MFPE 23 AI presentation.pptx
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This document provides an overview of artificial intelligence (AI) and its potential uses in education. It defines AI as computer systems that can perform tasks typically requiring human intelligence, such as visual perception, speech recognition, decision-making, and language translation. The document discusses major branches of AI including machine learning, natural language processing, computer vision, and robotics. It also covers current AI applications in education like AI-generated tutoring, lesson plans, and issues around algorithmic bias, privacy, accountability, and the changing roles of teachers and students with increased AI integration.
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MFPE 23 AI presentation.pptx
- 1. Exploring AI and Its Potential Role in Education Suzanne Reymer Montana State Library MFPE 2023 1
- 2. Objectives • Basic knowledge of AI ‒ What is it? ‒ What is it being used for? ‒ What are some common applications? • Some uses of AI in education ‒ Concepts – training and bias ‒ Tutoring ‒ Lesson plans • Ethics and Issues 2
- 3. What's your comfort level with AI? • Complete newbie – I've heard of it but know little about it • Know enough to be concerned – hear news reports and stories from students and educators • I've played around with it a bit but want to learn more • I've worked with it a lot and have knowledge and experience to share • I should be up there leading this workshop – not you 3
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- 6. In the News – October 16, 2023 6
- 7. What is AI? AI stands for Artificial Intelligence. It is a branch of computer science that aims to create intelligent machines that work and learn like humans AI involves the development of algorithms and computer programs that can perform tasks that typically require human intelligence such as visual perception, speech recognition, decision-making, and language translation - Chat GPT
- 8. AI Humor Break • Joke 1: Why did the computer go to art school? Because it wanted to learn how to draw a better "byte"! • Joke 2: Why do robots love to visit the beach? Because they love to surf the 'net! • Joke 3: Why was the computer cold at the office? It left its Windows open! Don't quit your day job for a career in stand up, Chat GPT! 8
- 9. Branches of AI • Machine Learning – the development of algorithms and statistical models that enable computer systems to learn from data without being explicitly programmed - ChatGPT, computer- generated images, voice assistants… • Natural Language Processing – program computers to process and analyze large amounts of natural language data – chatbots, machine translation • Computer Vision - enables computers to interpret and understand visual data from the world around them – image processing, facial recognition • Robotics 9
- 10. From Turing Test to Self Driving Cars 10
- 11. From Chess to Alexa 11
- 12. Algorithms An algorithm is a set of instructions that a computer program follows to complete a task • Recipe • Directions 12 https://www.bbc.co.uk/bitesize/topics/z3tbwmn/article s/z3whpv4
- 13. Chat GPT – Generative Pre-Trained Transformer Generative AI is a type of artificial intelligence technology that can produce various types of content including text, imagery, audio and synthetic data. It is used to create new content - a text, an image, even computer code - by learning how to take actions from past data. The recent buzz around generative AI has been driven by the simplicity of new user interfaces for creating high-quality text, graphics and videos in a matter of seconds. Given an initial text as prompt, it will produce text that continues the prompt. 13
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- 18. There is no one correct definitive answer from generative AI. Think of it as smart autofill. 18
- 19. Bing 19
- 21. Sometimes the results are less satisfying AKA the Importance of Prompts A drawing illustrating the evolution of computers General Dynamics robot dog dressed in giant spider costume 21
- 22. “Knowledge workers must know how to use generative systems and prompts to generate value going forward.” – Amy Webb 22
- 23. Different results from different models DALL-E Stable Diffusion 23
- 24. The Evolution of AI 24 ANI Artificial Narrow Intelligence ASI Artificial Super Intelligence AGI Artificial General Intelligence
- 25. Ethical Issues for Education • Privacy and Data Security: ‒ Data Collection ‒ Data Ownership • Bias and Fairness: ‒ Algorithmic Bias ‒ Equity • Transparency and Accountability: ‒ Explainability ‒ Accountability 25
- 26. More Ethical Issues • Teacher and Student Roles: ‒ Teacher Autonomy ‒ Student Autonomy • Depersonalization of Education: ‒ Loss of Human Connection • Ethics of Profiling and Targeting: ‒ Personalized Learning • Long-term Impact on Learning: ‒ Overreliance on AI • Accessibility and Inclusivity: ‒ Digital Divide 26
- 27. "And we should start teaching it in our schools—the essential techno-literary skills of learning how to learn, learning how to relearn, and becoming a lifelong learner." Kevin Kelly, co-founder Wired 27
Editor's Notes
- Does anyone recognize this image? HAL 9000 from 2001 A Space Odyssey. This is what comes to mind for many when we think about Artificial Intelligence: Open the pod bay doors, HAL. I’m sorry, Dave, I’m afraid I can’t do that. This is a lot of the fear about AI – when it goes rogue and works against us. Or it’s pursuing its own separate aims.
- Joke 1 is a play on words and relies on a pun to create humor. The joke goes: "Why did the computer go to art school? Because it wanted to learn how to draw a better 'byte'!" The humor in this joke comes from the double meaning of the word "byte." In the context of computers, a "byte" is a unit of digital information storage, typically consisting of 8 bits. However, the word "byte" also sounds like the word "bite," which is what someone might do when they eat or take a piece of something with their teeth. The joke creates an amusing image of a computer attending art school to improve its ability to "draw" (create) a better byte (bite), as if it were a physical object that could be improved through artistic skill. The humor comes from the blending of the digital concept of a byte with the physical act of biting, as well as the absurd idea of a computer attending art school.
- You’ll also hear the term large language models used in conjunction with machine learning and AI. Computers are fed large amounts of data which they “learn” from and rely on to formulate responses. NLP enables to interact with computers using our language rather than theirs.
- Who can describe the Turing Test? 1950 Alan Turing’s test – could a human interacting with a computer think it was human. Early work on AI was rule based and logic driven. Some wanted to go in other directions and base it on neural networks – how the human brain works. Limited computing power didn’t allow that until 1990s. I haven’t heard it said expressly but I imagine the Internet also played into this allowing computers to interact – network. Self driving cars are a really good example of the ultimate AI neural network – multiple sensors in each vehicle networking with sensors in other vehicles and with traffic signals, street/climate sensors. Taking in and processing data and reacting to changing information and conditions. Not only requires advanced AI but robust wireless Internet connectivity – 5G and better
- Part of the history of AI involved playing games such as chess. 1997 was when IBM’s Deep Blue first beat a chess champion – Garry Kasparov in a six game match. Computers have gone on to win at Jeopardy and Go. A big step came with AlphaZero that taught itself to play chess without any prior human knowledge or data. Many of us have had experience with AI in our daily lives from interactions with voice assistants like Alexa, Siri and Google to auto-correct and auto-complete functions on our phones. This is fairly obvious but AI is also increasingly in many other products – pretty much anything labeled “smart” has some AI components.
- I like this description from a BBC website designed for kids. I particularly like the directions example. There is an order and a process to follow. As any of us who’ve ever accidentally or on purpose gone the wrong when following map directions, we may have heard either an insistent “return to the route” follow the algorithm or a “recalculating” as a new algorithm is created. TikTok purportedly has some of the most sophisticated algorithms designed to keep you glued to their site. It looks for how long you look at a video, do you like it, follow the creator. It will keep feeding you more similar and different to hone the algorithm – continually recalculating.
- This is how Chat GPT defines itself. I will add my own – generative meaning it generates new content from an incredibly large corpus of data on which it has been pre-trained. It does does so by transforming the prompt it is given. One of the things to keep in mind is that it is not thinking or creating the text. It is simply looking for the most likely next word to follow based on the content it has in its memory. I’ve heard it described as intelligent auto-correct. As it’s not thinking or evaluating the text only looking at the likelihood of the next word in succession, it’s not assessing the correctness of the overall answer. If it has taken in a lot of text going in one direction, it is likely to go in that direction, whether or not that is objectively true. Hence, the possibility of bias depending on what has been fed into the database and/or the need to evaluate answers. There are numerous instances of it confidently producing an entirely wrong answer. This is known as an hallucination.
- Each Chat GPT search currently costs around $.02. Those costs will be going down as computing power increases.
- Note I did have to modify my request to AI image generators to get the results I wanted. One of the things I like about Bing is they provide some sources.
- These are a couple of the AI generated images that attracted a lot of attention in March. One of the fun games to play with AI generated images is what’s wrong with the image. There’s almost always some bits that are off. And these are good tells that the image isn’t authentic.
- These were a couple of my fails with Dall-E. I’m not sure what the first one is. I had in mind a variation on the classic evolution of man illustration. The second one just can’t be unseen. But good prompts are key. Often you can refine the image by refining the prompts.
- We’re not teaching these tools. We’re banning them.
- The prompt was “a realistic image of a white cat in a life jacket going head first down a water slide at a water park”
- Narrow is basically what we have today: Siri by Apple, Alexa by Amazon, Google Home Assistant (other virtual assistants), Email Spam Filters, Facial Recognition, Speech Recognition/Translation Software, Google Search, IBM Watson, Content Recommendation Systems (Netflix, Youtube, Amazon, online shopping), Self-Driving Cars, Drone Robots They’re capable of learning but they are applied to specific functions and don’t extend beyond. AGI is science fiction: Ironman’s Jarvis, Her, HAL from 2001 A Space Odyssey, AI programs from The Matrix, The Terminator, Data from Star Trek Capable of human-like cognitive processes ASI – self-improving, surpassing human intelligence, the Singularity