ttps://doi.org/10.1080/10696 679. 2022. 2056488. Schiff D. Education for AI, not AI for education: The role of education and ethics in national AI policy strategies. Int J Artif Intell Educ. 2022;32(3):527–63. Selwyn N. The future of AI and education: Some cautionary notes. Eur J Educ. 2022;57(4):620–31. Setia MS. Methodology series module 3: Cross-sectional studies. Indian J dermatology. 2016;61(3):261–4. Shi Y, and M. Ye. Responsible Leadership: Review and Prospects. Am J Industrial Bus Manage. 2016;6(8):877–84. 1 0.4236/ajibm.2016.68083. Shribala V, Jhaneswaran S. Impact of Artificial Intelligence in Education. Shanlax Int J Manage. 2024;11:8–11. Strubell E, Ganesh A, McCallum A. (2019). Energy and policy considerations for deep learning in AI. Proceedings of AAAI. Taeihagh A. Governance of artificial intelligence. Policy Soc. 2021;40(2):137–57. Taherdoost H, Madanchian M. (2024). The Impact of Artificial Intelligence on Research Efficiency. Tai MCT. The impact of artificial intelligence on human society and bioethics. Tzu chi Med J. 2020;32(4):339–43. Thomas M. (2022). The future of AI: how artificial intelligence will change the world. Built in, 10. 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Introduction","content":"\u003cp\u003eThe evolving landscape of artificial intelligence (AI) is rapidly transforming the educational sector, offering both unprecedented opportunities and critical challenges for sustainable development (Dissanayake, et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). As societies move towards the Fourth Industrial Revolution, the integration of AI into education is seen not only as a means to enhance learning experiences and administrative efficiency but also as a crucial strategy for preparing future generations to thrive in a world shaped by technological complexity (Al-Zahrani, \u0026amp; Alasmari, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe deployment of AI technologies enables personalized learning, supports inclusive practices, and helps educators address diverse learner needs, aligning education with the values of justice and ethical responsibility (Mansour, et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). For future generations, sustainable development in education requires a holistic approach that integrates ethical considerations and justice into AI adoption (Meier, et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). AI-driven platforms are increasingly being used to widen access to quality education, democratize learning opportunities, and facilitate lifelong skill development, all of which are key priorities under the United Nations Sustainable Development Goals (SDGs) (Fu, \u0026amp; Weng, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Bisiriyu, \u0026amp; Dhar, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this context, the education sector faces pressing questions about the ethical implications of data-driven decision making (Al-Zu\u0026rsquo;bi, et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). The education sector faces a critical challenge in preparing future generations for a rapidly changing and technology-driven world. Many young learners continue to experience educational gaps due to insufficient resources, inadequate digital infrastructure, lack of adaptive and personalized learning approaches (James, Malkin, \u0026amp; Nusche, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Failure to bridge AI usage will deepen already existing educational inequalities, leaving millions of youth unprepared for labour market demands and lifelong learning in an AI-augmented world (Harry, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Mental health challenges, social exclusion, and economic disadvantages are likely to become more pronounced, threatening the cohesive and sustainable development of societies (Schiff, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The inability to adapt education to technological and social changes will also hinder progress toward Sustainable Development Goals (SDGs), potentially stalling national and global development efforts (Selwyn, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Conversely, ensuring equitable access to technology, implementing inclusive and personalized learning, and supporting teacher training in digital skills that is what future generations are more likely to thrive. Students will gain the competencies needed for digital world, be more resilient to social and environmental change, and contribute meaningfully to sustainable societies (Ng, Chan, \u0026amp; Lo, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Addressing these problems will foster innovation, close opportunity gaps, and better equip youth to tackle complex global issues in the decades to come.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResearch Problems Summary\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsequences If Unresolved\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOutcomes If Solved\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDigital Inequality and Access\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidening Achievement Gaps and Educational Inequity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEquitable Educational Opportunities\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgorithmic Bias and Fairness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReinforced Socio-economic Disparities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRobust Ethical Safeguards\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData Privacy and Surveillance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivacy Breaches and Loss of Trust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInclusive and Personalized Learning\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeacher Preparedness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUndermined Social Cohesion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEmpowered Educators with Digital Skills\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoss of Human Touch\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePoor Development of Critical and Ethical Thinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBalanced Human-AI Interaction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eSource: Developed by researcher 2026\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e listing certain issues such as inequality and access, bias, data privacy and surveillance, teachers\u0026rsquo; preparedness and loss of human touch appears with AI usage in education sector. These issues will be reflected on education sector as achievement gaps and inequity, socio-economic disparities, privacy breaches, lack of trust, poor social cohesion and declining ethical thinking. Nonetheless, this gap shall be filled to ensure the existence of fair educational opportunities, enhance ethical procedures, establish personalized learning, improve teachers\u0026rsquo; skills and find Human-AI interaction education base.\u003c/p\u003e \u003cp\u003eIn education sector issues of students and lecturers are not similar where lecturers interfering with student\u0026rsquo;s high demand and expectation in term of immediate actions and responses (Browne, \u0026amp; Foss, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). On the other hand, students believe in disappearing and replacing every existed learning style calling it as \u0026ldquo;old style\u0026rdquo; coming to the loud voice and explanations in classrooms to be replaced all by technology and AI (Shi and Ye 2016; Pfeffer \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e"},{"header":"2. Literature Review and Hypotheses Development","content":"\u003cp\u003eThis section including previous studies discussed AI, FG, SD, ethics and justice in education sector. Based on literature body and hypothesis development concluded in conceptual model to be examined, research questions, research objectives.\u003c/p\u003e\n\u003cp\u003eFG in this study representing future students in schools and universities in term of knowledge and skills. The term defined in education sector as transforming education process to be more suitable for future learners, mindset of future students to be expected and prepared for adaptive and inclusive education system ensuring sustainability, empathy, tolerance and responsibility of lecturers and students (Nur, Zamroni, \u0026amp; Tamam, 2024). In this particular research paper future generation proposed as a gap to be filled by improving the current situation to the targeted situation which is sustainable future generation. Thus, examining artificial intelligence and sustainable development as predictors future generation.\u003c/p\u003e\n\u003cp\u003eStudies including (Shribala, \u0026amp; Jhaneswaran, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Wang, et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ali, et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) discussed the existed impact of AI on FG for instance in Shribala, \u0026amp; Jhaneswaran, (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) that there is negative influence of AI on performance, knowledge and skills of students in education sector. On the other hand, Wang, et al., (\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) reported AI as promoter of future generation goodness in term of improving learning quality and personalise learning based on student\u0026rsquo;s needs and situations. Ali, et al., (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) confirmed the importance of AI in education systems to be adopted and concerned by policymakers, the study highlighted role of AI in shaping future generation mentality, thinking, perceptions and skills. Jobin, Ienca, \u0026amp; Vayena, (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) critically explored AI role in education sector and found that well-structured guideline must be developed for both students and lecturers to understand how, why and when to use AI in education, ethical frame and justice are necessary to be part of the guidelines, adequate implementation for the guidelines to be in full vision as a strategy including diverse ways and solutions in education sector. Taherdoost, \u0026amp; Madanchian, (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); Tai, (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) emphasizing the transformative effects of AI on social, economic, and industrial aspects, shaping future human activities and capacities. Excessive reliance on AI by future students may impede the development of critical writing, research, and language skills. This dependence risks academic integrity and reduces critical thinking as AI-generated responses may lack depth or nuance. Accordingly the first hypothesis in this paper was developed as:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eH1: There is a significant positive impact of AI on FG\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eIn addition, Gohr, et al., (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e); Maghsoudi, Mohammadi, \u0026amp; Bakhtiari, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e negotiated that AI is the highest potential and most significant predictor of sustainable development in both developed and developing countries. In construction industry (Regona, et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) finalized the review by confirming the ability of AI in ensuring sustainable development to be conditional with full concern and implementation of ethical frame including privacy and resilience. To examine the effect of AI on SD in education sector this research developed:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eH2: There is a significant positive impact of AI on SD\u003c/em\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLiterature Summary\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable/Relation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLiterature\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eArtificial Intelligence \u0026rarr; Future Generation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eShribala, \u0026amp; Jhaneswaran, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Wang, et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Ali, et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2024\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eArtificial Intelligence \u0026rarr; Sustainable Development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eGohr, et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Maghsoudi, Mohammadi, \u0026amp; Bakhtiari, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Regona, et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSustainable Development \u0026rarr; Future Generation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNăstasă, Dumitra, \u0026amp; Grigorescu, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Abdeldjalil, Mohammed, \u0026amp; Asma, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSustainable Development Mediating the relationship between artificial intelligence and future generation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eGohr, et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Maghsoudi, Mohammadi, \u0026amp; Bakhtiari, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Emina, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEthics and Justice moderating AI and Sustainable Development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\u003cstrong\u003eSource: Developed by researcher 2026\u003c/strong\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eEmina, (\u003cspan citationid=\"CR15\"\u003e2021\u003c/span\u003e) affirmed the role of SD in developing FG, to manage this role responsibility, skills, knowledge and attitude must be considered as principles of sustainability amongst coming generation, where the research involved fairness, equity and stress minimization as moderators of SD. According to Qadeer, et al., (\u003cspan citationid=\"CR55\"\u003e2022\u003c/span\u003e) attainment of SD threated by several factors such as AI, lecturer\u0026rsquo;s readiness, rapid changes, technological revolution and population growth, this research proposed AI to be predictor of SD, in the same study Qadeer highlighted SD assurance for well-being of future generations. Thus, this paper proposing:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eH3: There is a significant positive impact of\u003c/em\u003e SD on FG\u003c/p\u003e\n\u003cp\u003eGohr, et al., (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e); Maghsoudi, Mohammadi, \u0026amp; Bakhtiari, (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) both studies negotiating the effect on artificial intelligence on industrial improvement reflected on potential future generations improvement in term of skills and other. This research proposing:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eH4: There is a positive mediating role of SD on the relationship between AI and FG\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eUNESCO website stated ethics as factor ensuring AI delivers sustainable development by framing regulations and limitation of using AI such as matters related to discrimination, transparency, bias and privacy where ethics crucially influencing the relationship (Wang, et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Ethics can amplify or inhibit influence of AI on sustainable development thus sustained future generation (Vinuesa, et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Based on literature hypothesis developed as:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eH5: There is a significant positive moderating role of ethics on the relationship between AI and SD\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eJustice prioritizing AI positivity to be reflected on sustainable development goals (Pendyala, 2024; Al-Adwan, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). At the same time that AI promoting SD in sectors justice is assuring global regulations and rules and policy makers concerning human rights and equitable education system (Javed, \u0026amp; Li, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In the same study concluded that for successful AI integration toward SD requires justice existence and consideration to robust global policy coordination, financial support and equitable benefit regulations to be released which is preventing any hard could be caused by AI usage. Following hypothesis was:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eH6: There is a significant positive moderating role of justice on the relationship between AI and SD\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe combination oof ethics and justice as moderators in one model based on (Aini, et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Vinuesa, et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This research paper examines the proposed model in education sector using the variables as visually presented in Fig. \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eMeanwhile to support the development of research model theoretical framework was developed as well in Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. T-EESST theory support accepting technology with sufficient awareness whenever developing balanced strategy between technological, environmental, economic and social aspects for sustainability in sectors and communities, this theory ensures comprehensive development and sustainable development with minimized negativity and harms. This is crucial for policy makers to concern this theory and serve the purpose of theory existence (Al-Emran, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Technology Acceptance Model (TAM) explaining how students and lecturers should adopt AI, policy makers should also understand the mechanism of healthy adoption for targeted future generation. This model contains perceived usefulness which is to what extent users believe that AI is greaten their performance and perceived ease of use which is to what extent users believe that AI won\u0026rsquo;t be complicated while using and could even learning process for students and teaching process for lecturers (Na, et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mogaji, et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIn similar context stakeholder theory has been employed to maintain all beneficiaries interest considering ethics and justice (Matthews, et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; da Costa, Gon\u0026ccedil;alves, \u0026amp; Montez, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Theory of sustainable development developed involved to support the current study model by ensuring sustainable development for the capital of the process, where it is students and future generation in this particular research. This theory allocated here to serve the goodness of future generation based on sustainable development goals set by policy makers toward the prosperity of future generations and the world (Emina, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Based on research hypothesis development referring to literature and supportive theories this research proposed the following conceptual mode to be examined Fig. \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e"},{"header":"3. Methods","content":"\u003cp\u003eThe paper employed quantitative method to collect the required data for data analysis. The research designed as cross sectional survey as it is more appropriate for unknown population size and geographical limitation existence to be considered as population-based survey (Setia, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Furthermore non-probability sampling method, where the data collected from both lecturers and students based on characteristics of being working lecturer and enrolling students both levels undergraduate and graduate levels the particular suitable sampling method is quota sampling method where the sub-groups are students and lecturers (Arrogante, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Questionnaires was utilized as measurement tool to collected the targeted data by preparing google form and distribute it amongst lecturers and students from multiple region. Total participants of 582 divided into 217 lecturers and 365 students has been screened and excluded 3 participants due to technical issue to remain total 579 as 217 lecturers and 362 students. The data will be analysed using two software, one is SPSS for descriptive analysis, outliers and multicollinearity and another is AMOS for hypothesis testing.\u003c/p\u003e"},{"header":"4. Findings","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDescriptive Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis section contain several sub-sections clarifying data analysis process starting with descriptive analysis and reliability test. The below table contains the questionnaire’s items for all study’s variables and reliability test, mean, standard deviation, critical ratio, average variance extracted and source for all items. The questionnaire’s items adapted from previous studies as stated in the table below, only reliability represented by Cronbach’s Alpha for this validated questionnaire’s statements. Items obtained the scores confirming the reliability as more than 0.7 for each items (Hussey, et al., 2025). Means of FG items obtained scores in range of 3.65 to 4.82, for AI items mean obtained in range of 3.68 to 4.80, for SD items mean obtained in range of 3.94 to 4.86, ethics items obtained means range of 4.03 to 4.95, justice items obtained means in range of 3.70 to 4.91.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Descriptive analysis, reliability test and sources\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eItems\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCronbach’s Alpha\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eDeviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAVE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eFuture Generation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eFG1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFuture generation’s knowledge can be \u0026nbsp; \u0026nbsp; improved by using AI in education.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e.926\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHolmes, Bialik, \u0026amp; Fadel, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eFG2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTo obtain sustained learning outcomes in future generation, ethics \u0026nbsp; \u0026nbsp; should be carefully regulated in education sector.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.083\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eFG3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThere are significant ethical risks on students, involved in using AI technologies in school settings.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eJobin, Ienca, \u0026amp; Vayena, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eFG4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNone of communities would be left behind if AI employed fairly and inclusively in education.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eFG5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDeployment AI in education with tailored ethical frame ensuring sustainable development for future generation skills and value.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.530\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eFG6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFuture generation will benefit from AI deployment in education by easing access to knowledge and information.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eVinuesa et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eFG7\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSeveral educational and social challenges for future generation will be solved by AI.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.689\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eFG8\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFuture generation will benefit most if sustainable development is integrated in curriculum.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.930\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eArtificial Intelligence\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAI1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI potentially accelerate student’s sustainable development.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eKulkov et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAI2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI in education improving the progress, monitor and forecasting future generation development.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.927\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;AI3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI usage should follow ethical guidance to prevent discrimination and bias amongst students.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eJobin et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAI4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSocial equity obtained by AI deployment avoiding unequal sustainable development in education.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.852\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAI5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI is a potential tool to improve education in sustainable way for future generations.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eVinuesa et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAI6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIn education using AI protects well-being of future generation.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.907\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSustainable Development\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSD1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eConcerning student’s sustainable development requires AI systems training for lecturers.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.932\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e.873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e.884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKulkov et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSD2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIn education sector there should be policies and regulations to ensure positive outcomes without harming societies.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJobin et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSD3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI usage in schools and universities lead to personalized learning then sustainable awareness and creativity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMichael, et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSD4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIn education sector students should learn to innovate solutions toward promoting sustainability.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eNa-Nan, et al., 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSD5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTeaching students about sustainable practice is important for long-term development.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.528\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eE1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI usage in education must prioritize student’s privacy and data protection for sustainable development goals.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e.911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e.890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eJobin, Ienca, \u0026amp; Vayena, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eE2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTransparency is crucial and concerned in AI systems used in sustainable development.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.420\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eE3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThere is accountability on AI users to ensure communities sustainability.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHolmes, Bialik, \u0026amp; Fadel, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eE4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEthical frames concerning bias and discrimination in AI-driven sustainability.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.488\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eE5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFollowing ethical standard in AI promotes trust and enhance sustainable development in education sector.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMittelstadt, et al., 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eJustice\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eJ1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI in education promotes availability and equal access to resources and opportunity to ensure sustainable development.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.758\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e.927\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e.914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eVinuesa et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eJ2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI tools in education reducing poverty and inequality for sustained societies.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.460\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eJ3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI should be used against bias and inequalities for sustainability initiatives in education sector.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.932\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eJ4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI providing chances for neglected communities.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.869\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eJ5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEthical implementation of AI in education sector ensuring social justice and positively affecting sustainable development.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.499\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote: Prepared by author.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: AVE, average variance extracted; CR, composite reliability. KMO 0.938\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe standard deviation of FG items scored in range of 1.037 to 1.930, AI items scored standard deviation in range of 1.847 to 1.990, SD items scored standard deviation in range of 1.528 to 1958, ethics items standard deviation scored range of 1.420 to 1.849, justice scored standard deviation in range of 1.460 to 1.932. The critical ratios scored more than 2 which is accepted according to (Collier, 2020) as FG scored .867, AI scored .809, SD scored .873, Ethics scored .911, justice scored .927. Average variance extracted AVE \u0026nbsp;recommended score more than 0.5 according to (Fornell, \u0026amp; Larcker, 1981) FG variable scored .926, AI scored .941, SD scored .884, ethics scored .890, justice scored .914. These results indicating the acceptance descriptive analysis for the items of questionnaires.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe measurement analysis included multicollinearity, VIF and tolerance were accepted according to (Sarstedt et al. 2023) in range of 1.299 to 1.427 as usual statistical accepted score, tolerance in range of 0.542 to 0.701as good and accepted scores, CFI above 0.9 to score 0.95, Chi-Square less than 3 as 2.901, SRMR less than 0.05 as very good value of 0.022 (Hu, \u0026amp; Bentler, 1999). RMSEA scored less than 0.08 as 0.009 according to (Henseler, et al., 2016).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Measurement evaluation\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTolerance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eChi-Square\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSRMR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSEA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFuture Generation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.701\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e2.901\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eArtificial Intelligence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSustainable Development\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.599\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEthics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.635\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eJustice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eNote: Prepared by author\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe correlation of all variables on each other was very good which FG-AI correlated at 0.492, FG-SD correlated at 0.550, FG-ethics correlated at 0.438, FG-justice correlated at 0.683, AI-SD correlated at 0.811, AI-ethics correlated at 0.704, AI-justice correlated at 0.658, SD-ethics correlated at 0.483, SD-justice correlated at 0.546, ethics-justice correlated at 0.752, \u0026nbsp;as all of these values accepted according to (Kang, et al., 2021).\u003c/p\u003e\n\u003cp\u003eTo provide comprehensive and detailed presentation of hypothesis testing of this research structural model as in (table 3) was necessary to showcasing each of direct and indirect relationships, P value, RMSEA and CFI conducted in structural equation modelling SEM by AMOS. Direct relationships for lecturer’s sample model indicated RMSEA=0.059 and CFI-0.931 where both scores accepted and indicating the goodness of the model. On the other hand, student’s model RMSEA=0.004 and CFI=0.909 as well indicating goodness of the model. This section will elaborate all results of direct relationships for both models (lecturer’s sample model and student’s sample model). First hypothesis \u003cem\u003eH1\u003c/em\u003e examining the positive impact of AI on FG which results reported as path coefficient= 0.564 with significant P value=***, concluded the acceptance of the hypothesis. For student’s model scored path coefficient= 0.477, P value= 0.002 which is less than 0.05 to indicate the significancy of the relationship and accepting the hypothesis in student’s model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Direct paths hypothesis testing results\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePath\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePath Coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSEA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eResult\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eDirect Relationships (Lecturer’s Model)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI\u0026nbsp;à\u0026nbsp;FG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI\u0026nbsp;à\u0026nbsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSD\u0026nbsp;à\u0026nbsp;FG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eDirect Relationships (Student’s Model)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI\u0026nbsp;à\u0026nbsp;FG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.477\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI\u0026nbsp;à\u0026nbsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSD\u0026nbsp;à\u0026nbsp;FG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eNote: Prepared by author\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSecond hypothesis \u003cem\u003eH2\u003c/em\u003e examining the positive impact of AI on SD, lecturer’s model indicated path coefficient=0.197, P value=***, which indicated accepted hypothesis. Meanwhile, student’s model resulted in path coefficient=0.519, P value=***, indicated accepted hypothesis as well. Third hypothesis H3 examining the positive impact of SD on FG, lecturer’s model found path coefficient=0.246, P value=***, to affirm the acceptance of the hypothesis. On another hand, student’s model found path coefficient=0.638, P value 0.012 which is less than 0.05 to assure the acceptance of the hypothesis. The following tests results as listed in (table 4) for the indirect relationships rolling of the mediator SD in the relationship between AI and FG, the moderators E \u0026amp; J rolling the relationships between AI and SD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Indirect paths hypothesis testing results\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePath\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndirect Effects\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMediation \u0026amp; Moderation (Lecturer’s Model)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI\u0026nbsp;à\u0026nbsp;\u003cem\u003eMe\u003c/em\u003eSD\u0026nbsp;à\u0026nbsp;FG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI\u0026nbsp;à\u0026nbsp;\u003cem\u003eMoE\u003c/em\u003e à\u0026nbsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI\u0026nbsp;à\u0026nbsp;\u003cem\u003eMoJ\u003c/em\u003e à\u0026nbsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMediation \u0026amp; Moderation (Student’s Model)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI\u0026nbsp;à\u0026nbsp;\u003cem\u003eMe\u003c/em\u003eSD\u0026nbsp;à\u0026nbsp;FG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAccepted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI\u0026nbsp;à\u0026nbsp;\u003cem\u003eMoE\u003c/em\u003e à\u0026nbsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAI\u0026nbsp;à\u0026nbsp;\u003cem\u003eMoJ\u003c/em\u003e à\u0026nbsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRejected\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eNote: Prepared by author\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMeSD= mediator sustainable development, MoE= Moderator ethics, MoJ= Moderator justice\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe results in (table 4) obtained from the structural model presented in (figure 3). Hypothesis \u003cem\u003e4\u0026nbsp;\u003c/em\u003epredicting a positive mediation of SD on the relationship between AI and FG. Results of indirect effect found in lecturer’s model to be 0.248, P value=***, indicating the acceptance of the hypothesis. Whereas, in student’s model for the same hypothesis indicated indirect effect=0.404, P value=***, resulted that there is a positive and significant mediation role of SD on the relationship between AI and FG in both (Lecturer’s and Student’s) models. Hypothesis \u003cem\u003e5\u003c/em\u003e predicting a positive moderation of E on the relationship between AI and SD. Lecturer’s model examined Hypothesis \u003cem\u003e5\u003c/em\u003e resulted as indirect effect=0.098, P value***, indicating the acceptance of the hypothesis. Thus, in student’s model hypothesis 5 examined and resulted as indirect effect=-0.006, P value=0.153, indicating rejecting hypothesis 5 due to negative indirect effect and insignificant P value being higher than 0.05. Hypothesis \u003cem\u003e6\u003c/em\u003e estimating positive moderation role of J on the relationship between AI and SD. Lecturer’s model resulted indirect effect of 0.115, P value=***, indicating the acceptance of the hypothesis. Meanwhile, student’s model resulted indirect effect=-0.293, P value=0.071, indicating reject hypothesis 6 due to the negative effect and P value being higher than 0.05. The results will be discussed in details in the following section. \u0026nbsp; \u0026nbsp;\u003c/p\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eIn term of direct relationships, lecturer’s and student’s models affirmed the positive and significant impact of AI on FG amongst lecturers, the results comes algin with \u0026nbsp; (Thomas, 2022) reported that AI definitely significantly influencing the future generation’s knowledge, skills and personalized learning. Zhang, Zhu, \u0026amp; Su, (2023) sorted critical need for developing a theory to guide and structuralize human behaviours and knowledge through using AI to be safe, reliable, extensible and sophisticated technology toward well prepared FG. Accordingly, the importance of AI for FG is definite, obtaining plenty of advantages and being competitive is mainly sourced by technology utilization toward providing fair chances to everyone to learn and save time, cost and effort in learning process.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn sequence, second direct relationship of AI and SD in education sector resulted as significant and positive at the same time confirming results found in previous studies as AI is crucial in education and needed for SD within the acknowledgment of policymakers of pros and cons of AI adaption in this particular industry (Goralski, \u0026amp; Tan, 2020). Additionally, Gohr, et al., (2025) concluded that AI is playing a role to sustain SD in the firms with ensuring balanced contextualization and generalizability in providing knowledge fits towards responsible changes. On the other hand, Vinuesa, et al., (2020) assured that SD carries both possibilities (positive and negative effect) on society, environment and economy needed for government role to maintain it. In other studies conducted by (Kulkov, et al., 2024; Mienye, Sun, \u0026amp; Ileberi, 2024) suggested a conceptual model for AI optimization of SD which includes certain variables such as strategic alignment, infrastructure development, change management, and continuous improvement. The third direct relationship between SD and FG was accepted as positive and significant relationship in both models (lecturers and students). Previous research Emina, (2021) affirmed that sustainable development is reflecting the situation of future generation. Achievement of better future generation led by sustainable development is not easily obtained which countries and governments shall work for it as early as possible (Holden, Linnerud, \u0026amp; Banister, 2014).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe indirect relationships starting with SD mediating role in the relationship between AI and FG. Results confirmed the significant positive mediating role of SD in the relationship between AI and FG in both lecturers and students models, where its affirming results stated in (Năstasă, Dumitra, \u0026amp; Grigorescu, 2024). Justice and ethics moderating AI toward critical governance (Taeihagh, 2021), ethics examined in this research and found significantly and positively moderating the relationship between AI and SD in lecturer’s mode. Literature reported significant moderation of ethics on SD (Hai Yen, et al., 2023), in education sector ethics has a significant moderating role with AI (Ahmed, 2024). In student’s model the hypothesis was rejected as ethics got insignificant and negative moderating role on the relationship between AI and SD, which indicates the neglection of students for ethical perception where they only concentrate on how easy the info is afforded. This finding is reflecting the different understanding of both lecturers and students to the concept of education and learning process from being learning skills and adding knowledge and information through discussion, analysis and brain storming from lecturers perception to shortest time to do assignments and easiest way to answers questions in this technology revolution from student’s perception. Here where is the ethical consideration allocated in both perceptions. Finally, justice examined as moderator on the relationship between AI and SD in two different samples. Lecturers sample found justice as significant and positive moderator on the relationship to be aligned with several previous studies employing justice as moderator but in this study its examined for the first time moderating AI and SD in education sector. Student’s model at the same time examined justice as a moderator on the same relationship and found to be rejected. These results embodied in major concern as students shown neglection of ethics and justice in AI usage in education sector.\u003c/p\u003e"},{"header":"6.\tImplications ","content":"\u003cp\u003eThe significant findings of this research enhancing the awareness of people in charge toward further direction and monitoring of AI usage behavior amongst students. Accordingly, policies, rules and regulation should be developed to protect AI daily use of students within ethical frame and guarantee the intergenerational justice. Devoting values amongst students and lecturers could help lecturers to guide and advice students how, when and where is the right time and matter for using AI in their education journey. As well as, students will be able to investigate, ask and gathering information using AI tools with no full relying on it as main and only source but double checking the information before using it by students. This is reflected on future generation knowledge and sustaining the contentious development amongst the intergeneration.\u003c/p\u003e"},{"header":"7.\tConclusion ","content":"\u003cp\u003eIn conclusion, objectives of this paper embodied in examining direct effect of AI on each of SD and FG, indirect effect of AI on FG mediated by SD and indirect effect on AI on SD moderated by ethics and justice employed in two models (lecturer\u0026apos;s and student\u0026rsquo;s). found to be going in different directions as lecturers reckon than AI is a self and personalized learning tools improving the quality and accuracy of education sector. AI widen student\u0026rsquo;s sights and expanding knowledge to facilitate and equalize learning opportunities and vacancies hunting. Meanwhile, students\u0026apos; perception to AI is a guaranteed provider for all required knowledge during their study journey. Neglecting ethical consequences and free restrictions allowing them to practice that. Students are not aware about justice importance in learning opportunities and vacancies eligibility. In addition, AI is playing a vital role in maintaining the sustainable development in education sector which surely will be reflected on skills, knowledge and behavior of the future generation ifthe ethical frame is taking a place in learning process. This research recommends authority of education sector to enhancethe awareness amongst students in term of healthy usage, lecturers shall involve tasks critical thinking based on enforce students using their pure skills, qualifying the lecturers to enable them directing the students, using contemporary methods to guide students properly, restricting AI usage in the continuous assessments and exams. Policymakers in education sector should set policies for AI usages to ensure the betterment of FG.\u003c/p\u003e"},{"header":"8.\tLimitation and Future Research","content":"\u003cp\u003eThis research has been challenging during data collection from lecturers where mostly lecturers don\u0026rsquo;t have time and shown no interest to fill up the questionnaires. Furthermore, students filling up the questionnaires without responsible sense in their answers. Thus, future researcher recommended to conduct qualitative research for collected data from lecturers where the interview could be more meaningful with reasonable findings.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no fundings for this research\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics, Consent to Participate, and Consent to Publish declarations: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study approached students up to 18 years old and lecturers where as\u0026nbsp;informed consent was obtained from all participants involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe protocol was approved by The Human Research Ethics Committee (JKEP) and was conducted in accordance with the\u0026nbsp;USIM/JKEP/2025-107.\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of \u003cstrong\u003eUniversiti Sains Islam Malaysia.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data been collected in this study is available and could be shared soft copy in excel file whenever is required. But there is no link for the data to be provided and possibility to do so because the data still needed for further research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdeldjalil C, Mohammed K, Asma O. Digitalization and sustainable development: A literature review focused on artificial intelligence (2019\u0026ndash;2024). J Law Sustainable Dev. 2024;12(11):e4155\u0026ndash;4155.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed H. (2024). Institutional integration of artificial intelligence in higher education: The moderation effect of ethical consideration. Int J Educational Reform, 10567879241247551.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAini Q, Purwanti P, Muti RN, Fletcher E. Developing sustainable technology through ethical ai governance models in business environments. 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Sci China Inform Sci. 2023;66(2):121101.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e\n\u003ch3\u003e\u003c/h3\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Artificial intelligence, Sustainable development, Moral imagination, Ethics, Justice, Future generations, Intergenerational responsibility, Sustainable education","lastPublishedDoi":"10.21203/rs.3.rs-9034636/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9034636/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examines the role of artificial intelligence (AI) on future generation (FG) mediated by sustainable development (SD). The nexus of artificial intelligence and sustainable development moderated by justice and ethics. Current AI revolution threaten the FG in education by higher plagiarism, losing critical skills, inequitable access, bias and discrimination, data privacy, misinformation and reliability issues. Ethics and Justice examined as moderators in relationship between AI and SD. Quantitative method employed and survey distributed amongst two explored perceptions students and lecturers. A sample size of 582 response been collected and analysed via AMOS. Students data resulted as there is a significant direct impact of AI on FG, a significant mediation statistical role of SD on the relationship between AI and FG, influence of AI on SD found to have insignificant statistical moderating role of Ethics \u0026amp; Justice. Lecturers data differently only Ethics were significantly statistically moderating AI and SD. Thus, education sector recommended to enrich the awareness of students in ethical frame importance in AI usage toward SD in the FG.\u003c/p\u003e","manuscriptTitle":"Artificial Intelligence, Moral Imagination, and Intergenerational Justice in Sustainable Education","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-23 19:35:27","doi":"10.21203/rs.3.rs-9034636/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-21T09:55:27+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-12T16:41:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50578205935061168518398635420077421372","date":"2026-04-12T07:49:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-12T06:05:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"288621693513209693617163394635393619263","date":"2026-04-08T16:02:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-07T07:49:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-29T06:01:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"51800527514242549990046297537491062148","date":"2026-03-18T15:32:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76823144375798605329218375996696242836","date":"2026-03-18T15:31:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-18T15:27:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-17T10:56:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-12T18:06:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sustainability","date":"2026-03-12T09:42:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3de45145-2a0b-4e33-bc8e-daba58c6abee","owner":[],"postedDate":"March 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T05:08:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-23 19:35:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9034636","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9034636","identity":"rs-9034636","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}