Artificial Intelligence Ethics Guidelines for K-12 Education: A Review of the Global Landscape

2021 ◽  
pp. 24-28
Author(s):  
Cathy Adams ◽  
Patti Pente ◽  
Gillian Lemermeyer ◽  
Geoffrey Rockwell
Keyword(s):  
Artificial Intelligence ◽  
Ethics Guidelines ◽  
K 12

Europe

2020 ◽  
pp. 649-666
Author(s):  
Andrea Renda
Keyword(s):  
Artificial Intelligence ◽  
Digital Technology ◽  
Policy Framework ◽  
Expert Group ◽  
Ethical Guidelines ◽  
Ethical Implications ◽  
Strong Focus ◽  
Ethics Guidelines ◽  
Definition Of ◽  
High Level

This chapter assesses Europe’s efforts in developing a full-fledged strategy on the human and ethical implications of artificial intelligence (AI). The strong focus on ethics in the European Union’s AI strategy should be seen in the context of an overall strategy that aims at protecting citizens and civil society from abuses of digital technology but also as part of a competitiveness-oriented strategy aimed at raising the standards for access to Europe’s wealthy Single Market. In this context, one of the most peculiar steps in the European Union’s strategy was the creation of an independent High-Level Expert Group on AI (AI HLEG), accompanied by the launch of an AI Alliance, which quickly attracted several hundred participants. The AI HLEG, a multistakeholder group including fifty-two experts, was tasked with the definition of Ethics Guidelines as well as with the formulation of “Policy and Investment Recommendations.” With the advice of the AI HLEG, the European Commission put forward ethical guidelines for Trustworthy AI—which are now paving the way for a comprehensive, risk-based policy framework.

scholarly journals Sustainable Curriculum Planning for Artificial Intelligence Education: A Self-Determination Theory Perspective

2020 ◽  
Vol 12 (14) ◽  
pp. 5568 ◽  
Author(s):  
Thomas K.F. Chiu ◽  
Ching-sing Chai
Keyword(s):  
Artificial Intelligence ◽  
Curriculum Design ◽  
Teaching Experience ◽  
Self Determination Theory ◽  
Curriculum Planning ◽  
Self Determination ◽  
Structured Interviews ◽  
Theoretical Frameworks ◽  
Intelligence Education ◽  
K 12

The teaching of artificial intelligence (AI) topics in school curricula is an important global strategic initiative in educating the next generation. As AI technologies are new to K-12 schools, there is a lack of studies that inform schools’ teachers about AI curriculum design. How to prepare and engage teachers, and which approaches are suitable for planning the curriculum for sustainable development, are unclear. Therefore, this case study aimed to explore the views of teachers with and without AI teaching experience on key considerations for the preparation, implementation and continuous refinement of a formal AI curriculum for K-12 schools. It drew on the self-determination theory (SDT) and four basic curriculum planning approaches—content, product, process and praxis—as theoretical frameworks to explain the research problems and findings. We conducted semi-structured interviews with 24 teachers—twelve with and twelve without experience in teaching AI—and used thematic analysis to analyze the interview data. Our findings revealed that genuine curriculum creation should encompass all four forms of curriculum design approach that are coordinated by teachers’ self-determination to be orchestrators of student learning experiences. This study also proposed a curriculum development cycle for teachers and curriculum officers.

Artificial Intelligence in Education

2021 ◽  
pp. 256-277
Author(s):  
Rashmi Khazanchi ◽  
Pankaj Khazanchi
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Pedagogical Practices ◽  
Student Centered ◽  
Tutoring Systems ◽  
Artificial Intelligence In Education ◽  
K 12 ◽  
Insight Into

Current educational developments in theories and practices advocate a more personalized, student-centered approach to teach 21st-century skills. However, the existing pedagogical practices cannot provide optimal student engagement as they follow a ‘one size fits all' approach. How can we provide high-quality adaptive instructions at a personalized level? Intelligent tutoring systems with embedded artificial intelligence can assist both students and teachers in providing personalized support. This chapter highlights the role of artificial intelligence in the development of intelligent tutoring systems and how these are providing personalized instructions to students with and without disabilities. This chapter gives insight into the challenges and barriers posed by the integration of intelligent tutoring systems in K-12 classrooms.

scholarly journals Envisioning AI for K-12: What Should Every Child Know about AI?

2019 ◽  
Vol 33 ◽  
pp. 9795-9799 ◽  
Author(s):  
David Touretzky ◽  
Christina Gardner-McCune ◽  
Fred Martin ◽  
Deborah Seehorn
Keyword(s):  
Artificial Intelligence ◽  
Science Teachers ◽  
Working Group ◽  
National Standards ◽  
National Guidelines ◽  
Call To Action ◽  
The Public ◽  
Online Resource ◽  
Teachers And Students ◽  
K 12

The ubiquity of AI in society means the time is ripe to consider what educated 21st century digital citizens should know about this subject. In May 2018, the Association for the Advancement of Artificial Intelligence (AAAI) and the Computer Science Teachers Association (CSTA) formed a joint working group to develop national guidelines for teaching AI to K-12 students. Inspired by CSTA's national standards for K-12 computing education, the AI for K-12 guidelines will define what students in each grade band should know about artificial intelligence, machine learning, and robotics. The AI for K-12 working group is also creating an online resource directory where teachers can find AI- related videos, demos, software, and activity descriptions they can incorporate into their lesson plans. This blue sky talk invites the AI research community to reflect on the big ideas in AI that every K-12 student should know, and how we should communicate with the public about advances in AI and their future impact on society. It is a call to action for more AI researchers to become AI educators, creating resources that help teachers and students understand our work.

SELF-IMPOSED ETHICAL GUIDELINES FOR AI IN EDUCATION

2020 ◽  
Vol 1 ◽  
Author(s):  
Anri Leimanis
Keyword(s):  
Artificial Intelligence ◽  
The Self ◽  
Ethical Principles ◽  
Educational Institutions ◽  
Public Agencies ◽  
Ethical Guidelines ◽  
Ai Ethics ◽  
Global Discourse ◽  
The Common ◽  
Ethics Guidelines

Advances in Artificial Intelligence (AI) applications to education have encouraged an extensive global discourse on the underlying ethical principles and values. In a response numerous research institutions, companies, public agencies and non-governmental entities around the globe have published their own guidelines and / or policies for ethical AI. Even though the aim for most of the guidelines is to maximize the benefits that AI delivers to education, the policies differ significantly in content as well as application. In order to facilitate further discussion about the ethical principles, responsibilities of educational institutions using AI and to potentially arrive at a consensus concerning safe and desirable uses of AI in education, this paper performs an evaluation of the self-imposed AI ethics guidelines identifying the common principles and approaches as well as drawbacks limiting the practical and legal application of the policies.

scholarly journals Artificial intelligence ethics guidelines for developers and users: clarifying their content and normative implications

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mark Ryan ◽  
Bernd Carsten Stahl
Keyword(s):  
Artificial Intelligence ◽  
Large Degree ◽  
Theoretical Understanding ◽  
Content Type ◽  
Practical Action ◽  
Ai Ethics ◽  
Guidance Documents ◽  
Ethics Guidelines ◽  
Degree Of Convergence ◽  
Normative Implications

Purpose The purpose of this paper is clearly illustrate this convergence and the prescriptive recommendations that such documents entail. There is a significant amount of research into the ethical consequences of artificial intelligence (AI). This is reflected by many outputs across academia, policy and the media. Many of these outputs aim to provide guidance to particular stakeholder groups. It has recently been shown that there is a large degree of convergence in terms of the principles upon which these guidance documents are based. Despite this convergence, it is not always clear how these principles are to be translated into practice. Design/methodology/approach In this paper, the authors move beyond the high-level ethical principles that are common across the AI ethics guidance literature and provide a description of the normative content that is covered by these principles. The outcome is a comprehensive compilation of normative requirements arising from existing guidance documents. This is not only required for a deeper theoretical understanding of AI ethics discussions but also for the creation of practical and implementable guidance for developers and users of AI. Findings In this paper, the authors therefore provide a detailed explanation of the normative implications of existing AI ethics guidelines but directed towards developers and organisational users of AI. The authors believe that the paper provides the most comprehensive account of ethical requirements in AI currently available, which is of interest not only to the research and policy communities engaged in the topic but also to the user communities that require guidance when developing or deploying AI systems. Originality/value The authors believe that they have managed to compile the most comprehensive document collecting existing guidance which can guide practical action but will hopefully also support the consolidation of the guidelines landscape. The authors’ findings should also be of academic interest and inspire philosophical research on the consistency and justification of the various normative statements that can be found in the literature.

scholarly journals Actionable Principles for Artificial Intelligence Policy: Three Pathways

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Charlotte Stix
Keyword(s):  
Artificial Intelligence ◽  
Development Process ◽  
Stakeholder Participation ◽  
Expert Group ◽  
Governmental Policy ◽  
Ai Ethics ◽  
Ethics Guidelines ◽  
Multi Stakeholder ◽  
High Level

AbstractIn the development of governmental policy for artificial intelligence (AI) that is informed by ethics, one avenue currently pursued is that of drawing on “AI Ethics Principles”. However, these AI Ethics Principles often fail to be actioned in governmental policy. This paper proposes a novel framework for the development of ‘Actionable Principles for AI’. The approach acknowledges the relevance of AI Ethics Principles and homes in on methodological elements to increase their practical implementability in policy processes. As a case study, elements are extracted from the development process of the Ethics Guidelines for Trustworthy AI of the European Commission’s “High Level Expert Group on AI”. Subsequently, these elements are expanded on and evaluated in light of their ability to contribute to a prototype framework for the development of 'Actionable Principles for AI'. The paper proposes the following three propositions for the formation of such a prototype framework: (1) preliminary landscape assessments; (2) multi-stakeholder participation and cross-sectoral feedback; and, (3) mechanisms to support implementation and operationalizability.

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