AI in Educational Robotics

• AI4STEM Curriculum focuses on the application of AI in educational robotics.
• It introduces the 5 Big Ideas in Artificial Intelligence using the Internet of Things (IoT) in STEM education.
• Date: 24.08.2023
• Project Number: 2022-1-FR01-KA220-SCH-000085611

Revision History

• DRAFT was created on 24.08.2023 by Sofia Sousa, Ana Barroca, and Joana Santos (SCHOLÉ).

Referenced Documents

• AI4STEM Proposal with ID 1 and Reference 2022-1-FR01-KA220-SCH-000085611

Module Introduction

• The module explores AI and its applications in everyday life.
• It helps teachers understand AI and the interaction between AI and the Internet of Things (IoT).
• Teachers can find information about AI, its applications, and examples for elementary and secondary school classrooms.
• The module explores how AI and IoT can be taught through the 5 Big Ideas (AI4K12 initiative).
• There is a focus on the 5th Big Idea, Societal Impact.

Glossary - Key Notions and Concepts

• Artificial Intelligence (AI): Combines computer science and datasets for problem-solving, performing tasks requiring human intelligence.
• Examples: visual perception, speech recognition, decision-making, and translation.
• Robot: An automatically operated machine that replaces human effort.
• Capacity-based AI: Categorized into Artificial Narrow Intelligence, Artificial General Intelligence, and Artificial Superintelligence.
• Functionality-Based AI: Categorized by how AI applies learning capabilities to process data and interact with the environment.
• AI4K12 project: Focused on teaching AI in K-12 in the US, aligning with CSTA standards for computer science education.
• Internet of Things (IoT): Uses computer tools to automate real-world processes, transferring information over a network.

Introduction to Artificial Intelligence (AI)

• AI simulates human intelligence using computer programs, making everyday products and services easier to use.
• AI focuses on developing algorithms and systems for tasks requiring human intelligence, such as reasoning, self-learning, problem solving, pattern recognition, decision-making, and understanding language.
• AI can learn in three different ways:
• Supervised: AI learns from a person who provides information.
• Semi-supervised: AI learns from a series of images with known categories.
• Unsupervised: AI identifies patterns and differentiates images autonomously.

Types of Artificial Intelligence

• AI exists in various types, each with its own applications and challenges.
• Classification of AI types depends on Capacity-based and Intelligence and Functionality-Based criteria.
• Capacity-based AI can be divided into three types of capabilities:
• Artificial Narrow Intelligence (ANI): Executes specific actions or commands.
• Example: image recognition software, self-driving cars, and AI assistants like Siri or Alexa.
• Artificial General Intelligence (AGI): Learns, thinks, and performs tasks almost like a human.
• Goal: create machines that can multitask and act in everyday life like human assistants.
• Artificial Superintelligence (ASI): Seen in science fiction movies; surpasses human intelligence through continuous learning.
  • Example: Ex Machina or I, Robot.
• Reactive Machines: Fundamental AI that reacts to requests but cannot store memory or learn from past experiences.
  • Example: filtering spam from email boxes and recommending movies on Netflix.
• Limited Memory: AI that stores past data and makes predictions, improving performance through built knowledge over time.
  • Example: chatbots and self-driving cars.
• Theory of Mind: AI that can pick up on emotions and act on them.
• Self-Aware: AI that reaches singularity, becoming independent and out of human control.
  • Example: Sophia (robot).

Task for the classroom - AI in the classroom

• Teachers show images of AI applications (robots, virtual assistants, facial recognition apps, self-driven cars, chatbot websites) and ask students what they know about them.
• Questions to ask:
• Do all these AIs work the same way?
• What are the differences? Why do they work differently?
• Students are separated into groups to classify the AIs, and teacher introduces the different types of AI and why.
• Learning Objectives:
• Discuss & understand what is AI.
• Understand types of AI.
• Discuss the similarities and differences in the types of AI.

Application of AI in Everyday Life

• AI is integrated into daily routines, like unlocking phones with facial recognition and receiving personalized recommendations.
• AI is used in various sectors:
• Healthcare
• Finance
• Manufacturing
• Transportation
• Entertainment
• Education.
• Search engines use AI algorithms for various functions such as voice and image search, translation, and maps.
• Virtual assistants such as Apple's Siri and Amazon's Alexa use natural language processing (NLP), speech recognition, and smart device integration.
• AI is used in autonomous transportation (TESLA), medical diagnoses, and educational platforms.
• Examples: Khan Academy, Duolingo, Squirrel AI.
• AI is commonly used in smart homes with AI thermostats and safety systems.

Task for the classroom - AI in everyday life

• Discuss with students how much they rely on AI.
• Questions to ask:
• Has AI made life easier?
• Do you have smart equipment at home? What does it do?
• Do we use any AI at school?
• Where there could be more AI?
• Learning Objectives:
• Identify how AI is part of daily routines.
• Discuss the use of AI in everyday life.
• Familiarize with having AI in our daily lives.

AI and the 5 Big Ideas

• The "Five Big Ideas" of AI were proposed by John Haugeland to summarize the key concepts of AI.
• The ideas provide an overview of the fundamental principles behind AI development.
• Perception: Computers can see and hear the world with sensors.
• Representation & Reasoning: Agents maintain representations of the world for reasoning.
• Learning: Computers can learn from various inputs; machine learning helps find patterns in data.
• Natural Interaction: AI agents require knowledge to interact with humans naturally.
• Societal Impact: AI has positive and negative impacts on society, requiring a balance between technology use and enhanced human interactions.

Societal Impact in AI

• AI has significant impacts across society, from the economy to daily lives.
• Examples:
• Automating repetitive tasks.
• Improving health and medicine.
• Improving safety in transport.
• Transforming education.
• Creating personalization in E-Commerce.
• Improving accessibility options for people with disabilities.
• Optimizing pattern detecting in Cyber Security.
• Ethical and privacy issues rise in terms of data collection/analysis.
• Public administration, risks prediction, and safety improvement in Government and Global decision-making.
• The Societal Impact of AI can be positive or negative due to biases in data while training the AI.

The Internet of Things and Artificial Intelligence

• IoT and AI are strongly connected; IoT helps AI process and respond to real-world events, meaning that AI is essential to IoT.
• Developers are asking to what extent AI can be taken.
• There are rule-based and more sophisticated AI.
• Example: Trigger switch in pressed, turn on light A or "If trigger switch is pressed, and it's dark, turn on light A”. This means that the AI would have to recognize not only the event (the button being pressed) but also the state (the darkness)
• AI can help IoT reduce the need for direct human participation.
• Since AI is improving/mimicking human skills, IoT developments should be closely monitored for new opportunities and symbiosis.
• Some examples of the interaction and contribution of AI to the IoT:
• Robots in Manufacturing: Making the manufacturing process better over time with implementation of sensors
• Self-driving Cars: They can predict behaviors with sensors and AI algorithms.
• Smart Thermostat Solution: Can manage the temperature automatically with AI in place.

Task for the classroom - Iot and AI

• Ask the students to think of examples where the two are used and describe what is the role of the IoT and the role of the AI.
• For instance:
• Smart parking system in an office or school, where the AI studies the movement of cars inside the park for some time.
• An healthy diet monitoring system that collects data of the choices each student makes daily.
• Objectives:
• Differentiate between IoT and AI.
• Identify examples of applications or industries that apply IoT and AI combined,
• Understand the role of both IoT and AI.

Ethics in Artificial Intelligence

• Ethical concerns related to AI:
• Fairness
• Data responsibility
• Privacy.
• Climate degradation
• Human rights
• Accountabilty
• Tech misuse
• Always take privacy into consideration.
• AI can prevent students from developing social/personal skills.

Task for the classroom - Ethics and AI

• Show the students some school equipment that is used in the classroom and ask students to describe the equipment.
• What are some of the benefits and drawbacks of these technologies?
• Define positive and negative aspect about the use of it and define some safe rules while using the equipment.
• Create an “Ethics in the classroom” anchor chart with suggestions.
• Learning Objectives:
• Describe at least one impact on society.
• Create at least one guiding principle.
• Gain conscience about the risk.
• Reflecting on the positive and negative aspects of AI.