AI Competency Framework for Students PDF

AI competency framework for students UNESCO – a global leader in education The Global Education 2030 Agenda Education is UNESCO’s top priority because it is a UNESCO, as the United Nations’ specialized agency for basic human right and the foundation...

AI competency framework for students UNESCO – a global leader in education The Global Education 2030 Agenda Education is UNESCO’s top priority because it is a UNESCO, as the United Nations’ specialized agency for basic human right and the foundation for peace education, is entrusted to lead and coordinate the and sustainable development. UNESCO is the Education 2030 Agenda, which is part of a global United Nations’ specialized agency for education, movement to eradicate poverty through 17 Sustainable providing global and regional leadership to drive Development Goals by 2030. Education, essential to progress, strengthening the resilience and capacity achieve all of these goals, has its own dedicated Goal 4, of national systems to serve all learners. UNESCO which aims to “ensure inclusive and equitable quality also leads efforts to respond to contemporary education and promote lifelong learning opportunities global challenges through transformative learning, for all.” The Education 2030 Framework for Action with special focus on gender equality and Africa provides guidance for the implementation of this across all actions. ambitious goal and commitments. Published in 2024 by the United Nations Educational, Scientific and Cultural Organization 7, place de Fontenoy, 75352 Paris 07 SP, France © UNESCO 2024 ISBN: 978-92-3-100709-5 https://doi.org/10.54675/JKJB9835 This publication is available in Open Access under the Attribution-ShareAlike 3.0 IGO (CC-BY-SA 3.0 IGO) license (http://creativecom- mons.org/licenses/by-sa/3.0/igo/). By using the content of this publication, the users accept to be bound by the terms of use of the UNESCO Open Access Repository (https://www.unesco.org/en/open-access/cc-sa). 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Cover credit: Heena Rajput/Shutterstock.com* Designed and printed by UNESCO Printed in France CLD1179.24  S H O R T S U M M A R Y Preparing students to be responsible and creative citizens in the era of AI Artificial intelligence (AI) is increasingly integral to our lives, necessitating proactive education systems to prepare students to be responsible users and co-creators of AI. Integrating AI learning objectives into official school curricula is crucial for students globally to engage safely and meaningfully with AI. The UNESCO AI competency framework for students aims to help educators in this integration, outlining 12 competencies across four dimensions: Human-centred mindset, Ethics of AI, AI techniques and applications, and AI system design. These competencies span three progression levels: Understand, Apply, and Create. The framework details curricular goals and domain-specific pedagogical methodologies. By 2022, Grounded in a vision of students as AI only co-creators and responsible citizens, 15 countries the framework emphasizes critical judgement of AI solutions, awareness of had included AI citizenship responsibilities in the era of learning objectives AI, foundational AI knowledge for lifelong learning, and inclusive, sustainable AI in their national design. curricula “Since wars begin in the minds of men and women it is in the minds of men and women that the defences of peace must be constructed” AI competency framework for students Foreword The past decade has seen widespread adoption of artificial intelligence (AI) in all areas of human development, with the public release of generative AI tools in November 2022 only accelerating its permeation within social life. The education sector, which is at the heart of the transformation of human societies, has been no exception. This process of rapid technological change brings multiple opportunities but also risks and challenges for students, teachers and society at large. In the era of AI, school students need to be prepared to become active co-creators of AI, as well as future leaders © UNESCO who will shape novel iterations of the technology and define its relationship with society. This is exactly the ambition of UNESCO’s AI competency framework for students – the first ever global framework of its kind. It aims to support the development of core competencies for students to become responsible and creative citizens, equipped to thrive in the AI era. This will help students acquire the values, knowledge and skills necessary to examine and understand AI critically from a holistic perspective, including its ethical, social and technical dimensions. The new framework embodies UNESCO’s mandate by anchoring its vision of AI and education in principles of human rights, inclusion and equity. This approach seeks to ensure that AI supports the development of human capabilities, protects human dignity and agency, and promotes justice and sustainability. The publication builds on UNESCO’s previous work in the field, such as the ICT competency framework for teachers, AI and education: Guidance for policy-makers, and the more recent Guidance for generative AI in education and research. It reflects the contributions of a wide range of stakeholders, drawing on UNESCO Member States’ insights on developing and implementing AI school curricula, the expertise of an international working group, three international consultation meetings, and multiple rounds of online consultations. The AI competency framework for students has been developed hand in hand with a competency framework for teachers. It is my hope that these two frameworks will empower students and teachers to shape the digital futures we want. In a world characterized by rising complexity and uncertainty, it is our collective responsibility to ensure that education remains the central space for transformation of our shared futures. Stefania Giannini UNESCO Assistant Director-General for Education Acknowledgements Under the leadership of Stefania Giannini, Assistant Director-General for Education, and the guidance of Sobhi Tawil, Director of the Future of Learning and Innovation Division at UNESCO, the drafting of the publication was led by Fengchun Miao, Chief of Unit for Technology and AI in Education. The framework was drafted by Fengchun Miao, Chief of Unit for Technology and AI in Education at UNESCO and Kelly Shiohira, Director of the Global Science of Learning Education Network. The development of the framework also benefited from the contributions of a group of international experts, including Natalie Lao, Executive Director of the App Inventor Foundation, and Lidija Kralj, Education Analyst at EduConLK. UNESCO is grateful to them for contributing their expertise. Special appreciation is also extended to the following experts for peer-reviewing the publication: Kate Arthur, Co-founder and partner at Comz; Ke Gong, President of the World Federation of Engineering Organizations (WFEO); Kaśka Porayska-Pomsta, Professor of AI in Education at University College London; Nisha Talagala, Co-Founder and CEO of AIClub and AIClubPro; Monique Brodeur, Hugo Couture, Sophie Gosselin, Yves Munn and Benoit Petit from the Conseil supérieur de l’éducation du Québec; and Luc Bégin, Nicolas Bernier and Guillaume Pelletier from the Commission de l’éthique en science et en technologie. Thanks also go to the following UNESCO colleagues for contributing to the peer-review process: Andrea Detmer at the Executive Office of the Culture Sector; Amal Kasry, Chief of the Basic Sciences, Research, Innovation and Engineering Section; Karalyn Monteil, Head of the Programmes and Stakeholder Outreach Unit at the Culture Sector; Renato Opertti, Senior Education Expert at the International Bureau of Education; Arianna Valentini at the International Institute for Higher Education in Latin America and the Caribbean; Soichiro Yasukawa, Chief of the Disaster Risk Reduction Unit in the Science Sector; Martiale Kana Zebaze, Senior Programme Specialist for Science, Technology and Innovation at the UNESCO Harare Office; as well as Jaco Du Toit, Chief, and Zeynep Varoglu, Programme Specialist, at the Section for Universal Access to Information and Digital Inclusion in the Communication and Information Sector. Special thanks go to Luisa Ferrara at the Unit for Technology and AI in Education within the Future of Learning and Innovation Division, for managing expert inputs, and to Glen Hertelendy from the same Unit for coordinating the production of the publication. Additionally, UNESCO is grateful to Jenny Webster for copy-editing and proofreading the text. Finally, UNESCO would like to thank the Tomorrow Advancing Life (TAL) Education Group of China for generously supporting this publication project and, more broadly, for promoting the potential of artificial intelligence for the future of education. AI competency framework for students – Table of contents Table of contents Foreword............................................................................................................................... 6 Acknowledgements............................................................................................................... 7 List of tables and boxes........................................................................................................ 10 List of acronyms and abbreviations..................................................................................... 11 Chapter 1: Introduction....................................................................................................... 12 1.1 Why an AI competency framework for students?................................................................. 12 1.2 Purpose and target audience............................................................................................... 13 Chapter 2: Key principles..................................................................................................... 14 2.1 Fostering a critical approach to AI....................................................................................... 14 2.2 Prioritizing human-centred interaction with AI.................................................................... 15 2.3 Encouraging environ­mentally sustainable AI....................................................................... 15 2.4 Promoting inclusivity in AI competency development......................................................... 16 2.5 Building core AI competencies for lifelong learning............................................................ 17 Chapter 3: Structure of the AI competency framework for students................................... 18 3.1 The framework..................................................................................................................... 18 3.2 Progression levels................................................................................................................ 20 Level 1: Understand............................................................................................................. 20 Level 2: Apply....................................................................................................................... 20 Level 3: Create...................................................................................................................... 21 3.3 Aspects............................................................................................................................... 21 Human-centred mindset...................................................................................................... 22 Ethics of AI........................................................................................................................... 23 AI techniques and applications............................................................................................ 24 AI system design.................................................................................................................. 25 Chapter 4: Specifications of AI competencies for students.................................................. 27 4.1 Level 1: Understand............................................................................................................. 27 4.2 Level 2: Apply....................................................................................................................... 37 4.3 Level 3: Create...................................................................................................................... 45 8  AI competency framework for students – Table of contents Chapter 5: Applying the framework.................................................................................... 53 5.1 Aligning AI competencies as the foundation for national AI strategies............................... 53 5.2 Building interdisciplinary core and cluster AI curricula for AI competency........................... 56 5.3 Framing future-proofing and locally feasible AI domains as carriers of the curriculum......... 58 5.4 Tailoring age-appropriate spiral curricular sequences......................................................... 59 5.5 Building enabling learning environments for AI curricula.................................................... 61 5.6 Promoting the professionalization of AI teachers and streamlining their support............... 62 5.7 Guiding the cohort-based design and organization of pedagogical activities..................... 64 5.8 Constructing competency-based assessments on the progression of key AI aspects........... 69 Conclusion........................................................................................................................... 78 References............................................................................................................................ 79 Endnotes.............................................................................................................................. 80 9 AI competency framework for students – List of tables and boxes List of tables Table 1. AI competency framework for students................................................................. 19 Table 2. Competency blocks for level 1: Understand........................................................... 29 Table 3. Competency blocks for level 2: Apply.................................................................... 37 Table 4. Competency blocks for level 3: Create.................................................................... 45 Table 5. Examples of assessment tasks................................................................................ 73 List of boxes Box 1: Recommendation on the Ethics of Artificial Intelligence.......................................... 53 Box 2: Supporting human resource development: The Republic of Korea’s National Strategy for Artificial Intelligence............................................................................ 55 Box 3: The United Arab Emirates’ interdisciplinary approach to K-12 AI curricula.............. 57 Box 4: The spiral curricular sequence of ‘Day of AI’ courses................................................. 60 Box 5: Typical enabling learning environment set up by governments’ AI curricula........... 61 Box 6: An AI competency framework for AI subject teachers in China................................ 63 Box 7: Pedagogical methodologies in the MIT curriculum on the ethics of AI for middle school students........................................................................................................ 66 10  AI competency framework for students – List of acronyms and abbreviations List of acronyms and abbreviations AGI Artificial general intelligence AI Artificial intelligence AI CFS AI competency framework for students CCDI Computing, Creative Design and Innovation CG Curricular goal GAN Generative adversarial networks K-12 Kindergarten through 12th grade ICT Information and communication technology IEA International Energy Agency IGO Intergovernmental organization ITU International Telecommunication Union MIT Massachusetts Institute of Technology NGO Non-governmental organization STEAM Science, technology, engineering, arts and mathematics STEM Science, technology, engineering and mathematics TVET Technical and vocational education and training UNESCO United Nations Educational, Scientific and Cultural Organization 11 AI competency framework for students – Chapter 1: Introduction Chapter 1: Introduction 1.1 Why an AI competency Governments acknowledged the urgent framework for students? need to develop AI literacy and more advanced AI competencies as early as 2019, The rapid iterations and proliferation of when they adopted the UNESCO Beijing artificial intelligence (AI) across all aspects of Consensus on AI and Education. Indeed, the life and all sectors are posing new challenges Beijing Consensus underlined the need to regarding the nature of machine intelligence, equip people with AI literacy across all layers the collection and use of personal data, the of society. However, according to a recent role of humans and machines in decision- survey conducted across 190 countries, making, and the impact of AI on social and only some 15 countries were found to be environmental sustainability. It is essential developing or implementing AI curricula that education systems prepare students in school education (UNESCO, 2022b). The not only with the knowledge and skills survey also found that there was wide to use AI, but also with insight into the variation in how countries defined AI literacy, potential impact of technology on societies skills and competency. The results of the and the environment at large. Given the survey therefore underscored the urgency transformative potential of AI for human of developing a harmonized approach to societies, it is crucial to equip students with integrating AI-related teaching and learning the values, knowledge and skills needed for content in school curricula. the effective use and active co-creation of AI. Far too often, the definition of AI Education, as a public sector, cannot be competencies for students is influenced reduced to a testing ground for the passive by training designed and/or provided by adoption of AI. The role of the education private companies, which tends to focus sector is not only to prepare students to on technical skills to operate profit-driven adapt to a society that is increasingly being AI platforms. Such approaches seldom transformed by AI technologies; it also has engage with the broader critical issues a key role to play in empowering young of the implications of AI for learning and people to help co-create sustainable futures citizenship, more broadly. There is currently by rebalancing our relationships, not only a void in too many education systems when with others, but also with technology and it comes to public-approved frameworks the environment. By defining the core for introducing AI-related content and competencies that students are likely to methods to educational curricula. One require as we move deeper into the AI era, of the challenges that public education the ultimate aim of this AI competency systems are facing in filling this void is the framework for students (AI CFS) is to help lack of an international reference framework shape responsible and creative citizens that on AI competencies for students. Such can co-create these desirable futures. an international reference framework can inform the design of national/local AI competency frameworks for students that 12  AI competency framework for students – Chapter 1: Introduction promote a critical and ethical approach to 1.2 Purpose and target audience AI tools, as well as develop the foundational knowledge required for their effective and The AI CFS aims to serve as a guide for meaningful use in education. The aim of this public education systems to build the AI CFS is to fill this void. competencies required of all students and citizens for the effective implementation of AI technology is a rapidly moving target. It is national AI strategies and the building of therefore critical to ensure that all students inclusive, just and sustainable futures in this have a core set of knowledge, skills and new technological era. values for interacting ethically and effectively with AI in the present. This foundation can More specifically, the AI CFS: (1) provides a enable students to utilize future iterations of global reference framework on the core set AI technology in an appropriate and human- of AI competencies for students to inform centred manner. the design of national or institutional AI competency frameworks; (2) specifies The AI CFS supports educational authorities typical attitudinal and behavioural to respond to these needs by defining a performance relating to the key aspects of AI core set of competencies for students that competencies at different levels of mastery fall under four aspects: Human-centred to help design AI-related curricular content mindset; Ethics of AI; AI techniques and for school students; and (3) recommends applications; and AI system design. These an open-ended roadmap to help plan the four aspects are articulated at three levels learning sequence of AI curricula across of progression or mastery (understanding, grade levels. application and creation), resulting in a total of twelve competency blocks. For each As a global reference framework, the AI CFS of these competency blocks, the AI CFS is to be tailored to the diverse readiness proposes detailed specifications on relevant levels of local education systems in terms of pedagogical methodologies and strategies curricula, the enabling learning environment for the planning and provision of AI-related for teaching AI, preparedness of teachers, curricular content. and the prior knowledge and capacities of specific groups of students. The AI CFS is aimed principally at policy- makers, curriculum developers, providers of education programmes on AI for students, school leaders, teachers and educational experts. 13 AI competency framework for students – Chapter 2: Key principles Chapter 2: Key principles 2.1 Fostering a critical students with the values, knowledge approach to AI and skills necessary to critically examine the proportionality of AI from an ethical Critical thinking is a fundamental skill that perspective. This includes examining and students need to meaningfully engage with understanding its impact on human agency, AI as learners, users and creators. Students social inclusion and equity, institutional also have the responsibility to determine and individual security, cultural and what types of AI should be developed and linguistic diversity, the construction and how they should be used to drive human expression of plural opinions, as well as societies towards inclusive, environmentally on the environment and on ecosystems. sound, shared futures. School students Students are expected to move beyond need to be supported to become active the misconception that AI is a solution to co-creators of AI, as well as potential leaders everything. Rather, they are to become who will define further iterations of AI and conscious decision-makers on when AI its interactions with human society for systems and applications should, or should present and future generations. To support not, be used; what problems they may or this vision, the AI CFS is designed to foster may not solve; and when and how AI should a critical approach to AI by engaging be designed and used as one part of a wider students with fundamental questions, such solution. The AI CFS aims to nurture students’ as: is AI poised to help solve real-world aspirations to apply and design AI tools to challenges faced by humans, or does it pose serve meaningful specific purposes or to insurmountable threats to humans? Are address real-world challenges and promote adverse impacts on climate of training and sustainable development. using AI disproportionate to its anticipated benefits? What social, economic, political and Societies are moving into the era of AI at demographic impacts of the use of AI should different paces, but students everywhere are, be carefully reviewed? or will be, citizens in contexts characterized by widespread AI integration. They will not The AI-driven transformation across only have to comply with legal regulations development sectors has profound and ethical principles, but, as citizens, implications for human agency, human they will also have to contribute to the interactions, social equity, economic adaptation of AI standards and regulations. inclusiveness, and environmental The framework therefore highlights the sustainability. Thus, in the first place, school importance of supporting students to students are expected to be conscious become responsible and ethical users of, and knowledgeable of the advantages as well as contributors to, AI. It engages and limitations of existing affordances of students to reflect on key controversies AI. The pre-condition for responsible use surrounding AI, internalize ethical consists in students’ abilities to detect principles, and become familiar with related the trustworthiness and proportionality regulations. of AI tools. The AI CFS aims to prepare 14  AI competency framework for students – Chapter 2: Key principles The AI CFS sets out a forward-looking compromise the development of human vision of the type of citizenship required intellectual skills. While AI can be used to by societies increasingly shaped by AI. It challenge and extend human thought, it proposes that students be challenged and should not be allowed to usurp or replace enabled to make meaningful use of AI for critical thinking. The protection and self-actualization; to evaluate its social, enhancement of human agency should, economic and environmental impacts; therefore, always be a core principle in and to contribute, at a level appropriate the design of AI curricula and education for their age or grade, to the development programmes. The AI CFS aims to support of AI regulations, helping to shape our students to understand the types of relationship with technology in society data that AI may collect from them, the at large. methods with which the data may be used to train AI models, and the impact that the data cycle may have on their privacy and 2.2 Prioritizing human-centred wider lives. It seeks to stimulate students’ interaction with AI intrinsic motivation to grow and learn as individuals and to reinforce their autonomy In the era of AI, interaction between humans in contexts in which sophisticated AI and AI systems and applications will become systems are increasingly being integrated. an essential constituent element of public Critical AI competencies, as proposed in service, production and commerce, social this framework, can also guide students practice, learning, and daily life. Establishing to understand the unique value of social the competencies needed to understand and interaction and of the creative works ensure human-centred interaction with AI in produced by humans that should not be these domains is a priority for the AI CFS. replaced by AI outputs. By developing UNESCO’s human-centric approach competencies for human-centred advocates that the design and use of AI engagement with AI, the framework aims to should serve the development of human prevent students from becoming addicted to capabilities, protect human dignity or dependent on AI, and to foster behaviours and agency, and promote justice and that maintain human accountability for high- sustainability throughout the entire AI life stakes decisions. cycle and all possible human–AI interaction loops. Such an approach must be guided by human rights principles and respect 2.3 Encouraging environmentally for the linguistic and cultural diversity that sustainable AI defines the knowledge commons. A human- As co-creators and potential leaders of the centred approach also requires that AI be next generations of AI technology, students used in ways that ensure transparency and need to have a critical understanding of the explainability, as well as human control and adverse environmental impact of profit- accountability. driven approaches to the design, training As AI becomes increasingly sophisticated and deployment of AI models. Education and more widely used, a key danger is its systems bear the responsibility of ensuring potential to undermine human agency and that students understand carbon emissions, 15 AI competency framework for students – Chapter 2: Key principles analyse the root causes of climate change, life cycle. This covers the selection of and act judiciously to protect the climate representative data, the choice of bias- and the environment. agnostic algorithms and anti-discrimination training methods, the design of accessible In the race to produce increasingly powerful functionalities, testing for the inclusiveness AI models, environmental sustainability of AI outputs, and impact assessment of the is often considered to be of secondary use of AI on social inclusion. With regard importance. In some instances, it has even to AI system design, students can deepen been intentionally obscured by claims that their understanding and application skills AI holds the promise of solving climate to assess the needs of users with different change. As global leaders and policy-makers abilities as well as those from diverse work to consider regulations around the linguistic and cultural backgrounds. consumption of energy and the protection of the environment, it is imperative that In selecting the models and categories students understand how the training of AI of technologies as vectors of AI-related models is contributing to the destruction of teaching and learning, care is needed to the natural environment. Learning about AI avoid favouring certain demographics over should empower them to urgently explore others. When recommending specific AI tools more climate-friendly approaches to the for educational purposes, rigorous public design, training and use of AI models. The validation mechanisms must be applied AI CFS attends to this by guiding students to avoid algorithms with bias(es) related to design and implement project-based to gender, ability, socio-economic status, learning activities on the environmental language, ethnicity and/or culture. AI tools impacts of AI use and training, prompting that are designed to support individuals students to investigate potential solutions to with disabilities and promote linguistic and mitigate these impacts. cultural diversity should be given priority. Where such validation mechanisms are unavailable, the recommendation of specific 2.4 Promoting inclusivity in AI AI tools for use at scale should be avoided. competency development Turning to delivery of the curriculum, specific Access to AI and AI competencies represent measures can be outlined to provide basic the two sides of citizens’ basic rights in enabling conditions for the implementation today’s world. All students should have of the AI CFS-based curriculum. While AI inclusive access to the environments frameworks or educational programmes required for learning about AI at the basic should be designed to be applicable to level, and they should be supported to learn all students, including those who live in how to embed the principle of inclusivity low-tech settings, engagement with AI into the design of AI and be prepared to without access to the internet and AI tools contribute to an inclusive AI society. will limit the scope and mastery level of AI competencies. Governments should When defining AI competencies, school commit to promoting inclusive access to students should be provided with basic internet connectivity, updated digital opportunities to understand and apply devices, open-source or affordable AI the principle of inclusivity across the AI 16  AI competency framework for students – Chapter 2: Key principles programmes and software, and essential AI the need to understand controversies devices, with the support of academia or surrounding AI and the key ethical the private sector, where appropriate. Once principles that guide regulation, as well again, these efforts must pay particular as foster practical skills to combat bias, attention to students who have disabilities protect privacy, promote transparency and and/or are from linguistic or cultural minority accountability, and adopt an ethics-by- groups. design approach to the co-creation of AI. The core competencies are brand-agnostic 2.5 Building core AI and product-agnostic, ensuring that students competencies for lifelong can appropriately engage with a range of learning tools, as well as with future iterations of AI technologies. It enables them to develop an AI-related teaching and learning should age-appropriate and progressively deeper serve to build core AI competencies that understanding of AI data, algorithms, models allow students to accommodate new and system design. Students must be knowledge, as well as adapt to solving supported to construct this understanding problems in new contexts with novel AI by connecting AI concepts with real-world technologies. First and foremost, these challenges to develop critical problem- core competencies must include values solving skills. Students should be further associated with an ethical and human- encouraged to exploit their creativity in centred mindset. Students need guidance to an effort to optimize existing AI models or progressively deepen their understanding co-create more meaningful AI. These core of particular human rights – such as rights competencies constitute the foundation for to equality, non-discrimination, privacy further learning and more specialized use of and plural expression – as well as their AI in further education, work and life. implications for varying forms of human–AI interaction. The competencies also reflect 17 AI competency framework for students – Chapter 3: Structure of the AI competency framework for students Chapter 3: Structure of the AI competency framework for students 3.1 The framework It also aims to foster a critical understanding of the proportionality1 of specific AI tools The AI CFS specifies twelve competency for our human needs and for the sustainable blocks based on a matrix of two dimensions. development of the environment and The first dimension comprises four ecosystems. Ethics of AI, the second interlinked aspects of AI competencies, while aspect, encompasses the social and ethical the second dimension includes three levels components of students’ AI competencies, of progression or mastery that students are including the social skills to navigate, expected to engage with iteratively. understand, practise and contribute to the adaptation of a growing set of principles that While the AI CFS anchors the definition of regulate human behaviour throughout the AI competency on three pillars that frame entire life cycle of AI. wider core competencies for students – namely, knowledge, skills and values The third aspect, AI techniques and – it also aims to encourage an ethical applications, represents an integrated understanding of human-led methods view of the intrinsically linked conceptual underlying AI systems. Based on this knowledge on AI and associated operational conceptualization, the framework defines skills, using selected AI tools and authentic four essential constituent elements of tasks. The last aspect is AI system design, students’ AI competency: a human-centred which covers comprehensive engineering mindset, ethics of AI, AI techniques and skills that determine the problem scoping, applications, and AI system design. These architecture building, training, testing and elements focus on fundamental values, optimization of AI systems. This aspect aims social responsibilities to uphold ethical to challenge and enable students to gain principles, foundational knowledge and a deeper understanding of AI systems and skills, and higher-order thinking skills for scaffold their exploratory learning for the system design. While different elements pursuit of further study in the field of AI. can be developed through domain-specific learning and pedagogical methodologies, The second dimension of the framework AI competencies are ultimately a set of outlines three levels of progression: interdisciplinary, general abilities and value Understand, Apply and Create, which are orientations that extend beyond particular AI designed to reflect levels of mastery across domains or tools. all four aspects outlined above. They can be used to furnish AI curricula or programmes The first aspect positions students’ of study with a spiral learning sequence competencies within a human-centred attitude towards the benefits and risks of AI. 18  AI competency framework for students – Chapter 3: Structure of the AI competency framework for students across grade levels, to assist students in (1) the scoping of main AI-related focus areas progressively building a systematic and and expected mastery levels, tailored to local transferable schema of competencies. AI readiness and available instructional time; (2) the identification of AI-related learning The framework matrix cuts across the four content that can be integrated across aspects for the three levels of progression existing curricula, subject areas, and grade or mastery (see Table 1). At the intersection levels; (3) the definition of proficiency levels of these levels and aspects are twelve and the development of assessment criteria constituent blocks of AI competencies whose to assess students’ general AI competencies characteristics underpin the critical thinking, and progression; and (4) the design ethical examination, practical use and and exploration of age-appropriate and iterative co-creation of AI. These competency domain-specific agile teaching and learning blocks should be understood as interlinked methodologies. Many of these factors will units for the framing of key components. be vital to consider when a country, district Rather than considering them as fragmented or school localizes this framework; the and disparate topics to be learned in selection of focus aspects and specification isolation, they can be connected and woven of the desired mastery levels, for instance, together as the operational organs of AI will depend on students’ existing AI competency. competencies, the training and skills of The matrix provides a blueprint for learning teachers, the availability of learning hours, outcomes at a minimum level of mastery and local AI readiness, including affordability within a certain competency block. More and infrastructure. specifically, the matrix is designed to guide: Table 1. AI competency framework for students Competency aspects Progression levels Understand Apply Create Human-centred Human agency Human Citizenship in the era mindset accountability of AI Ethics of AI Embodied ethics Safe and responsible Ethics by design use AI techniques and AI foundations Application skills Creating AI tools applications AI system design Problem scoping Architecture design Iteration and feedback loops 19 AI competency framework for students – Chapter 3: Structure of the AI competency framework for students 3.2 Progression levels This level of mastery provides the essential attitudinal, cognitive and practical The three levels reflect increasing foundations for the further study of AI. It sophistication, proficiency and ethical does not define the exit-level competencies consciousness in using and co-creating for specific areas or domains of AI overall. AI technology. Students are expected to progress through them reciprocally. Level 2: Apply These levels, and the specifications of each competency block, can guide both the Given that the use of AI has permeated all formative and summative evaluations of sectors, as well as all aspects of life, including students’ AI competencies, as well as inform education and work, students at school the design of contextually relevant and agile should be prepared to become responsible, pedagogical methodologies. active and effective users of AI, both for the sake of their own individual interests, Level 1: Understand as well as to address shared sustainability challenges. The outcomes at the second This first level is designed for all students. All level, ‘Apply’, are therefore relevant for all individuals are, or will be, interacting with school students and can be used to tailor some form of AI over the course of their lives. the scope, breadth and level of difficulty of It is also true that AI providers have been thematic modules of a formal AI curriculum. mining and manipulating data from almost Studying at this level requires students to all internet users. All students must therefore have acquired a basic understanding of the develop the human-centred values, human-centred approach and essential knowledge and skills needed to engage in ethical principles for AI, as well as basic AI a safe, informed and meaningful manner knowledge and application skills. in their daily interaction with AI in various spheres of life. At the ‘Apply’ level, students are expected to enhance, transfer and adapt their learned At the ‘Understand’ level, students are values, knowledge and skills to new learning expected to foster an understanding of processes. They do so by addressing what AI is and construct age-appropriate theoretical questions and/or practical tasks interpretations of the values, ethical issues, in more complex contexts, and by critically concepts, processes and technical methods examining advanced technical methods underlying AI tools and their uses. They behind AI tools. Upon achieving this level, should be able to explain or exemplify their students will have constructed a sound knowledge with connections to real-life and transferable foundation of conceptual or social practices and assimilate novel knowledge and associated AI skill-sets. They knowledge by integrating them into their should also be able to apply the human- own knowledge schemas. centred mindset and ethical perspective to the assessment, study and practical uses of AI tools. 20  AI competency framework for students – Chapter 3: Structure of the AI competency framework for students Students at this level may progress to tools or AI models. Throughout the iterative the third, more specialized level, Create. process of customizing and testing AI However, it is possible that some students technologies, students are expected to will not have a strong interest in AI, or will reinforce the sense of being an AI co-creator lack sufficient time or opportunities to and belonging within a broader community, finetune their AI competencies within the helping to lead the human-centred design formal learning environment at school. For and use of AI. At this level, students are many, ‘Apply’ at Level 2 will be the point also expected to enhance their capacity to of exit for their AI-related competency critically assess the social implications of AI development, at least at school. and to personalize the responsibilities of being a citizen in AI-driven societies. Level 3: Create Learning at the ‘Create’ level also aims The exponential pace of innovation within to foster students’ creative problem- the AI sector means that technology solving skills and a proactive attitude to providers are defining the terms of the advocating for ethical AI practices. Meeting transformation of our societies. Developing the requirements of this level in full will critical AI competencies is critical to ensuring require sufficient allocation of learning that the design, deployment and use of time and space within the curriculum (e.g. AI responds to the needs of users and an entire semester or multiple semesters). benefits the public. School students should The learning programme must also provide be prepared to create trustable AI tools the necessary AI resources and facilitate and to take a leading role in the definition age-appropriate innovative pedagogical and design of the next generation of AI methodologies. For students who do not technologies. At the ‘Create’ level, students have a strong interest in pursuing deeper are expected to become conscientious AI study in the field, the learning outcomes at co-creators, developing human-centred this level, in particular under the ‘AI system solutions to positively impact the design design’ aspect, should be offered as elective and use of AI. Study at this level requires programmes rather than as compulsory the integrated application of the acquired requirements for all students. values, knowledge and skills on AI to design, implement and test AI solutions that can 3.3 Aspects help address real-world challenges. The four aspects specify the essential Students will critically leverage their constituent elements of AI competencies knowledge and skills on data, algorithms and that students need to build and continuously ethical design; actively craft AI applications; update in order to become responsible users and deliberate on the adaptation of AI and active co-creators of AI, and potential regulations. leaders in defining and developing next At the ‘Create’ level, students are expected to generations of AI. reinforce their interest in AI innovation and develop new AI tools based on open-source and/or customizable datasets, programming 21 AI competency framework for students – Chapter 3: Structure of the AI competency framework for students Human-centred mindset Competency aspects Progression levels Understand Apply Create Human-centred Human agency Human Citizenship in the era mindset accountability of AI The ‘Human-centred mindset’ aspect focuses Human accountability: Students are on students’ values, beliefs and critical expected to recognize that human thinking skills, applied to the examination accountabilities are the legal obligations of of whether AI is fit for purpose, whether its AI creators and AI service providers, and to use is justified, how humans should interact understand what human accountabilities with it, and what responsibilities individuals they should assume during the design and institutions should take on to contribute and use of AI. They should also develop an to the building of safe, inclusive and just AI awareness that human accountability is a societies. A human-centred mindset lays legal and social responsibility when using AI the foundation for further engagement to assist in decision-making, and that human with all aspects of AI. The full expression choice should not be ceded to AI when of this aspect also encompasses human making high-stakes decisions. identities in relation with AI, assuming social and civic responsibilities, and the pursuit Citizenship in the AI era: Students are or deepening of personal interests in the AI expected to critically understand the impact era. The values and skills that this aspect is of AI on human societies and to promote intended to nurture can be characterized by responsible and inclusive design and use the following three competency blocks: of AI for sustainable development. They should have an awareness of their civic and Human agency: Students are expected social responsibility as citizens in the era of to be able to recognize that AI is human- AI. Students are also expected to develop a led and that the decisions of AI creators desire to continue learning about, and using, influence the way in which AI systems AI throughout their lives to support self- impact human rights, human–AI interaction, actualization. as well as their own lives and societies. They are expected to understand the implications of protecting human agency throughout the design, provision and use of AI. Students will understand what it means for AI to be human-controlled, and what the consequences might be when this is not the case. 22  AI competency framework for students – Chapter 3: Structure of the AI competency framework for students Ethics of AI Competency aspects Progression levels Understand Apply Create Ethics of AI Embodied ethics Safe and responsible Ethics by design use The ‘Ethics of AI’ aspect represents the ethical assigning social status, or predictive value judgements, embodied reflections, algorithms for grading examinations). and social and emotional skills students This includes the ability to assess require to navigate, understand, practise and whether a certain AI solution infringes contribute to the adaptation of a growing set upon human values and rights, of principles and regulatory rules relative to particularly data privacy, and to the entire life cycle of AI systems. Students decide on whether a particular AI are expected to understand and apply method complies with global or local knowledge on the governance of ethics at regulations. the intersection of global implications and local contexts. As the rapid iterations of AI Proportionality: Students develop are triggering more profound controversies, the capacity – as appropriate for their the scope of the ethics of AI is expanding, age and ability level – to examine and new regulations, laws and rules are whether or not the use of a specific AI being adopted. The three competency system is advantageous in achieving blocks for this aspect outline key steps for a justified aim, and whether or not a students to gradually internalize ethical given AI method is appropriate to the principles as well as habituate compliance context. with AI regulations. Non-discrimination: Students are Embodied ethics: Students are expected aware of and are able to detect to develop a basic understanding of the gender, ethnic, cultural and other issues underlying key ethical debates around biases embedded in AI tools or their AI, including the impact of AI on human outputs. Further, students are aware rights, social justice, inclusion, equity and of AI divides within and between climate change within their local context and countries, and understand the need personal lives. They will have understood, to make efforts to address these internalized, and adopted the following and ensure greater accessibility and principles in their reflective practices and inclusivity. uses of AI tools in their learning and beyond: Sustainability: Students are able to Do no harm: Students demonstrate explain and illustrate the implications an understanding that AI systems of AI systems for environmental should not be used for purposes that sustainability. might be harmful for humans (such as facial recognition for surveillance or 23 AI competency framework for students – Chapter 3: Structure of the AI competency framework for students Human determination in human–AI of the risks of disclosing data privacy collaboration: Students are able to and they take measures to ensure that demonstrate why humans should their data are collected, used, shared, bear ethical and legal responsibilities archived and deleted only with their for the use of AI; they are able to deliberate and informed consent. exemplify how humans can remain They are also aware of the specific accountable in AI-assisted decision- risks of certain AI systems, and are making loops, rather than cede able to protect their own safety, as determination to machines. well as that of their peers, when using AI. Transparency and explainability: Students are aware that users are Ethics by design: Students are entitled to request explanatory expected to adopt an ethics-by- information from designers and design approach to the design, providers on how AI tools work, how assessment and use of AI tools, as well their outputs are produced based as to the review and adaptation of AI on algorithms and models, and the regulations. Students are aware that degree to which the deployment and assessing the intent behind AI design application of certain AI tools are involves examining all steps of the AI appropriate for users of a certain age life cycle, starting with the stage of or ability level. conceptualization. Students should be able to assess the compliance of an AI Safe and responsible use: Students tool with ethical regulations, as well are expected to be able to use AI in as review AI regulations and inform a responsible manner in compliance adaptation. with ethical principles and locally applicable regulations. They are aware AI techniques and applications Competency aspects Progression levels Understand Apply Create AI techniques and AI foundations Application skills Creating AI tools applications The ‘AI techniques and applications’ a human-centred mindset and its associated aspect represents the intrinsically linked ethical principles. The basic knowledge conceptual knowledge on AI and associated structure and practical skills on data and operational skills, in connection with AI programming is the foundation for the concrete AI tools or authentic tasks. This capacity to design and build AI systems, aspect serves as the most important and especially for students who have strong transferable technical foundation for a interests and abilities in the field. The ‘AI concrete understanding and application of techniques and applications’ aspect implies 24  AI competency framework for students – Chapter 3: Structure of the AI competency framework for students that students are expected to look into life, concretizing a human-centred mindset exemplar AI tools to gain insight on how AI and ethical principles by understanding how is developed, based on data and algorithms. AI works and how AI interacts with humans. Students will synchronically acquire skills in AI programming and reinforce the Application skills: Students are expected transferability of their knowledge and skills to be able to construct an age-appropriate by applying them to the crafting of AI tools. understanding of data, AI algorithms and In the stream of the three progression levels, programming, as well as acquire transferable students are also expected to integrate application skills. Students are expected ethical, cultural and social parameters, and to be able to critically evaluate and solidify the interdisciplinary foundational leverage free and/or open-source AI tools, knowledge and skills in science, technology, programming libraries and datasets. engineering, mathematics, arts, languages Creating AI tools: Students are expected to and social studies. be able to deepen and apply knowledge and AI foundations: Students are expected skills on data and algorithms to customize to be able to build basic knowledge and existing AI toolkits to create task-based AI skills on AI, particularly with respect to tools. Students are expected to integrate data and algorithms, understanding their human-centred mindset and ethical the importance of the interdisciplinary considerations into the assessment of foundational knowledge required to existing AI resources. They are also expected gradually deepen understanding of data to develop the social and emotional skills and algorithms. Students should also be needed to engage in creating with AI, able to connect conceptual knowledge on including through adaptivity, complex AI with their activities in society and daily communication and teamwork skills. AI system design Competency aspects Progression levels Understand Apply Create AI system design Problem scoping Architecture design Iteration and feedback loops The aspect of ‘AI system design’ focuses field. Students are also expected to deepen on the systemic design thinking and and practise ‘ethics by design’. Although comprehensive engineering skills required the systemic design thinking methodology, for problem scoping, design, architecture associated human-centred values and ethical building, training, testing and optimization principles, and required knowledge and of AI systems. This aspect aims to challenge skills on AI may be embedded in all other the explainability of AI systems and to enable aspects of students’ AI competencies, this exploratory learning for students who will aspect mainly targets students who have a pursue further programmes of study in the 25 AI competency framework for students – Chapter 3: Structure of the AI competency framework for students particular interest in, and commitment to, the interdisciplinary skills necessary to deepening their knowledge and skills in this leverage datasets, programming tools field. and computational resources to construct a prototype AI system. This includes the Problem scoping: Students are expected expectation that they apply deepened to be able to understand the importance of human-centred values and ethical principles ‘AI problem scoping’ as the starting point in their configuration, construction and for AI innovation. They are expected to optimization. be able to examine whether AI should be used in particular situations, from a legal, Iteration and feedback: Students are ethical and logical perspective; and to expected to enhance and apply their define the boundaries, goals and constraints interdisciplinary knowledge and practical of a problem before attempting to train methods to evaluate the appropriateness an AI model to solve it. Students are also and methodological robustness of an AI expected to acquire the knowledge and model and its impact on individual users, project-planning skills needed in order societies and the environment. They should to conceptualize and construct an AI be able to acquire age-appropriate technical system, including the ability to assess the skills to improve the quality of datasets, appropriateness of different AI techniques, reconfigure algorithms and enhance define the need for data, and devise test and architectures in response to results of tests feedback metrics. and feedback. They should be able to apply a human-centred mindset and ethical Architecture design: Students are expected principles in simulating decision-making on to be able to cultivate basic methodological when an AI system should be shut down and knowledge and technical skills to configure how its negative impact can be mitigated. a scalable, maintainable and reusable They are also be expected to cultivate their architecture for an AI system covering layers identities as co-creators within the wider AI of data, algorithms, models and application community. interfaces. Students are expected to develop 26  AI competency framework for students – Chapter 4: Specifications of AI competencies for students Chapter 4: Specifications of AI competencies for students The following specifications of the AI CFS cohorts, based on their AI readiness and clarify what each competency block entails that of their teachers, available instructional in terms of curricular goals, desirable time and local learning environments. The pedagogical methods and required learning specifications include recommendations environments, with consideration given to for configuring these environments in line inclusivity as well as variation in levels of AI with the curricular goals, with regard to readiness. inclusivity, the potential of open-source options, and the sharing of AI resources with The specifications outlined below are academic institutes and the private sector. based on the assumption that students’ AI competencies are the result of the Finally, the specifications also propose integrated interventions of national AI pedagogical methodologies for specific curricula; extracurricular programmes; domains of AI at a certain progression level. informal learning through various media, These may inspire teachers and students to including the internet; and engagement explore agile methods of delivery that are with families and local communities. To relevant for specific contexts and needs. guide the development of an AI curriculum, the AI CFS specifies the expected learning and behavioural outcomes of a formal AI 4.1 Level 1: Understand curriculum while considering the impact The overall goal of this level is to support all of informal learning in social contexts. AI- students to acquire an understanding of related learning – introduced into curricula what AI is and to construct age-appropriate as a specific subject, or as modules within interpretations of the values, ethical related disciplines, such as computer issues, concepts, processes and technical science or information and communication methods underlying AI tools and their uses. technology (ICT) – should be allocated Students should also be supported to make adequate instructional time within a connections between their knowledge of semester, or preferably, across multiple AI and real-life experiences, and between semesters. domain-specific knowledge of AI and The specified curricular goals outline knowledge of related learning areas. domain-specific values, knowledge and The curricular goals outlined in Table 2 help skills that can be applied to students at a to map the set of foundational values, ethical range of ages and ability levels, who are principles, knowledge and understanding exposed to AI-related learning for the first that can ensure the proper and effective time. It is up to national or institutional use of AI by students – an ability sometimes curriculum agencies to define concrete referred to as ‘AI literacy’. The suggested learning objectives for specific student pedagogical methods are designed to 27 AI competency framework for students – Chapter 4: Specifications of AI competencies facilitate age- and domain-appropriate real-world use scenarios. The specifications teaching and learning practices that can also recommend basic learning settings, potentially stimulate students’ interests and which include practising with unplugged support their learning trajectory on the basis and low-tech options. of concrete tools, personal experiences, and 28  AI competency framework for students – Chapter 4: Specifications of AI competencies for students Table 2. Competency blocks for level 1: Understand STUDENT CURRICULAR GOALS SUGGESTED LEARNING COMPETENCY (AI curricula or programmes PEDAGOGICAL METHODS ENVIRONMENTS of study should…) (Institutions and teachers (The following learning can consider and adapt the settings can be following learning methods.) provided and adapted.) Human- 4.1.1 Human agency CG4.1.1.1 Foster an Visualizing the abstract Unplugged centred understanding that AI concept of human agency learning settings Students are is human-led: Based on throughout the AI life mindset like paper-based expected to be selected AI tools, explain to cycle: Ask students to draw articles, printed able to recognize students that AI is human- concept maps of human reading materials that AI is human- led; facilitate students to agency in key steps of the and worksheets. led and that the develop a stepwise and life cycle of selected AI tools, decisions of the AI including data ownership, Locally available integral comprehension of creators influence human agency which may respecting data privacy when AI tools including how AI systems collecting and processing mobile phones with cover principles on data impact human AI applications. ownership and data privacy, data, explainability of AI rights, human–AI protection of human rights algorithms and AI models, Predownloaded interaction, and in collecting and processing human-controlled evaluation or recorded videos their own lives data, explainability of AI of AI outputs, and human and other resources and societies. They methods, human control in determination in AI-assisted related to specific are expected to deployment, and human decision-making. The case studies, or understand the determination in using AI concept maps should also scenarios that implications of for decision-making. Guide reflect on the potential present a dilemma. protecting human students to understand that consequences of a loss of agency throughout AI cannot replace human human agency at each step, Search engines, the design, thinking or intellectual for the individual and for online videos and provision and use development. society. supplemental of AI. Students will online learning understand what it CG4.1.1.2 Facilitate an Simulating an AI Act courses. means for AI to be understanding on the courtroom debate to human-controlled, necessity of exercising evaluate creators’ intents and what the sufficient human underlying prohibited AI consequences control over AI: Expose systems: Based on an age- could be when that students to real-world appropriate interpretation is not the case. scenarios and guide of the definition of AI students to experience the systems prohibited under consequences of human the European Union’s AI Act, oversight in controlling AI organize students to act as (e.g. weak regulations failing jury members to evaluate to prevent the design and selected examples of AI production of harmful AI systems that are due to be tools, the institutional use of prohibited under the AI AI to substitute for humans Act, deliberating on what when making high-stakes their creators’ intents and decisions, and the absence motivations may have been. of human validation of the Help students understand accuracy of AI outputs). how these systems can do Help students to grasp harm to humans, especially the necessity of exercising by undermining human human control over AI agency: for example, an 29  AI competency framework for students – Chapter 4: Specifications of AI competencies for students STUDENT CURRICULAR GOALS SUGGESTED LEARNING COMPETENCY (AI curricula or programmes PEDAGOGICAL METHODS ENVIRONMENTS of study should…) (Institutions and teachers (The following learning can consider and adapt the settings can be following learning methods.) provided and adapted.) Human- systems at regulatory, AI system may deploy centred institutional and individual techniques to weaken mindset levels to protect human a person’s awareness or safety, morality and dignity. purposefully impair their ability to make an informed CG4.1.1.3 Nurture critical decision. thinking on the dynamic relationship between Scenario-based human agency and understanding of human- machine agency: Expose controlled interaction students to real-world cases with AI: Select examples or in which AI can support scenarios in which AI tools human agency and human are used in workplaces or decision loops, support daily life, denoting what students to understand they and their human users how humans can properly are contributing to the interact with AI to enhance target task units. Encourage human capacities. Guide students to recognize the students in holding conflict- contribution AI can make based debates on dynamic in scenarios where human boundaries between human capabilities and intelligence agency and AI agency, may have limitations, revealing situations in underlining the importance which a certain extent of of using AI to enhance machine agency might human capacities while be needed (e.g. detecting ensuring human control. medical patterns that are Debating the dynamic undetectable for human boundary between doctors in diagnosing rare human agency and diseases, auto spell check machine agency: Based and autocorrection when on the real-world cases humans draft reports, auto of dilemmas surrounding captioning or automating humans’ reliance on machine video-production in the agency, encourage students development of course to conduct a debate on the materials, automatic changing roles humans and language translation, etc.). AI may play in AI-supported Foster a critical view that problem-solving and while human agency must decision-making processes. be upheld when using AI to Guide student to visualize make high-stakes decisions, the abstract boundaries the relationship between between human agency and human and machine agency machine agency in various in real-world situations contexts. should be examined based on the specific needs and contextual factors involved. 30  AI competency framework for students – Chapter 4: Specifications of AI competencies for students STUDENT CURRICULAR GOALS SUGGESTED LEARNING COMPETENCY (AI curricula or programmes PEDAGOGICAL METHODS ENVIRONMENTS of study should…) (Institutions and teachers (The following learning can consider and adapt the settings can be following learning methods.) provided and adapted.) Ethics of AI 4.1.2 Embodied ethics CG4.1.2.1 Illustrate Case studies on scenarios Unplugged dilemmas around AI and containing controversies learning settings Students are identify the main reasons around AI: Present age- and materials expected to be able behind ethical conflicts: appropriate real-world or including print to develop a basic Based on concrete AI tools, simulated scenarios, and stories or case understanding of guide students to surface guide students to surface studies, worksheets the ethical issues dilemma decisions that controversies surrounding and posters. around AI, and the individual or corporate the AI tools and their uses. potential impact creators need to make in the Discuss the main reasons Locally available of AI on human design and development of behind such ethical conflicts AI tools including rights, social AI (e.g. maximizing the scale and facilitate students to those available justice, inclusion, of data collection versus through mobile draw infographics or concept equity and climate protecting data ownership, phone apps. maps illustrating the core AI change within their recording users’ private ethical principles. Predownloaded or local context and data for the training of AI Individual or group recorded videos with regard to their models versus protecting reflection on the personal and other resources personal lives. They their privacy, promoting implications of ethical related to specific will understand, machine control to generate dilemmas: Engage students cases or scenarios and internalize profit versus guaranteeing in group discussion and that present a the following key the primacy of human opinion taking on ethical dilemma. ethical principles, agency, and prioritizing AI and will translate dilemmas that may arise Search engines, safety versus accelerating these in their from uses of AI in daily life online videos or the iteration of AI). Support reflective practices students to associate and learning in local contexts resources related to and uses of AI tools perspectives on these (e.g. whether large language case studies. in their lives and models should use the dilemmas with the reasons learning: data of local communities behind ethical conflicts in their training or not; Do no harm: around AI. to what extent AI has a Evaluating CG4.1.2.2 Facilitate negative environmental AI’s regulatory scenario-based impact or mitigates climate compliance and understandings of ethical change; how much of their potential to principles on AI and their privacy users should forego infringe on human personal implications: to exchange benefits of AI rights Offer students opportunities services). Guide students Proportionality: to discuss age-appropriate to present their opinions Assessing AI’s real-world cases around through age-appropriate benefits against the six core AI ethical formats such as essays, risks and costs; principles: (1) ‘do no posters, drawings or evaluating context- harm’, 2) proportionality, storyboards. appropriateness (3) non-discrimination, Searching for and (4) sustainability, (5) Non-discrimination: human determination, validating examples of Detecting biases ‘AI for the public good’: and (6) transparency and promoting Organize individual or and explainability. Guide inclusivity and group scoping of examples students to build a sustainability of AI tools or approaches knowledge framework on to the use of AI that the ethics of AI and practice 31  AI competency framework for students – Chapter 4: Specifications of AI competencies for students STUDENT CURRICULAR GOALS SUGGESTED LEARNING COMPETENCY (AI curricula or programmes PEDAGOGICAL METHODS ENVIRONMENTS of study should…) (Institutions and teachers (The following learning can consider and adapt the settings can be following learning methods.) provided and adapted.) Ethics of AI (understanding AI’s them in evaluating the AI support the public good, environmental and tools being used in their including promoting societal impacts) lives and schools. equity and inclusion for people with disabilities, Human CG4.1.2.3 Guide the preserving linguistic and determination: embodied reflection and