AI and IoT in everyday life

• This module will explore AI and its applications in everyday life with the goal of helping teachers understand and explore AI in the classroom, using examples and the Internet of Things (IoT).
• Teachers will find information about AI, its applications, examples, suggestions and learning objectives.
• The module introduces AI and IoT through the lens of the 5 Big Ideas proposed by the AI4K12 initiative, specifically focusing on Societal Impact.

Glossary - Key notions and concepts

• AI combines computer science and robust datasets to enable problem-solving.
• AI involves computer systems performing tasks requiring human intelligence like visual perception, speech recognition, decision-making, and language translation.
• A robot is an automatically operated machine replacing human effort but not necessarily resembling humans.
• Capacity-based AI is categorized into artificial narrow intelligence, artificial general intelligence, and artificial superintelligence, based on learning and knowledge application.
• Functionality-based AI is categorized by how an AI applies its learning to process data, respond to stimuli and interact.
• The AI4K12 project focuses on teaching AI in K-12 in the US, aligning AI education with the CSTA standards for computer science education.
• IoT uses computer tools to automate real-world processes to reduce human participation and enables computing devices to transfer information over a network.

Introduction to Artificial Intelligence (AI)

• AI is the ability of machines to simulate human intelligence using computer programs.
• AI focuses on developing algorithms and systems for tasks requiring human intelligence like reasoning, self-learning, problem-solving, pattern recognition, decision-making, and language understanding.
• Supervised AI learning involves a person providing information to the AI when faced with certain situations.
• Semi-supervised AI learning involves the programmer identifying images for the AI, which then classifies other images itself.
• Unsupervised AI learning involves the AI identifying patterns and differentiating images autonomously.

Types of Artificial Intelligence

• AI exists in various types with its own applications and challenges.
• AI is constantly evolving and investment is increasingly comprehensive.
• Classification of AI types depends on Capacity-based, Intelligence and Functionality.
• Artificial Narrow Intelligence (ANI) describes AI tools performing specific actions, like image recognition software, self-driving cars, and AI assistants like Siri or Alexa.
• Artificial General Intelligence (AGI) describes AI that can learn, think and perform tasks almost as a human being; like ChatGPT.
• Scientist believe when machines reach Artificial Superintelligence (ASI), that they will keep learning and be able to become stronger than humans.

AI Functionality

• AI can be sorted in four different types with regard to functionality:
• Reactive Machines react immediately to requests but cannot store any memory, used for filtering spam in email boxes.
• Limited Memory AI can store past data and make predictions.
• Theory of Mind refers to a model of AI that can pick up subtle emotions.
• Self-Aware marks AI that reaches singularity like Sophia (Hanson Robotics).

Application of Al in everyday life

• AI is present in our routine, from facial recognition to Netflix recommendations.
• AI is found various sectors such as healthcare, finance, education etc.
• Google uses AI algorithms (Voice and Image search, Translate, Maps).
• Apple's Siri or Amazon's Alexa allow interaction through natural language processing (NLP, Speech Recognition, Smart Device Integration).
• AI is present in the automotive industry with autonomous transportation (TESLA, Efficiency Optimization, Intelligent Navigation).
• AI helps in medical diagnoses and assist doctors in detecting anomalies.
• AI can adapt the contents and learning based needs (Khan Academy, Duolingo, Squirrel Al).
• One of the most recurrent uses of AI can be found in smart homes.

AI and the 5 Big Ideas

• The "Five Big Ideas" of AI were proposed by John Haugeland and summarize the concepts that make up AI.
• The 5 Big Ideas that have made the industry soar are
• Perception is where computers can perceive the world with sensors
• Representation & Reasoning in processing data, agents maintain representation.
• Learning is defined as computers holding the capability to learn from the various input.
• Natural Interaction means AI agents require knowledge to interact with humans naturally.
• Societal Impact means AI has both positive and negative impacts on society.

Societal Impact in Al

• AI has a significant impact on society in various areas and levels.
• Examples of AI use include automating repetitive tasks, health, medicine, autonomous systems, education, e-commerce, cyber security, and ethics.
• Societal Impact can be positive or negative due to biases in the data.

The Internet of Things and Artificial Intelligence

• IoT helps AI to process and create an appropriate response to an event.
• AI is essential to IoT.
• An example of contributions of AI to Iot is robots in manufacturing, Self-driving cars, Smart Thermostat Solutions.

Ethics in Artificial Intelligence

• Ethical concerns include fairness, data responsibility, privacy, climate degradation, threaten human rights, accountability, and technology misuse.
• When focusing on AI in education and child-rearing, it is a must to consider the potential of privacy invasion.
• Being able to rely on Al poses as an issue to students who can prevent the development of social, personal, communication, reasoning skills etc.