4 Use of AI

Use of AI

The integration of Artificial Intelligence (AI) in education presents a complex interplay of opportunities and challenges, particularly concerning ethics, the digital divide, and the imperative for responsible teaching practices. AI technologies have the potential to enhance student learning outcomes by providing personalized learning experiences and improving engagement through adaptive learning systems (“The Role of AI in Improving Student Learning Outcomes: Evidence in Vietnam”, 2024; Nguyen, 2024; “Artificial Intelligence in education: transformative potentials and ethical considerations”, 2023). However, the deployment of these technologies raises significant ethical concerns, including issues of data privacy, algorithmic bias, and the implications of AI-mediated interactions on the educational experience (Nguyen, 2024; Eden, 2024; Ma & Jiang, 2023). Moreover, the digital divide remains a critical barrier, as unequal access to technology can exacerbate existing educational inequities, particularly in low-income and rural areas (Chisom, 2024; Edeni, 2024; Samuel-Okon, 2024).

Addressing these challenges requires a multifaceted approach that emphasizes ethical standards and equitable access to AI resources. Educational institutions must develop clear guidelines for the ethical use of AI, ensuring that all students benefit from these advancements while minimizing risks associated with misuse (Song, 2024; Holmes et al., 2021; Walczak & Cellary, 2023). Furthermore, fostering digital literacy among educators and students is essential to bridge the digital divide and promote inclusive educational practices (Bentley, 2024; Samuel-Okon, 2024). As AI continues to evolve, it is imperative that stakeholders engage in ongoing dialogue about its ethical implications and strive to create a framework that supports responsible AI integration in education (Jobin & Ienca, 2019; (“Artificial Intelligence in education: transformative potentials and ethical considerations”, 2023; Abuodha, 2024).

In summary, while AI holds transformative potential for enhancing educational practices, it is crucial to navigate the ethical landscape and address the digital divide to ensure that all learners can thrive in an increasingly digital world.

Ethics

The ethics of using artificial intelligence (AI) is a multifaceted issue that encompasses a variety of ethical principles, guidelines, and frameworks aimed at ensuring responsible development and deployment of AI technologies. As AI continues to permeate various sectors, including healthcare, agriculture, and education, the need for robust ethical guidelines becomes increasingly critical.One of the primary ethical considerations in AI is the establishment of clear regulations and frameworks that govern its use. Hasan emphasizes the necessity for governments and professional bodies to create unified approaches to guide ethical AI implementation, particularly in healthcare and pharmacy practices (Hasan, 2024). This sentiment is echoed by Huang et al., who note that the field of AI ethics is interdisciplinary and requires comprehensive guidelines that address ethical theories, policies, and principles related to AI (Huang et al., 2023). The proliferation of AI ethics guidelines, as noted by Munn, indicates a growing recognition of the need for ethical oversight, with over 50 frameworks emerging globally from various governments and organizations (Munn, 2022).

Moreover, the ethical principles that underpin AI usage often include autonomy, transparency, fairness, accountability, and non-maleficence. Ossa highlights that these principles are crucial for ensuring that AI systems operate ethically within healthcare contexts, yet they often remain abstract and poorly defined in practice (Ossa, 2024). Similarly, Franzke’s analysis reveals that many existing guidelines focus primarily on the technology itself rather than embedding ethics at their core, which can lead to a disconnect between ethical intentions and actual practices (franzke, 2022). This gap is further complicated by the fact that many AI ethics guidelines tend to emphasize transparency and accountability, yet often fail to provide actionable frameworks for implementation (Gevaert et al., 2021).

The ethical implications of AI are not limited to its technical aspects but also extend to its societal impacts. Ryan’s thematic analysis of AI in agriculture identifies key ethical principles that are frequently discussed, such as fairness and accountability, which are essential for mitigating bias and ensuring equitable outcomes (Ryan, 2022). In the context of business, Breidbach and Maglio warn that the unregulated use of AI can lead to unethical behaviors, including surveillance capitalism, highlighting the need for ethical considerations in data-driven business models (Breidbach & Maglio, 2020).

Furthermore, the importance of engaging diverse perspectives in the development of ethical guidelines cannot be overstated. Huriye stresses the necessity of incorporating a variety of viewpoints to ensure that AI is designed and deployed responsibly (Huriye, 2023). This aligns with the findings of Silva, who emphasizes the need for software development companies to actively address the ethical implications of AI technologies in their practices (Silva, 2023).

In conclusion, the ethics of using AI is a complex and evolving field that necessitates a concerted effort from multiple stakeholders, including policymakers, technologists, and ethicists. The establishment of clear, actionable ethical guidelines is essential for navigating the challenges posed by AI technologies and ensuring their responsible use across various domains.

Digital Divide

The digital divide refers to the disparities in access to, use of, and benefits derived from digital technologies, particularly the internet and artificial intelligence (AI). This divide is increasingly relevant as AI technologies proliferate, influencing various aspects of society, including education, healthcare, and employment. The digital divide can be categorized into three primary dimensions: access, capability, and outcome, which are essential for understanding how AI impacts different populations (Wu, 2022).

Access to digital technologies remains a significant barrier for many individuals, particularly those from low socioeconomic backgrounds. Research indicates that merely providing access to devices is insufficient; it must be accompanied by training and support to navigate the complexities of digital environments (Goedhart et al., 2022). Moreover, the emergence of AI technologies has introduced new forms of inequality, as individuals with limited digital literacy may struggle to utilize AI effectively, thereby exacerbating existing disparities (Huang, 2024). For instance, studies show that individuals with higher AI literacy tend to trust and effectively engage with AI applications, while those lacking such literacy face challenges in leveraging these technologies (Zhang et al., 2020).

The capability aspect of the digital divide emphasizes the skills necessary to engage with digital technologies. Factors such as age, gender, and socioeconomic status significantly influence individuals’ ability to utilize AI tools (Goedhart et al., 2022; , Chu et al., 2022). Older adults, for example, often exhibit lower digital skills compared to younger generations, resulting in a widening gap in technology use (Chernova et al., 2019). This generational divide is compounded by the fact that AI systems frequently reflect societal biases, potentially leading to ageism and other forms of discrimination in their applications (Stypińska & Franke, 2023).

Outcome disparities are also critical in understanding the digital divide in the context of AI. The benefits of AI technologies are often concentrated in high-income countries, leaving marginalized communities at a disadvantage (Gulumbe et al., 2023). This concentration not only undermines collective security but also exacerbates health inequities, as access to AI-driven healthcare solutions is often limited to those with better resources (Elendu, 2023). Furthermore, the integration of AI in education has shown potential to either bridge or widen existing gaps, depending on how resources are allocated and utilized (Li, 2023; , Familoni, 2024).

In conclusion, the digital divide is a multifaceted issue that is increasingly intertwined with the development and deployment of AI technologies. Addressing this divide requires a comprehensive approach that considers access, capability, and outcome disparities, ensuring that all individuals can benefit from the advancements in AI. Policymakers and researchers must prioritize strategies that enhance digital literacy and equitable access to AI technologies to mitigate the risks of deepening inequalities in society (Lutz, 2019; , Carter et al., 2020).

Teaching Responsibly

The integration of artificial intelligence (AI) into educational frameworks necessitates a responsible approach to teaching AI literacy. This involves not only understanding the technological aspects of AI but also addressing the ethical, social, and pedagogical implications of its use in educational settings. The literature emphasizes the importance of developing AI literacy among educators and students alike, ensuring that they are equipped to navigate the complexities of AI technologies responsibly.One of the primary concerns in teaching AI is the potential for educators to either over-rely on AI tools or fear being replaced by them. Liu highlights that while AI can enhance content design and optimize teaching processes, it is crucial for educators to embrace AI as a collaborative partner rather than a replacement, fostering a more enriching learning environment for students (Liu, 2023). This sentiment is echoed by Boscardin, who argues for increased AI literacy among educators to promote ethical awareness and social responsibility in the use of AI technologies (Boscardin, 2023). Such literacy is essential for educators to effectively guide students in understanding the implications of AI in their lives and future careers.Furthermore, the literature underscores the necessity of incorporating ethical considerations into AI education. Otero et al. advocate for an exploratory education model that integrates science and computer science while addressing ethical dimensions, which is fundamental for K-12 students to grasp the basic principles of AI (Otero et al., 2023). This is supported by Choi’s findings, which demonstrate that structured ethics education can significantly alter middle school students’ perceptions and attitudes towards AI, emphasizing the importance of practical exercises in understanding data bias and ethical AI principles (Choi, 2024). By embedding ethical discussions within AI curricula, educators can cultivate critical thinking skills and foster a responsible approach to technology use among students.The development of AI literacy must also be tailored to the diverse needs of different educational contexts. Zhao et al. emphasize the importance of enhancing AI literacy among primary school teachers, as their understanding directly influences the quality of AI education delivered to students (Zhao et al., 2022). Similarly, Yetişensoy and Rapoport highlight the inadequacies in current efforts to promote AI literacy, suggesting that a more comprehensive approach is necessary to equip citizens with the knowledge required to engage with AI technologies responsibly (Yetişensoy & Rapoport, 2023). This aligns with the stakeholder-first approach proposed by Figaredo, which advocates for designing educational experiences that prioritize the needs of various audiences, thereby enhancing the relevance and effectiveness of AI literacy initiatives (Figaredo, 2023).

Moreover, the integration of AI into educational curricula should not only focus on technical skills but also on fostering a critical understanding of AI’s societal implications. Ng et al. stress the importance of educating learners about the applications and ethical issues surrounding AI, which can significantly impact their lives (Ng et al., 2021). This holistic approach is further supported by Voulgari et al., who argue for the redesign of curricula to enable students to critically engage with AI applications and become informed citizens (Voulgari et al., 2021). Such educational strategies are vital for preparing students to navigate an increasingly AI-driven world, ensuring they can leverage technology responsibly and ethically.In conclusion, teaching responsible AI literacy involves a multifaceted approach that encompasses ethical considerations, tailored educational strategies, and a collaborative mindset among educators and students. By fostering a comprehensive understanding of AI’s implications and applications, educational institutions can prepare learners to engage with AI technologies in a manner that is both informed and responsible.