Official regulations on AI

TT
by to-teach Team
9 pagesMiddle Schoolnon-subject specific content, Sustainable Development Goals (SDG), Politics
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Description

Objective: The worksheet aims to teach learners about the official regulations governing artificial intelligence (AI). The focus is on the risk classification of AI applications, the fundamental rights of citizens and the balance between innovation and protection.



Contents and methods: The first phase of the worksheet serves as a warm-up and uses the method of joint idea gathering. The information text introduces the topic and explains key concepts such as risk assessment, transparency and data security. The methods include text comprehension by selecting the correct statement, classifying specific AI examples with justification, and reflective and creative forms of work such as open questions and designing a poster on the importance of AI regulation.


Competencies:

  • Risk assessment: Ability to classify AI applications according to their potential risk to fundamental rights and security.
  • Critical thinking: Weighing up the need for regulation in the context of innovation and risk protection.
  • Communication: Formulating a reasoned opinion on AI regulation.


Target group and level: Years 8–10 (middle school)


ESD:

  • 9: Industry, innovation and infrastructure: The Act aims to promote the responsible development of AI and maintain a balance between innovation and risk protection.
  • 16: Peace, justice and strong institutions: The main purpose of the regulation is to protect the fundamental rights of citizens and create a uniform legal framework for AI technologies.

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Objective: This worksheet provides an in-depth understanding of the technical fundamentals and ethical implications of artificial intelligence at the upper secondary level. The aim is to go beyond mere application and understand the underlying mechanisms (such as neural networks and machine learning) and critically reflect on their social implications.


Content and methods: The content covers fundamental technical concepts of artificial intelligence such as machine learning, deep learning, and neural networks, the distinction between weak and strong AI, and the analysis of everyday digital applications according to criteria such as data volume, algorithms, and learning ability. This is supplemented by practical case studies on personalized learning systems and ethical and social issues such as bias, responsibility, and the impact on learning and creativity. The methods include technical term explanations, comparative classification tasks, scenario-based case analyses, multi-perspective role-plays from different points of interest, and stimulating discussion and position exercises in the classroom, in which learners justify and reflect on their attitudes.


Competencies:

  • Technical expertise: Confident use of technical terms such as algorithms, training data, and artificial neurons.
  • Analytical skills: Ability to identify the role of training data and bias in AI models.
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Target group and level: From grade 10 onwards

non-subject specific content