Aimed at language educators seeking clarity, practical insights, and critical reflections in the rapidly changing AI landscape, the Opening AI for Language Learning (OAILL) podcast explores the evolving intersection of linguistics, pedagogy, and AI in language teaching and learning. Initiated by the Language and Applied Research Center at San Diego State University (SDSU-LARC), it features hosts Mat Schulze, Professor of German and Director of SDSU-LARC, and Phil Hubbard, Senior Lecturer Emeritus at the Stanford University Language Center, longtime colleagues with decades of experience in technology for language education. In place of the all-too-common hype surrounding AI, they offer conversations in which they and occasional guests share their research and practice-informed perspectives, commentaries on others’ work, and their own professional and personal AI experiences. We are grateful for the support for Opening AI for Language Learning by the Language and Applied Research Center at San Diego State University and the Southern Area International Languages Network – SAILN – which is part of the California World Languages Project. Our producer and editor is Chris Brown. Mari Ocando Finol is the production coordinator of OAILL . Our music was composed by Tillmann Spiegl. Live conversations are moderated and the podcast is promoted by Shahnaz Ahmadeian. Evan Rubin is our publicist. Episodes drop on Tuesday every 2 weeks. And remember: Artificial intelligence is no substitute for natural ignorance. Links: Phil Hubbard: https://web.stanford.edu/~efs/phil/ Mat Schulze: https://pantarhei.press/mat/ The PantaRhei.press blog about OAILL: https://pantarhei.press/oaill/ The SAILN website about OAILL: https://larc.sdsu.edu/sailn/oaill
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Signup to Generate a PitchAimed at language educators seeking clarity, practical insights, and critical reflections in the rapidly changing AI landscape, the Opening AI for Language Learning (OAILL) podcast explores the evolving intersection of linguistics, pedagogy, and AI in language teaching and learning.
Recent episodes include "017 AI detectors do not work" (27 October 2026, 32 minutes), "016 Good (Slow) AI is excellent" (13 October 2026, 26 minutes), and "Teaching with AI: 2 times 3 takeaways" (29 September 2026, 30 minutes).
Opening AI for Language Learning publishes roughly every two weeks, with episodes averaging 33 minutes.
Booking probability for Opening AI for Language Learning is 29%, and the host is rated Selective on guests. Opening AI for Language Learning requires a Pod Score of 80 or higher. Opening AI for Language Learning's contact route on record: verified email.
The strongest fits for Opening AI for Language Learning are Educational Support Services. Opening AI for Language Learning has an education audience.
Opening AI for Language Learning is an education podcast.
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Episode #17
In this episode, Mat and Phil continue to explore Sam Illingworth’s Slow AI , this time turning their attention to AI detectors. Beyond the question of whether AI detectors work, the hosts discuss the technical, ethical...
Episode #16
When should you use AI, and when should you leave it alone? In today’s episode, we dig into the central question of Sam Illingworth’s book Slow AI: Know When to Use AI and When to Leave it Alone , exploring what it...
Episode #15
Mat and Phil look back to look forward: What can the history of language teaching teach us about its future with AI? If generative AI represents something fundamentally new, does responding to it require leaving behind...
Episode #14
How can language teachers keep up with AI when the technology itself keeps changing? And how can teacher educators prepare future teachers for a landscape that may look very different just a few years from now? Drawing...
Episode #13
What does it mean to understand a language? Today’s generative AI tools can produce remarkably convincing linguistic forms, but can these systems understand the language they produce? In today’s episode, Mat and Phil...
Episode #12
What can generative AI do for language teaching and learning—and where does it fall short? Mat and Phil beam us back to Oxford, Ohio, for Part 2 of their conversations from the 2026 CALICO Conference, exploring AI for...
Episode #11
What are researchers learning about the role of generative AI in language teaching and learning? Recorded live at the 2026 CALICO Conference, Mat and Phil interview Robert Godwin-Jones, Jeffrey Maloney, Mingjun Tang...
Episode #10
Mat and Phil reflect on what their own Sustained Integrated Professional Development around GenAI looks like in practice. They discuss books, podcasts, courses, tools, and the conversations that are shaping their own...
Episode #9
What does it really mean for a machine to "think"? In this episode, Mat and Phil explore the life and legacy of pioneering mathematician Alan Turing, whose work laid the foundation for modern computing and artificial...
Episode #8
Exploring two contrasting perspectives on AI in education by Andreas Horn and Emily Bender, Mat and Phil reflect on AI’s promises and pitfalls, what artificial intelligence really means, and how language educators can...
Episode #7
Mat and Phil welcome their first-ever guest, Glenn Stockwell, to discuss professional development, learner training, and the ethical, legal, and policy challenges of generative AI in language education. The conversation...
Episode #6
<p>In this episode, Phil reports to Mat on his adventures at the TESOL 2026 Convention in Salt Lake City, March 24-27. Phil talked with exhibitors and attended as many AI-focused presentations, panels, and posters as he...
<p>In this episode, Mat and Phil discuss a book chapter by Glenn Stockwell, in which he writes about professional development and learner training for AI, highlighting the importance of ongoing reflection, learning...
<p>Language teachers can build their AI competence through the seven guiding principles of Sustained Integrated Professional Development. From starting small to taking a learner’s perspective, from reflecting critically...
<p>Mat and Phil return with six additional knowledge areas and skills that language teachers need to navigate AI thoughtfully, including course and lesson creation, assessment, and student misconduct, highlighting the...
<p>Learning about GenAI? Mat and Phil talk about the first four (of ten) knowledge areas and skills language teachers should aim to have now: prompting, ethics, chatbots, and translation. Combining practical examples...
Episode #1
<p>What is a large language model (LLM), actually? How do these systems work? Why can they feel like human conversation partners, and why is that perception misleading? Mat and Phil open the podcast by answering these...
Recent guests on Opening AI for Language Learning. Study who booked and why before you pitch.
Speakology AI
Xi'an Jiaotong-Liverpool University
UC Santa Barbara
Ohio University
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