Journal Article•10.1111/bjet.13556 1. A Competency Framework for AI Literacy: Variations by Different Learner Groups and an Implied Learning Pathway Hyunkyung Chee, Solmoe Ahn, Jihyun Lee 27 Dec 2024-British Journal of Educational Technology
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Key components of AI literacy include basic AI knowledge, understanding data and algorithms, ethical considerations, and the ability to utilize AI tools. Educational initiatives should focus on fostering critical and responsible integration of AI, ensuring workforce readiness and public awareness.
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- Guides design of tailored AI curricula for learners.
- Supports systematic lifelong AI literacy development policies.
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This study develops a comprehensive AI literacy competency framework, varying by learner group (K-12, higher education, workforce), and proposes a learning pathway, emphasizing critical, strategic, and responsible AI integration, to guide AI curriculum design and lifelong learning.
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Journal Article•10.4018/979-8-3693-8252-3.ch002 Andi Asrifan, Uswah Mujahidah Rasuna Said, Juvrianto Chrissunday Jakob +1 more 16 Dec 2024-Advances in educational technologies and instructional design book series
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Key components of AI literacy include understanding AI principles, fostering critical thinking, ensuring ethical technology use, promoting equitable access, and preparing the workforce for evolving demands. Educational initiatives and public awareness are essential for navigating an AI-driven world confidently.
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- Empowers individuals to engage with AI technologies effectively.
- Promotes equitable access and participation in AI initiatives.
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This chapter emphasizes the crucial role of AI literacy in navigating an AI-driven world with confidence, ethical awareness, and informed decision-making, empowering users to engage judiciously with AI technologies and promoting equitable access to AI-driven opportunities.
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Journal Article•10.1016/j.caeai.2024.100214 3. Developing an artificial intelligence literacy framework: Evaluation of a literacy course for senior secondary students using a project-based learning approach Siu-Cheung Kong, Man-Yin William Cheung, Olson Tsang 1 Mar 2024
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The study emphasizes problem-solving competence, ethical understanding of AI principles, and metacognitive strategies as key components of AI literacy. Educational initiatives like project-based learning enhance workforce readiness and public awareness, preparing students for responsible participation in an AI-driven society.
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- Develops AI Literacy Framework for future citizen participation.
- Enhances problem-solving competence through project-based learning.
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This study evaluates a 14-h AI literacy course for senior secondary students using project-based learning, finding improved problem-solving competence, metacognitive strategies, and understanding of AI ethics, with implications for developing an AI Literacy Framework.
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Journal Article•10.17504/protocols.io.bp2l6dbpzvqe/v1 4. AI Literacy Framework (ALiF): A Progressive Competency Development Protocol for Higher Education v1 23 Nov 2024
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The AI Literacy Framework (ALiF) emphasizes four core competency areas: Technical Understanding, Critical Evaluation, Practical Application, and Ethical Considerations, essential for developing AI literacy among students, faculty, and staff in higher education, fostering innovation and academic integrity.
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- Systematic development of AI literacy in higher education.
- Promotes academic integrity and innovation.
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The AI Literacy Framework (ALiF) provides a structured protocol for developing AI literacy in higher education, comprising a three-level progression system across four core competency areas, promoting innovation while maintaining academic integrity.
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Journal Article•10.1109/isec61299.2024.10665282 5. AI in Education: Crafting Policies for Tomorrow's Learning Landscape Mehdi Roopaei, Nasrin Dehbozorgi 9 Mar 2024
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The paper emphasizes integrating AI into curricula, focusing on critical thinking, problem-solving, ethical use, data privacy, and educator training. These components are essential for preparing students for AI-rich job markets and fostering public awareness of AI's implications.
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- Reform educational systems for AI-driven job markets.
- Develop policies for ethical AI use in education.
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This study explores AI's impact on education, highlighting the need for policies on AI integration, ethical use, and educator training to prepare students for AI-driven job markets and enhance learning outcomes in an AI-rich future.
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Journal Article•10.5334/uproc.142 6. Integrating Artificial Intelligence in Vocational and Adult Education: A Supplement to the DigCompEdu Framework George Bekiaridis, Graham Attwell 28 Aug 2024-Ubiquity proceedings
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The paper identifies key AI competencies for educators, including data literacy, computational thinking, and ethical considerations of AI use, essential for integrating AI in education. These competencies support workforce readiness and enhance public awareness of AI's role in learning environments.
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- Develop AI competencies for educators in adult education.
- Enhance digital competencies for future educational practices.
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The AI Pioneers project integrates AI into adult education and VET, identifying key AI competencies for educators, supplementing the DigCompEdu framework with skills in data literacy, computational thinking, and AI ethics, enhancing educators' digital competencies and preparing students for an AI-driven future.
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Book Chapter•10.4018/979-8-3693-0831-8.ch014 7. Integrating Professional Perspectives for AI Literacy Kristopher Merceron, Karene Best 12 Feb 2024-Advances in educational technologies and instructional design book series
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Key components of AI literacy include interdisciplinary curriculum integration, ethical considerations, practical applications, and continuous professional development. Educational initiatives must focus on equipping students with knowledge and skills for workforce readiness and fostering public awareness in an AI-driven world.
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- Collaboration enhances AI literacy in education.
- Continuous professional development is essential for educators.
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Integrating professional perspectives for AI literacy in education involves equipping students with knowledge and skills to excel in an AI-driven world through collaborative efforts between librarians and communication professors.
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Journal Article•10.61506/02.00291 8. Ethical Governance of Artificial Intelligence: Guiding Youth towards Responsible Digital Citizenship Asma Yunus, Shahzad Khaver Mushtaq, Ruqia Safdar Bajwa +1 more 1 Jun 2024-Journal of policy research
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The paper emphasizes digital literacy, critical thinking, and ethics awareness as key components of AI literacy. It advocates for educational initiatives, collaboration among stakeholders, and robust policies to prepare youth for responsible AI interaction and promote ethical digital citizenship.
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- Promote ethical AI use through digital literacy and critical thinking.
- Establish collaboration for ethical guidelines and AI literacy programs.
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This policy paper proposes a framework to guide youth in responsible AI use through digital literacy, critical thinking, and ethics awareness, emphasizing the need for collaboration to establish concrete guidelines and promote informed privacy choices in an AI-driven society.
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Journal Article•10.4018/979-8-3693-0884-4.ch007 9. Enforcing the Ethics of Artificial Intelligence in Education 20 Sep 2024-Advances in educational technologies and instructional design book series
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The chapter emphasizes AI literacy through educational initiatives that promote understanding of AI's ethical implications, workforce readiness for AI integration, and public awareness campaigns to foster inclusivity and transparency, ensuring all stakeholders are equipped to navigate the AI age effectively.
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- Promotes equity, transparency, and inclusivity in AI education.
- Provides strategies for ethical AI implementation in educational contexts.
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This chapter explores the UNESCO Recommendation on AI ethics, focusing on AI's intersection with education, and provides practical approaches for implementing ethical AI in education, promoting equity, transparency, and inclusivity through real-world examples and UNESCO's Policy Area 8 guidelines.
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Journal Article•10.51583/ijltemas.2024.130816 10. Strategic Framework for Human-Centric AI Governance: Navigating Ethical, Educational, and Societal Challenges Chris Gilbert, Mercy Abiola Gilbert 16 Sep 2024-International journal of latest technology in engineering management & applied science
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The paper emphasizes education and upskilling as key components of AI literacy, focusing on ethical considerations, workforce readiness, and inclusive access. It advocates for comprehensive educational initiatives to enhance public awareness and ensure responsible AI integration into society.
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- Illustrates AI's impact across various industries through case studies.
- Emphasizes addressing ethical and societal challenges in AI development.
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This research proposes a human-centric AI governance framework, built on five principles, to ensure AI enhances human capabilities, promotes transparency, and upholds ethical standards, addressing challenges and risks through case studies and a collective effort to navigate AI's rapid expansion responsibly.
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Journal Article•10.48550/arxiv.2412.12108 11. Responsible AI Governance: A Response to UN Interim Report on Governing AI for Humanity Sarah Kiden, Bernd Carsten Stahl, Beverley Townsend +22 more 29 Nov 2024
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The report emphasizes fostering AI literacy through educational initiatives, workforce readiness programs, ethical considerations in AI development, and enhancing public awareness. These components are essential for ensuring individuals and communities can effectively engage with and benefit from AI technologies.
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- Promotes equitable and inclusive AI ecosystems.
- Advocates for legally binding norms and transparency.
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This report responds to the UN's Interim Report on AI governance, emphasizing AI's transformative potential for SDGs while highlighting risks and advocating for robust governance, equitable AI ecosystems, and harmonized international frameworks.
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Journal Article•10.70715/jitcai.2024.v1.i1.004 12. The Impact of Generative AI on Student Engagement and Ethics in Higher Education 3 Nov 2024
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The study highlights the need for comprehensive AI literacy courses, ethical guidelines, faculty training, and student involvement in policy formation to ensure responsible AI use, addressing educational initiatives, workforce readiness, and public awareness in the AI age.
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- Need for clear ethical guidelines on AI use.
- Importance of AI literacy courses for students.
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This study examines the impact of generative AI on student engagement and ethics in higher education, revealing widespread AI usage, trust concerns, and a need for AI literacy courses, highlighting the importance of clear guidelines and faculty training for responsible AI use.
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Proceedings Article•10.58459/icce.2024.5007 13. AI and Data Science Literacy Framework for Educators Nurul Amelina Nasharuddin, Nurfadhlina Mohd Sharef, Muhd Khaizer Omar 25 Nov 2024
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The paper emphasizes AI basics, data science literacy, ethical AI use, and pedagogy as key components of AI literacy. It advocates for educational initiatives that prepare educators and students for responsible AI integration, fostering workforce readiness and public awareness.
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- Educators gain knowledge for effective AI integration in teaching.
- Framework prepares students for the digital age.
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This study proposes a literacy framework for educators to effectively integrate AI and data science into teaching, focusing on conceptual, pedagogical, and ethical aspects, while emphasizing technical skills such as programming, to prepare students for the digital age.
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Journal Article•10.1145/3685680 14. Generative AI Literacy: Twelve Defining Competencies R. Annapureddy, Alessandro Fornaroli, D. Gatica-Perez 3 Aug 2024
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The paper outlines twelve competencies for generative AI literacy, emphasizing foundational AI knowledge, prompt engineering, ethical and legal considerations, and the need for educational programs to prepare individuals for responsible use and understanding of generative AI in various domains.
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- Guides research on generative AI literacy understanding.
- Supports development of educational programs and training initiatives.
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This paper introduces a competency-based model for generative AI literacy, outlining 12 essential skills and knowledge areas, including AI literacy, prompt engineering, programming, ethics, and law, to equip individuals to use generative AI responsibly.
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Journal Article•10.4018/979-8-3693-0884-4.ch004 15. UNESCO's AI Competency Framework 20 Sep 2024-Advances in educational technologies and instructional design book series
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UNESCO's AI competence framework emphasizes knowledge, tools, and ethical awareness as key components of AI literacy. It highlights the importance of educational initiatives, professional growth, and effective assessment to prepare teachers and students for an AI-driven future.
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- Improve instructional strategies and individualized learning environments.
- Enhance professional growth and ethical awareness in education.
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UNESCO's AI Competency Framework offers a foundation for AI literacy in education, addressing opportunities and challenges such as ethical issues, contextual adaptability, and professional growth, to equip teachers and students for an AI-driven future.
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Journal Article•10.69478/jitc2024v6n4a06 16. AI-Powered Pedagogy: Integrating Artificial Intelligence in Information Technology Education for Future Workforce Readiness Roger Mission, Renald Jay Fio, Annie Rose Mission 30 Dec 2024-Journal of innovative technology convergence.
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The study emphasizes expanding AI-related curricula, incorporating hands-on learning, and equipping educators for effective instruction. It highlights the need for ethical considerations in AI education and improving access to AI tools to enhance workforce readiness and public awareness.
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- Expand AI-related topics in IT curricula.
- Equip educators for effective AI instruction.
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This study investigates AI integration in IT education, revealing a gap between current curricula and industry demands. It recommends expanding AI topics, hands-on learning, and educator training to improve student skills and address inequities.
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Journal Article•10.1177/10776958241277682 17. Preparing Public Relations’ Practitioners for the AI Era: Advancing Pedagogical Principles in Public Relations’ Artificial Intelligence Education 19 Sep 2024
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The paper identifies essential knowledge areas for AI literacy in public relations: programming and coding proficiency, AI fundamentals, retrieval-augmented generation systems, and LangChain framework for information security, emphasizing ethical considerations and client value centricity in educational initiatives.
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- Need for tailored AI education in public relations.
- Essential knowledge areas for PR AI education outlined.
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Public relations education must adapt to the AI era by incorporating tailored curricula, focusing on authentic dialogue, client value centricity, and legal/ethical considerations, with essential knowledge areas including programming, AI fundamentals, and information security.
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Journal Article•10.1080/10494820.2023.2255228 18. Artificial intelligence (AI) literacy education in secondary schools: a review 8 Sep 2023-Interactive Learning Environments
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The paper emphasizes AI literacy education in secondary schools, focusing on collaborative project-based learning, diverse teaching tools, and assessments. It highlights the need for ethical use of AI, preparing students for future careers, and fostering public awareness of AI technologies.
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- Provides insights for educators on AI literacy implementation.
- Suggests pedagogical approaches and assessment methods for secondary education.
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This study reviews AI literacy education in secondary schools, analyzing 50 studies from 2016-2022, and identifies collaborative project-based learning, teaching tools, and assessment methods, providing insights for educators and policymakers to foster students' AI literacy and technological skills.
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Proceedings Article•10.1145/3585088.3594495 19. Fostering AI Literacy with Embodiment & Creativity: From Activity Boxes to Museum Exhibits Duri Long, Sophie Bargues Rollins, Jessica Roberts +1 more 19 Jun 2023
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The paper emphasizes understanding knowledge representations, machine learning steps, and AI ethics as key components of AI literacy. It highlights the importance of educational initiatives and informal learning contexts, such as activity boxes and museum exhibits, to foster this literacy.
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- Development of activity boxes and museum exhibits to foster AI literacy.
- Focus on learner interests, meaningful outputs, and embodiment and collaboration.
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This paper developed Knowledge Net and Creature Features, two activity boxes for family groups to engage with in their homes that communicate AI literacy competencies such as understanding knowledge representations, the steps of machine learning, and AI ethics.
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Book Chapter•10.4018/978-1-6684-3861-9.ch001 20. Artificial Intelligence and Machine Learning Education and Literacy 27 May 2022
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Key components of AI literacy include understanding AI systems, critical thinking skills, ethical considerations, and addressing misinformation and bias. Educational initiatives must focus on teacher training, workforce readiness, and enhancing public awareness to navigate the challenges and benefits of AI.
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- The paper proposes a framework for teacher training on AI and ML education.
- Initial findings provide insights on attitudes, requirements, and recommendations of teachers.
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In this paper , a framework for teacher training on AI and ML education is proposed, where the design of the teacher training courses and initial findings are described, and insights on the attitudes, the requirements, and the recommendations of the teachers emerged.
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Key Components of AI Literacy for the AI Age
The integration of Artificial Intelligence (AI) into various aspects of life has made AI literacy a critical skill for individuals to navigate the AI-driven world effectively. AI literacy encompasses the knowledge, skills, and ethical awareness necessary to engage with AI technologies judiciously. This section explores the key components of AI literacy, focusing on educational initiatives, workforce readiness, ethical considerations, and public awareness, drawing insights from relevant research papers.
Educational Initiatives
Educational initiatives play a pivotal role in fostering AI literacy across different learner groups. Research indicates that AI literacy should be tailored to different educational levels and disciplines to ensure relevance and effectiveness.
K-12 Education
At the K-12 level, the focus should be on building foundational AI knowledge, including basic concepts, device usage, and ethical considerations (Chee et al., 2024). Hands-on activities and project-based learning can help students develop problem-solving skills and critical thinking (Kong et al., 2024). For instance, collaborative project-based learning has been identified as an effective pedagogical approach for fostering AI literacy in secondary schools ("Artificial intelligence (AI) literacy education in secondary schools: a review", 2023).
Higher Education
In higher education, the emphasis shifts to more advanced competencies, such as understanding data and algorithms, problem-solving, and career-related skills (Chee et al., 2024). The AI Literacy Framework (ALiF) provides a structured approach to developing AI literacy across three key stakeholder groups: students, faculty, and staff. It outlines a three-level progression system across four core competency areas: Technical Understanding, Critical Evaluation, Practical Application, and Ethical Considerations (Zary, 2024).
Vocational and Adult Education
In vocational and adult education, the focus is on integrating AI into existing frameworks, such as the DigCompEdu framework, to develop skills in data literacy, computational thinking, and ethical considerations (Bekiaridis & Attwell, 2024). This ensures that educators are well-prepared to integrate AI tools into their teaching practices.
Workforce Readiness
Workforce readiness is another critical component of AI literacy. As AI continues to reshape employment landscapes, it is essential to equip the workforce with the necessary skills to adapt to evolving technological demands.
Technical Skills
The workforce requires competencies in interpreting and utilizing AI tools for specific careers, along with error detection and AI-based decision-making (Chee et al., 2024). For example, in the field of public relations, practitioners need to develop skills in programming, AI fundamentals, and the retrieval-augmented generation (RAG) system ("Preparing Public Relations’ Practitioners for the AI Era: Advancing Pedagogical Principles in Public Relations’ Artificial Intelligence Education", 2024).
Ethical Considerations
Workforce readiness also involves understanding the ethical implications of AI use. This includes ensuring transparency, accountability, and fairness in AI applications (Gilbert & Gilbert, 2024). For instance, in higher education, students should be equipped with the skills to critically evaluate AI-generated content and understand institutional guidelines on AI use (Zaidy, 2024).
Ethical Considerations
Ethical considerations are a cornerstone of AI literacy. As AI becomes more integrated into various sectors, the need for ethical awareness and responsible use of AI technologies becomes increasingly important.
Ethical Governance
Ethical governance of AI involves ensuring that AI systems are developed and deployed in ways that align with human values and ethical standards. This includes addressing issues such as data privacy, algorithmic bias, and transparency (Yunus et al., 2024) (Gilbert & Gilbert, 2024). The UNESCO Recommendation on the Ethics of Artificial Intelligence provides a comprehensive framework for ethical AI use, emphasizing the need for equity, transparency, and inclusivity (Mutawa, 2024).
Responsible AI Use
Promoting responsible AI use requires fostering critical thinking and ethical awareness among individuals. This can be achieved through educational initiatives that emphasize the ethical boundaries and principles governing AI use (Kong et al., 2024) (Yunus et al., 2024). For example, project-based learning approaches have been shown to support critical reflection on the ethical use of AI (Kong et al., 2024).
Public Awareness
Public awareness is essential for ensuring that individuals are informed about the benefits and challenges of AI. This includes fostering a critical understanding of AI technologies and their impact on society.
Democratization of AI Literacy
The democratization of AI literacy is crucial for empowering marginalized communities and enabling equal participation in AI-related dialogues and initiatives (Asrifan et al., 2024). This can be achieved through public engagement initiatives, such as museum exhibits and activity boxes, that communicate AI literacy competencies in an accessible and engaging manner (Long et al., 2023).
Critical Thinking and Informed Decision-Making
Public awareness should also focus on fostering critical thinking and informed decision-making. This includes equipping individuals with the skills to identify biases, misinformation, and ethical issues related to AI (Asrifan et al., 2024) ("Artificial Intelligence and Machine Learning Education and Literacy", 2022). For instance, understanding how AI systems work and their limitations is essential for making informed decisions about their use ("Artificial Intelligence and Machine Learning Education and Literacy", 2022).
Table: Educational Initiatives for AI Literacy
Educational LevelKey CompetenciesCitation
Conclusion
In conclusion, AI literacy is a multifaceted concept that requires a comprehensive approach to education, workforce readiness, ethical considerations, and public awareness. By fostering AI literacy, individuals can navigate the AI-driven world with confidence, ethical awareness, and informed decision-making. The insights from the research papers highlight the importance of tailored educational initiatives, ethical governance, and public engagement in preparing individuals for the AI age.
Key components of AI literacy include basic AI knowledge, understanding data and algorithms, ethical considerations, and the ability to utilize AI tools. Educational initiatives should focus on fostering critical and responsible integration of AI, ensuring workforce readiness and public awareness.
This study develops a comprehensive AI literacy competency framework, varying by learner group (K-12, higher education, workforce), and proposes a learning pathway, emphasizing critical, strategic, and responsible AI integration, to guide AI curriculum design and lifelong learning.
Key components of AI literacy include understanding AI principles, fostering critical thinking, ensuring ethical technology use, promoting equitable access, and preparing the workforce for evolving demands. Educational initiatives and public awareness are essential for navigating an AI-driven world confidently.
This chapter emphasizes the crucial role of AI literacy in navigating an AI-driven world with confidence, ethical awareness, and informed decision-making, empowering users to engage judiciously with AI technologies and promoting equitable access to AI-driven opportunities.
The study emphasizes problem-solving competence, ethical understanding of AI principles, and metacognitive strategies as key components of AI literacy. Educational initiatives like project-based learning enhance workforce readiness and public awareness, preparing students for responsible participation in an AI-driven society.
This study evaluates a 14-h AI literacy course for senior secondary students using project-based learning, finding improved problem-solving competence, metacognitive strategies, and understanding of AI ethics, with implications for developing an AI Literacy Framework.
The AI Literacy Framework (ALiF) emphasizes four core competency areas: Technical Understanding, Critical Evaluation, Practical Application, and Ethical Considerations, essential for developing AI literacy among students, faculty, and staff in higher education, fostering innovation and academic integrity.
The AI Literacy Framework (ALiF) provides a structured protocol for developing AI literacy in higher education, comprising a three-level progression system across four core competency areas, promoting innovation while maintaining academic integrity.
The paper emphasizes integrating AI into curricula, focusing on critical thinking, problem-solving, ethical use, data privacy, and educator training. These components are essential for preparing students for AI-rich job markets and fostering public awareness of AI's implications.
This study explores AI's impact on education, highlighting the need for policies on AI integration, ethical use, and educator training to prepare students for AI-driven job markets and enhance learning outcomes in an AI-rich future.
The paper identifies key AI competencies for educators, including data literacy, computational thinking, and ethical considerations of AI use, essential for integrating AI in education. These competencies support workforce readiness and enhance public awareness of AI's role in learning environments.
The AI Pioneers project integrates AI into adult education and VET, identifying key AI competencies for educators, supplementing the DigCompEdu framework with skills in data literacy, computational thinking, and AI ethics, enhancing educators' digital competencies and preparing students for an AI-driven future.
Key components of AI literacy include interdisciplinary curriculum integration, ethical considerations, practical applications, and continuous professional development. Educational initiatives must focus on equipping students with knowledge and skills for workforce readiness and fostering public awareness in an AI-driven world.
Integrating professional perspectives for AI literacy in education involves equipping students with knowledge and skills to excel in an AI-driven world through collaborative efforts between librarians and communication professors.
The paper emphasizes digital literacy, critical thinking, and ethics awareness as key components of AI literacy. It advocates for educational initiatives, collaboration among stakeholders, and robust policies to prepare youth for responsible AI interaction and promote ethical digital citizenship.
This policy paper proposes a framework to guide youth in responsible AI use through digital literacy, critical thinking, and ethics awareness, emphasizing the need for collaboration to establish concrete guidelines and promote informed privacy choices in an AI-driven society.
The chapter emphasizes AI literacy through educational initiatives that promote understanding of AI's ethical implications, workforce readiness for AI integration, and public awareness campaigns to foster inclusivity and transparency, ensuring all stakeholders are equipped to navigate the AI age effectively.
This chapter explores the UNESCO Recommendation on AI ethics, focusing on AI's intersection with education, and provides practical approaches for implementing ethical AI in education, promoting equity, transparency, and inclusivity through real-world examples and UNESCO's Policy Area 8 guidelines.
The paper emphasizes education and upskilling as key components of AI literacy, focusing on ethical considerations, workforce readiness, and inclusive access. It advocates for comprehensive educational initiatives to enhance public awareness and ensure responsible AI integration into society.
This research proposes a human-centric AI governance framework, built on five principles, to ensure AI enhances human capabilities, promotes transparency, and upholds ethical standards, addressing challenges and risks through case studies and a collective effort to navigate AI's rapid expansion responsibly.
The report emphasizes fostering AI literacy through educational initiatives, workforce readiness programs, ethical considerations in AI development, and enhancing public awareness. These components are essential for ensuring individuals and communities can effectively engage with and benefit from AI technologies.
This report responds to the UN's Interim Report on AI governance, emphasizing AI's transformative potential for SDGs while highlighting risks and advocating for robust governance, equitable AI ecosystems, and harmonized international frameworks.
The study highlights the need for comprehensive AI literacy courses, ethical guidelines, faculty training, and student involvement in policy formation to ensure responsible AI use, addressing educational initiatives, workforce readiness, and public awareness in the AI age.
This study examines the impact of generative AI on student engagement and ethics in higher education, revealing widespread AI usage, trust concerns, and a need for AI literacy courses, highlighting the importance of clear guidelines and faculty training for responsible AI use.
The paper emphasizes AI basics, data science literacy, ethical AI use, and pedagogy as key components of AI literacy. It advocates for educational initiatives that prepare educators and students for responsible AI integration, fostering workforce readiness and public awareness.
This study proposes a literacy framework for educators to effectively integrate AI and data science into teaching, focusing on conceptual, pedagogical, and ethical aspects, while emphasizing technical skills such as programming, to prepare students for the digital age.
The paper outlines twelve competencies for generative AI literacy, emphasizing foundational AI knowledge, prompt engineering, ethical and legal considerations, and the need for educational programs to prepare individuals for responsible use and understanding of generative AI in various domains.
This paper introduces a competency-based model for generative AI literacy, outlining 12 essential skills and knowledge areas, including AI literacy, prompt engineering, programming, ethics, and law, to equip individuals to use generative AI responsibly.
UNESCO's AI competence framework emphasizes knowledge, tools, and ethical awareness as key components of AI literacy. It highlights the importance of educational initiatives, professional growth, and effective assessment to prepare teachers and students for an AI-driven future.
UNESCO's AI Competency Framework offers a foundation for AI literacy in education, addressing opportunities and challenges such as ethical issues, contextual adaptability, and professional growth, to equip teachers and students for an AI-driven future.
The study emphasizes expanding AI-related curricula, incorporating hands-on learning, and equipping educators for effective instruction. It highlights the need for ethical considerations in AI education and improving access to AI tools to enhance workforce readiness and public awareness.
This study investigates AI integration in IT education, revealing a gap between current curricula and industry demands. It recommends expanding AI topics, hands-on learning, and educator training to improve student skills and address inequities.
The paper identifies essential knowledge areas for AI literacy in public relations: programming and coding proficiency, AI fundamentals, retrieval-augmented generation systems, and LangChain framework for information security, emphasizing ethical considerations and client value centricity in educational initiatives.
Public relations education must adapt to the AI era by incorporating tailored curricula, focusing on authentic dialogue, client value centricity, and legal/ethical considerations, with essential knowledge areas including programming, AI fundamentals, and information security.
The paper emphasizes AI literacy education in secondary schools, focusing on collaborative project-based learning, diverse teaching tools, and assessments. It highlights the need for ethical use of AI, preparing students for future careers, and fostering public awareness of AI technologies.
This study reviews AI literacy education in secondary schools, analyzing 50 studies from 2016-2022, and identifies collaborative project-based learning, teaching tools, and assessment methods, providing insights for educators and policymakers to foster students' AI literacy and technological skills.
The paper emphasizes understanding knowledge representations, machine learning steps, and AI ethics as key components of AI literacy. It highlights the importance of educational initiatives and informal learning contexts, such as activity boxes and museum exhibits, to foster this literacy.
This paper developed Knowledge Net and Creature Features, two activity boxes for family groups to engage with in their homes that communicate AI literacy competencies such as understanding knowledge representations, the steps of machine learning, and AI ethics.
Key components of AI literacy include understanding AI systems, critical thinking skills, ethical considerations, and addressing misinformation and bias. Educational initiatives must focus on teacher training, workforce readiness, and enhancing public awareness to navigate the challenges and benefits of AI.
In this paper , a framework for teacher training on AI and ML education is proposed, where the design of the teacher training courses and initial findings are described, and insights on the attitudes, the requirements, and the recommendations of the teachers emerged.