The “AI 101” video series was put together by the nonprofits Khan Academy, the International Society for Technology in Education (ISTE), Code.org, and Educational Testing Service, according to a news release. The first module, “How AI Works,” launched Aug. 15, with future sessions on demystifying AI for educators, transforming learning with AI, ensuring a responsible approach to AI, and bringing AI to the classroom to be released in the coming weeks.
Even though this initiative is aimed at helping K-12 teachers level the playing field in digital education nationwide, AI 101 is available to anyone who visits the Code.org website. The website says these videos will “demystify AI, explore responsible implementation, address bias, and showcase how AI-powered learning can revolutionize student outcomes.”
Hadi Partovi, founder and CEO of Code.org, said there is a pressing need to help educators understand generative AI.
“The release of ChatGPT has forever changed the educational landscape and will bring computer science into every classroom,” he said in a public statement. “Launching this free training underscores the importance of preparing teachers and students for the realities of a technology-driven society. As part of our mission to make computer science available to all K-12 students, we believe it’s paramount to support and train teachers with the latest technology advancements.”
In a public statement, Khan Academy founder and CEO Sal Khan called AI “the biggest disrupter facing education today,” which he said underscores the need for these resources.
“As part of our mission to provide a free, world-class education for anyone, anywhere, we believe it’s important to provide professional learning opportunities for K-12 teachers,” Khan said. “The AI 101 for Teachers series provides an easily digestible introduction to AI and sets the stage for continued professional development.”
In the “How AI Works” video, OpenAI Chief Technical Officer Mira Murati and Runway CEO Cristobal Valenzuela explain how generative AI employs large language models that are trained on everything available on the Internet. In turn, those AI technologies use the text they were trained on to generate new information for purposes like writing essays, having conversations or writing code.
“In fact, most of the magic of AI is based on very simple math concepts from statistics applied billions of times using fast computers. AI uses probabilities to predict the text that you want it to produce based on all the previous text that it has been trained on,” Murati says in the video. “This simple system might not sound even remotely intelligent, but as it builds up from here, you’d be surprised where it goes.”
Valenzuela says that while AI might seem like magic to the uninitiated, it can get things wrong.
“And when it gets things wrong, people ask, ‘Does a large language model actually have artificial intelligence?’” he says in the video. “Discussions about AI often spark philosophical debates about the meaning of intelligence. Some argue that a neural network producing words, using probabilities, doesn’t have real intelligence.”