In this episode, Rob and Jared explore the origins of AI and how they led to ChatGPT. They discuss how AI’s continued growth has led to innovative tools as well as potential challenges in education. Contact us at [email protected] with any questions. You can also visit our blog at cedarville.edu/focusblog for additional resources. We would love to get your feedback!  Please fill out our survey to help improve our podcast and serve you better. 

This episode sets the stage for our summer series exploring ChatGPT. Our conversation begins with how the web has changed: Web 1.0, the internet's ”Stone Age,” featured static pages and one-sided conversations. Web 2.0, the ”Renaissance,” brought interactive pages; while Web 3.0 offered machine-readable, interoperable, and decentralized information.

AI's timeline began in 1950 with the Turing Test, measuring machine intelligence. In 1956, John McCarthy introduced the term "Artificial Intelligence" at the Dartmouth Conference. The "Golden Years" of AI (1957-1974) saw the first AI programs and labs. The first and second AI winters (1969, 1973-1980) were marked by decreased funding and interest due to criticism and failed machine translation, respectively. AI resurgence happened with the advent of expert systems (1980-1987), but another winter followed due to their market collapse (1987-1993). 

Important AI milestones include Deep Blue beating a world chess champion in 1997, IBM's Watson winning Jeopardy in 2011, chatbots passing the Turing Test in 2014, and the release of GPT-3 in 2020.

Educational AI has also made significant strides. An early example of ed-tech with AI capability is PLATO in 1963. That early technology has adapted to include automated essay grading. Tools like Gradescope and E-rater utilize algorithms to provide feedback on student essays, saving teachers’ time and giving students more immediate feedback. Personalized learning paths like OpenSimon use student data to provide real-time, personalized feedback based on student performance and behavior. Intelligent tutoring systems adapt to the learning needs of individual students based on their performance and behavior exemplified by Jill Watson, augmenting education through personalized, real-time feedback.

ChatGPT contributed to this description.