Milestone #1 Slide Deck
Delve into the world of Artificial Intelligence (AI) and Machine Learning (ML) as they impact our daily lives. Explore key concepts, conduct research, and work with Google's Teachable Machine to train and analyze data. The project aims to foster a foundational understanding of AI/ML and how biases can affect outcomes, culminating in a group discussion and presentation of findings.
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Presentation Transcript
Milestone #1 Slide Deck Let s get started!
Introduction Artificial Intelligence (AI) and Machine Learning (ML) have permeated just about every aspect of our daily lives. ML, in particular, guides everything from e-mail spam filters to medical diagnoses. Having a working knowledge of what AI and ML are and how they can be affected by bias is extremely important. In this project, you will do research into basic AI/ML and apply ML concepts via Google s Teachable Machine.
Brainstorm! In just a second, I m going to ask you to brainstorm the answers to two questions. The goal is not for you to be right, but just to start thinking about two concepts that are central to the project (we ll refine your answers later). Without looking anything up, write down your answers to the questions; if you don t know the answer, take your best guess. Quick tip: both questions ask about concepts with two words. If you don t know the whole term, try to define each word separately and combine the definitions. Ready for the questions?
Brainstorm! Without looking anything up, write down your answers to the following: What is artificial intelligence? What is machine learning? Remember, it s OK if you can t define either of the terms; try to define each word separately and combine the definitions. As an example: try to define artificial first, then intelligence, and combine the two definitions
Just for now. We ll take a deep dive into artificial intelligence and machine learning in this project but, for now, know that....Machine Learning (ML) is a subset of Artificial Intelligence (AI). Artificial Intelligence (AI) Machine Learning (ML)
Just for now. ...know that if you ve used any of the following, you have been helped by AI/ML: Social Media E-mail Automated maps (e.g., Google Maps) Siri/Alexa Netflix ...and a few others we ll discuss later...
In This Project... You will: Conduct research on key concepts in AI/ML in preparation for a group discussion, Get familiar with Google s Teachable Machine and Work with a partner to: train the Teachable Machine on a set of data of your choosing. analyze the results of working with the Teachable Machine, and present your findings.
The Final Product Will Be... Answers to the basic research questions, A discussion of your group s approach with the Teachable Machine, and A presentation that captures both. The audience for the final presentation will be a group of visitors. However, you will present to your peers in the interim to get practice and feedback.
What is Googles Teachable Machine? In this project, we ll be working with Google s Teachable Machine. I want you to take a sneak peak at it, to see what it does, and jot down some of your initial thoughts. For the next three minutes, visit the link below, take a look at the website, and jot down what you learn and what you think about the tool in your notes: https://teachablemachine.withgoogle.com/ This is just a sneak peak so be sure to stop when I call time... ready set go!
Keep in mind... The driving question for this project is What is Google s Teachable Machine and how can I unlock its power? Over the course of the project, you will become more familiar with AI/ML and apply your knowledge via the Teachable Machine. Your final product will be a presentation about your research and learning process and the answers you discovered to your classmates and, ultimately, a group of visitors.
Milestones #4: Student teams execute their Teachable Machine plan, train it on data of their choice, and document their experience. Teams then make plans for a future project and begin drafting their presentations. #1: Student is introduced to the project, presented with the driving question, introduced to a research question guide, and invited to start generating their own set of need to know questions (NTKs). #2: Student addresses the question guide and discusses their preliminary findings with the class. #3: Student gets a more in-depth understanding of both ML and Google s Teachable Machine, gets in a team, and collectively develops a plan for Google s Teachable Machine. #5: Student teams share what they ve learned about AI, ML, and the Teachable Machine along with their results to visitors.
Looking at the Milestones, what are your questions? Problem solving is the process of being at a start state, having an idea about the goal state, and developing a process to navigate from one to the other. A key factor that can drive the problem solving process is being aware of the questions you have and actively working, researching, and exploring to answer those questions -one at a time. Given what you know now about about the project, what are your thoughts? What are your questions? Jot those down!
Lets Discuss Expectations Work actively during the research phase and participate in discussion Keep track of questions that arise as you conduct the project; these are considered Need To Know (NTK) questions Work well with your partner to identify your plan for working with the Teachable Machine (you ll work independently at first and then with a partner later) Deliver and receive critique gracefully Participate in the collaborative development of the presentation Deliver the presentation along with your partner
A Note About Your Learning Experience The skills exercised in this project include: conducting research to gain foundational understanding applying a tool to explore a new concept Each of these skills are quite valuable in the real world. It s early in the process but what questions do you have about moving forward? What do you need to feel confident about the project?
Research Question Discussion In general, knowing how to explore interesting questions via self-guided research is an important skill. We will get some practice applying that skill in this project. The research questions (see your handout) were designed to help you build foundational knowledge about AI and ML. We will take a brief look at the questions for now (next slide), just so you can get familiar with them; we will explore them in depth shortly. You will be asked to find answers on the web, cite your sources, and rephrase your answers in your own words.
Now, Lets Start Working on NTKs What do you already know about artificial intelligence and/or machine learning? What questions were sparked from your three-minute overview of the Teachable Machine? What do you need to learn in order to use/apply the Teachable Machine? What questions do you have about what you need to have or know in order to complete this project?
