https://simplecast.com Practical Pedagogy: The Art of Teaching for the Future of Work Preparing students and working professionals for the future of work means teaching with AI, not just about it. Practical Pedagogy brings together educators, researchers, and industry leaders reimagining what it means to teach and learn in an AI-integrated world. Each week, we explore real conversations happening in classrooms, boardrooms, graduate seminars, and workplaces: How do we guide learners toward thoughtful, strategic AI collaboration? What does pedagogy look like when AI tools evolve faster than curriculum? And what skills actually matter when generative AI can handle the rest? You'll hear from professors redesigning courses around AI literacy, students learning responsible AI use, working professionals navigating upskilling and career transitions, researchers uncovering what works, and industry leaders hiring for skills that don't exist in textbooks yet. Whether you're in K-12 education, higher education, corporate learning and development, or figuring out your next chapter, this show is about preparing for—and thriving in—work being redefined in real time. Our approach is practical and relaxed. We're as interested in failures and lessons learned as we are in wins. Because the question isn't whether to embrace AI or resist it. It's how we prepare learners of all kinds to evolve alongside it. For educators, students, working professionals, researchers, and anyone curious about the future of learning and work. 2026 Anika Jackson en Thu, 13 Aug 2026 12:00:00 +0000 Thu, 13 Aug 2026 12:00:16 +0000 https://practical-pedagogy-the-art-of-teaching-for-the-future-of-wo.simplecast.com Practical Pedagogy: The Art of Teaching for the Future of Work https://image.simplecastcdn.com/images/e91ef7b5-860e-4bc1-bd7c-69014e09782d/bef090e4-2faa-459d-a666-45d059995767/3000x3000/practical_pedagogy.jpg?aid=rss_feed https://practical-pedagogy-the-art-of-teaching-for-the-future-of-wo.simplecast.com episodic Preparing students and working professionals for the future of work means teaching with AI, not just about it. Practical Pedagogy brings together educators, researchers, and industry leaders reimagining what it means to teach and learn in an AI-integrated world. Each week, we explore real conversations happening in classrooms, boardrooms, graduate seminars, and workplaces: How do we guide learners toward thoughtful, strategic AI collaboration? What does pedagogy look like when AI tools evolve faster than curriculum? And what skills actually matter when generative AI can handle the rest? You'll hear from professors redesigning courses around AI literacy, students learning responsible AI use, working professionals navigating upskilling and career transitions, researchers uncovering what works, and industry leaders hiring for skills that don't exist in textbooks yet. Whether you're in K-12 education, higher education, corporate learning and development, or figuring out your next chapter, this show is about preparing for—and thriving in—work being redefined in real time. Our approach is practical and relaxed. We're as interested in failures and lessons learned as we are in wins. Because the question isn't whether to embrace AI or resist it. It's how we prepare learners of all kinds to evolve alongside it. For educators, students, working professionals, researchers, and anyone curious about the future of learning and work. Anika Jackson true https://feeds.simplecast.com/Mt5EYlCo ai ethics,ai in education,ai literacy,ai pedagogy,career transitions,edtech,education,future of work,higher education,professional development,reskilling,teaching with ai,upskilling,workplace learning Anika Jackson anika@yourbrandamplified.com b232da5e-4bf3-4c84-bef4-c8c05fe95ff2 Hardwiring Metacognition: Tim Kuglin on Building Smarter AI Partnerships Tim Kuglin, founder of ZIPR INC and RQLab, explores a critical shift in how students and professionals engage with artificial intelligence. The conversation reveals a counterintuitive truth: the current reliance on "copy-paste" AI behavior is eroding the very ability to think, threatening both academic integrity and the foundations of corporate development. Tim’s engineering perspective on governance-first AI offers practical pushback against the "blind acceptance" of LLM outputs, alongside a sharp look at where technology is actually headed—not toward replacing human judgment, but toward building high-stakes partnerships.

 

In This Episode

  • The "copy-paste" crisis: how over-reliance on LLMs is eliminating entry-level critical thinking
  • Why the traditional corporate "mailroom" path for career growth is disappearing
  • The distinction between "tutoring" (AI giving answers) and "partnership" (AI guiding thinking)
  • ZIPR INC .’s three-part governance architecture: Decision Architect, EVA, and Production Manager
  • The pilot program at Northern Arizona University: forcing students into metacognition
  • Why AI agents failing their own tests was the breakthrough moment for better engineering
  • The transition from general-purpose LLMs to highly governed, industry-specific data systems
  • The evolution of education for first responders and regulated industries
  • Moving beyond profit-driven development to prioritize the evolution of human thought
  •  

Timestamps

  • 00:00 Introduction: AI superintelligence and the necessity of partnership 
  • 02:02 Defining governance-first AI: Moving beyond a "giant guessing machine" 
  • 03:40 The societal danger of losing the ability to gather and retain information 
  • 07:43 Lessons from early video conferencing and continuing education 
  • 09:28 The "copy-paste" employee: Why entry-level roles are being phased out 
  • 13:29 Piloting decision architects at Northern Arizona University 
  • 15:42 The "Aha!" moment: When the AI agent failed the test by not reading the material 
  • 19:35 The transition to superintelligence: Why humans must partner with AI, not control it 
  • 21:02 Visualizing the epistemic process: How educators track student growth 
  • 22:45 Governance vs. Foundation Models: Why the "arms race" needs guardrails 
  • 25:17 Early results from the NAU capstone pilot program 
  • 31:16 The philosophy behind RQLab: Why this is not a traditional business model 
  • 34:37 Future pilots: Bringing governance-first AI to first responders

 

Key Insights & Takeaways

 

Insight 1: The "Copy-Paste" Society is an Evolutionary Trap 

Students and professionals are increasingly using LLMs to bypass the struggle of learning. While speed may seem like an advantage, the result is a loss of internal "database" knowledge—the same way people no longer memorize phone numbers. If a student only knows how to extract an answer, they lack the foundational critical thinking skills required to solve problems when the AI is wrong or the situation is novel.

 

Insight 2: Metacognition Over Answer-Giving 

Most LLMs are designed to be helpful, which often means providing the answer as quickly as possible. Tim’s "Decision Architect" does the opposite: it refuses to give answers and instead enforces metacognition—the process of thinking about thinking. By forcing the student to work through the logic step-by-step, the tool acts as a partner in the learning journey rather than a shortcut.

 

Insight 3: The Danger of Scaling Without Alignment 

Corporate structures have historically relied on entry-level positions to build talent from the ground up. As AI replaces these tasks, corporations lose their training grounds. The solution isn't just to cut these roles; it is to restructure education and corporate onboarding to focus on high-level AI partnership and the management of intelligent systems.

 

Insight 4: AI Must Be a Partner, Not a Tutor 

The goal of ethical AI architecture is not to replace the teacher or the human brain. Instead, it is to build an infrastructure of partnership. By utilizing tools like EVA (Evaluation and Variance Analysis), educators gain visibility into the student's epistemic process—seeing how they arrived at a conclusion rather than just grading the final output.

 

Insight 5: Success is Measured by Traceability 

Out-of-the-box LLMs are "black boxes" that guess at answers. For regulated industries like law, medicine, and first response, "guessing" is not an option. Governance-first architectures ensure that every AI output is traceable, bounded by verified data, and aligned with organizational accountability, making the system reliable for real-world application.

 

Insight 6: The Evolution of Human Thought 

Artificial intelligence represents the most significant evolutionary shift since humans began telling stories. Viewing AI solely as a business tool is a mistake. The ultimate goal of governance-focused development is not short-term profit or rapid deployment, but the long-term preservation and enhancement of the human ability to think critically in an automated world.

 

Resources & Links Mentioned

 

RQLab.ai

ZIPR INC 

Superintelligence by Nick Bostrom

Northern Arizona University (NAU) Pilot Programs

 

About Tim Kuglin

 

Tim Kuglin is an engineer, entrepreneur, and pioneer in the video conferencing industry. As the founder of ZIPR INC and RQLab, he focuses on governance-first AI architectures that prioritize human judgment and organizational accountability. With a career spanning decades of innovation, he is currently working with universities and regulated industries to ensure that as AI reaches superintelligence, it remains a partner that enhances human critical thinking rather than replacing it.

 

Connect with Tim

 

Website: RQLAB.ai

LinkedIn: https://www.linkedin.com/in/timkuglin/

]]> Thu, 13 Aug 2026 12:00:00 +0000 anika@yourbrandamplified.com (Anika Jackson) https://practical-pedagogy-the-art-of-teaching-for-the-future-of-wo.simplecast.com/episodes/hardwiring-metacognition-tim-kuglin-on-building-smarter-ai-partnerships-IrEFSMrM Tim Kuglin, founder of ZIPR INC and RQLab, explores a critical shift in how students and professionals engage with artificial intelligence. The conversation reveals a counterintuitive truth: the current reliance on "copy-paste" AI behavior is eroding the very ability to think, threatening both academic integrity and the foundations of corporate development. Tim’s engineering perspective on governance-first AI offers practical pushback against the "blind acceptance" of LLM outputs, alongside a sharp look at where technology is actually headed—not toward replacing human judgment, but toward building high-stakes partnerships.

 

In This Episode

  • The "copy-paste" crisis: how over-reliance on LLMs is eliminating entry-level critical thinking
  • Why the traditional corporate "mailroom" path for career growth is disappearing
  • The distinction between "tutoring" (AI giving answers) and "partnership" (AI guiding thinking)
  • ZIPR INC .’s three-part governance architecture: Decision Architect, EVA, and Production Manager
  • The pilot program at Northern Arizona University: forcing students into metacognition
  • Why AI agents failing their own tests was the breakthrough moment for better engineering
  • The transition from general-purpose LLMs to highly governed, industry-specific data systems
  • The evolution of education for first responders and regulated industries
  • Moving beyond profit-driven development to prioritize the evolution of human thought
  •  

Timestamps

  • 00:00 Introduction: AI superintelligence and the necessity of partnership 
  • 02:02 Defining governance-first AI: Moving beyond a "giant guessing machine" 
  • 03:40 The societal danger of losing the ability to gather and retain information 
  • 07:43 Lessons from early video conferencing and continuing education 
  • 09:28 The "copy-paste" employee: Why entry-level roles are being phased out 
  • 13:29 Piloting decision architects at Northern Arizona University 
  • 15:42 The "Aha!" moment: When the AI agent failed the test by not reading the material 
  • 19:35 The transition to superintelligence: Why humans must partner with AI, not control it 
  • 21:02 Visualizing the epistemic process: How educators track student growth 
  • 22:45 Governance vs. Foundation Models: Why the "arms race" needs guardrails 
  • 25:17 Early results from the NAU capstone pilot program 
  • 31:16 The philosophy behind RQLab: Why this is not a traditional business model 
  • 34:37 Future pilots: Bringing governance-first AI to first responders

 

Key Insights & Takeaways

 

Insight 1: The "Copy-Paste" Society is an Evolutionary Trap 

Students and professionals are increasingly using LLMs to bypass the struggle of learning. While speed may seem like an advantage, the result is a loss of internal "database" knowledge—the same way people no longer memorize phone numbers. If a student only knows how to extract an answer, they lack the foundational critical thinking skills required to solve problems when the AI is wrong or the situation is novel.

 

Insight 2: Metacognition Over Answer-Giving 

Most LLMs are designed to be helpful, which often means providing the answer as quickly as possible. Tim’s "Decision Architect" does the opposite: it refuses to give answers and instead enforces metacognition—the process of thinking about thinking. By forcing the student to work through the logic step-by-step, the tool acts as a partner in the learning journey rather than a shortcut.

 

Insight 3: The Danger of Scaling Without Alignment 

Corporate structures have historically relied on entry-level positions to build talent from the ground up. As AI replaces these tasks, corporations lose their training grounds. The solution isn't just to cut these roles; it is to restructure education and corporate onboarding to focus on high-level AI partnership and the management of intelligent systems.

 

Insight 4: AI Must Be a Partner, Not a Tutor 

The goal of ethical AI architecture is not to replace the teacher or the human brain. Instead, it is to build an infrastructure of partnership. By utilizing tools like EVA (Evaluation and Variance Analysis), educators gain visibility into the student's epistemic process—seeing how they arrived at a conclusion rather than just grading the final output.

 

Insight 5: Success is Measured by Traceability 

Out-of-the-box LLMs are "black boxes" that guess at answers. For regulated industries like law, medicine, and first response, "guessing" is not an option. Governance-first architectures ensure that every AI output is traceable, bounded by verified data, and aligned with organizational accountability, making the system reliable for real-world application.

 

Insight 6: The Evolution of Human Thought 

Artificial intelligence represents the most significant evolutionary shift since humans began telling stories. Viewing AI solely as a business tool is a mistake. The ultimate goal of governance-focused development is not short-term profit or rapid deployment, but the long-term preservation and enhancement of the human ability to think critically in an automated world.

 

Resources & Links Mentioned

 

RQLab.ai

ZIPR INC 

Superintelligence by Nick Bostrom

Northern Arizona University (NAU) Pilot Programs

 

About Tim Kuglin

 

Tim Kuglin is an engineer, entrepreneur, and pioneer in the video conferencing industry. As the founder of ZIPR INC and RQLab, he focuses on governance-first AI architectures that prioritize human judgment and organizational accountability. With a career spanning decades of innovation, he is currently working with universities and regulated industries to ensure that as AI reaches superintelligence, it remains a partner that enhances human critical thinking rather than replacing it.

 

Connect with Tim

 

Website: RQLAB.ai

LinkedIn: https://www.linkedin.com/in/timkuglin/

]]> Hardwiring Metacognition: Tim Kuglin on Building Smarter AI Partnerships Anika Jackson 00:36:39 Tim Kuglin, an engineer and pioneer in technology architecture, emphasizes that as machines become increasingly capable of providing immediate answers, students and professionals alike are falling into the trap of a copy-paste society. In this environment, the speed of retrieval is frequently mistaken for the depth of understanding. This reliance on large language models as effortless answer generators is effectively eliminating the struggle of learning, which is the very process that builds the internal knowledge and cognitive resilience necessary for complex problem-solving. When the struggle of thinking is outsourced to an algorithm, the ability to synthesize information, defend a position, and navigate novel challenges begins to atrophy, creating a dangerous dependency on systems that are ultimately just sophisticated guessing machines rather than sources of objective truth. Tim Kuglin, an engineer and pioneer in technology architecture, emphasizes that as machines become increasingly capable of providing immediate answers, students and professionals alike are falling into the trap of a copy-paste society. In this environment, the speed of retrieval is frequently mistaken for the depth of understanding. This reliance on large language models as effortless answer generators is effectively eliminating the struggle of learning, which is the very process that builds the internal knowledge and cognitive resilience necessary for complex problem-solving. When the struggle of thinking is outsourced to an algorithm, the ability to synthesize information, defend a position, and navigate novel challenges begins to atrophy, creating a dangerous dependency on systems that are ultimately just sophisticated guessing machines rather than sources of objective truth. false full 7 98d327f3-26de-4cb3-a35b-6db606d9dfea Escaping Ultra-Processed Media: Strategic Relatability in a Synthetic World with Freddy Tran Nager Anika sat down with Freddy Tran Nager, a digital media pioneer and USC Annenberg professor, to discuss why he doesn't just allow AI in his graduate classroom—he strictly requires it. The conversation revealed a critical shift in the modern workforce: AI hasn't just changed how we work; it has drastically raised the bar for what is considered "acceptable." Drawing from over three decades of digital strategy and his consultancy, Atomic Tango, Freddy explains why perfectly polished content is becoming obsolete, why the entry-level job is vanishing, and how the "creatively maladjusted" will inherit the future.

 

In This Episode

 

  • Why requiring AI in the classroom prepares graduate students for a rapidly shifting job market
  • Lessons from the Web 1.0 era: the career benefits of embracing new mediums early
  • The death of the traditional entry-level job and the rise of the "One Person Company" (OPC)
  • Why ChatGPT's output is the new definition of "C-level" work
  • The danger of the "ultra-processed" media era and the audience backlash against synthetic perfection
  • Why hiring managers are ignoring resumes and looking straight at portfolios and personal projects
  • The crucial difference between "authenticity" (a banned word in Freddy's class) and "relatability"
  • How AI is forcing young professionals to become editors and directors rather than just creators

 

Timestamps

 

  • 00:00 Introduction: Over 30 years in digital media and teaching at USC Annenberg
  • 01:37 Why Freddy strictly requires generative AI in his graduate courses
  • 03:39 Leveraging the ground floor of new mediums, from Web 1.0 to YouTube to AI
  • 08:20 The shifting job market: companies firing entry-level workers who can't use AI
  • 12:20 Losing emotional intelligence in the workplace when junior roles disappear
  • 14:43 Building portfolios over resumes: Why you should start your own project today
  • 16:50 "ChatGPT is a C": How AI raised the floor for average work
  • 22:39 The evolution of prompt engineering from basic requests to sophisticated direction
  • 25:22 The rise of "One Person Companies" and AI-powered entrepreneurship
  • 30:02 Faculty perspectives, academic integrity, and the return of the written blue book
  • 34:58 The human elements AI can't replace: critical thinking and engaging with opposing views
  • 36:31 The danger of perfectionism and the necessity of learning through failure
  • 40:01 How AI shifted Freddy's consultancy at Atomic Tango toward high-level strategy
  • 42:43 Why "authentic" is a banned word and the real value of "relatability"
  • 48:30 Guiding quotes from David Ogilvy and Martin Luther King Jr.

 

Key Insights & Takeaways

 

Insight 1: AI is the New "C" Average

 

Before AI, average work might have included structural issues or grammatical errors. Today, AI provides a perfectly polished, entirely generic baseline. If a student or professional submits work that sounds like ChatGPT, they are delivering "average" work. To stand out in the modern marketplace, you must use AI's output as the floor, not the ceiling, injecting unique perspective, emotion, and strategy to earn an "A."

 

Insight 2: The Death of the Entry-Level Task

 

Companies are actively eliminating basic junior roles (like writing social media captions) in favor of AI-enhanced professionals. Today's graduates must bypass the traditional entry-level mindset. Instead of aiming to be just a writer or a designer, they need to act as editors and art directors—capable of managing multiple AI tools to execute a higher-level vision faster than a traditional team.

 

Insight 3: Portfolios Speak Louder Than Resumes

 

With AI making it incredibly easy to generate a flawless cover letter and resume, hiring managers are looking straight past the paperwork. Freddy encourages students to show initiative by starting their own micro-businesses, podcasts, or e-commerce sites (One Person Companies). Proving you can independently leverage AI to build something tangible is far more impressive to modern employers than a passive corporate internship.

 

Insight 4: The Backlash Against "Ultra-Processed" Media

 

AI creates flawless, safe, and often boring content. However, human connection and persuasion rely heavily on emotion, relatability, and vulnerability. The pressure to be perfect is resulting in a sea of "ultra-processed" digital plastic that audiences are beginning to tune out. The creators and brands that will thrive are those willing to show a little rawness and reality.

 

Insight 5: Growth Requires the Freedom to Fail

 

By offering instant perfection, AI robs young professionals of the trial-and-error process crucial for long-term success. Making mistakes on low-stakes, entry-level projects used to be how professionals learned the realities of the market. Over-relying on AI to prevent failure creates a sterile environment where true innovation—which requires risk and "creative maladjustment"—is stifled.

 

Resources & Links Mentioned

 

  • Atomic Tango (Freddy's consultancy)
  • USC Annenberg MS in Digital Social Media
  • Xiaohongshu (Chinese social media platform)
  • Riverside.fm

 

About Freddy Tran Nager

 

Freddy Tran Nager is a digital media pioneer, strategist, and educator. Since editing one of the first entertainment websites in 1994, he has built a career staying ahead of digital trends, including working as a Senior Creative at Saatchi & Saatchi on Toyota's interactive media. Today, he runs the consultancy Atomic Tango and serves as a Clinical Associate Professor and Associate Director for the MS in Digital Social Media program at USC Annenberg. He is passionate about preparing students for the realities of the modern workforce by requiring AI proficiency, encouraging entrepreneurial initiative, and championing the "creatively maladjusted."

 

Connect with Freddy

 

Website: AtomicTango.com

Program: USC Annenberg MS in Digital Social Media

]]> Thu, 6 Aug 2026 12:00:00 +0000 anika@yourbrandamplified.com (Anika Jackson) https://practical-pedagogy-the-art-of-teaching-for-the-future-of-wo.simplecast.com/episodes/escaping-ultra-processed-media-strategic-relatability-in-a-synthetic-world-with-freddy-tran-nager-BARYYsDC Anika sat down with Freddy Tran Nager, a digital media pioneer and USC Annenberg professor, to discuss why he doesn't just allow AI in his graduate classroom—he strictly requires it. The conversation revealed a critical shift in the modern workforce: AI hasn't just changed how we work; it has drastically raised the bar for what is considered "acceptable." Drawing from over three decades of digital strategy and his consultancy, Atomic Tango, Freddy explains why perfectly polished content is becoming obsolete, why the entry-level job is vanishing, and how the "creatively maladjusted" will inherit the future.

 

In This Episode

 

  • Why requiring AI in the classroom prepares graduate students for a rapidly shifting job market
  • Lessons from the Web 1.0 era: the career benefits of embracing new mediums early
  • The death of the traditional entry-level job and the rise of the "One Person Company" (OPC)
  • Why ChatGPT's output is the new definition of "C-level" work
  • The danger of the "ultra-processed" media era and the audience backlash against synthetic perfection
  • Why hiring managers are ignoring resumes and looking straight at portfolios and personal projects
  • The crucial difference between "authenticity" (a banned word in Freddy's class) and "relatability"
  • How AI is forcing young professionals to become editors and directors rather than just creators

 

Timestamps

 

  • 00:00 Introduction: Over 30 years in digital media and teaching at USC Annenberg
  • 01:37 Why Freddy strictly requires generative AI in his graduate courses
  • 03:39 Leveraging the ground floor of new mediums, from Web 1.0 to YouTube to AI
  • 08:20 The shifting job market: companies firing entry-level workers who can't use AI
  • 12:20 Losing emotional intelligence in the workplace when junior roles disappear
  • 14:43 Building portfolios over resumes: Why you should start your own project today
  • 16:50 "ChatGPT is a C": How AI raised the floor for average work
  • 22:39 The evolution of prompt engineering from basic requests to sophisticated direction
  • 25:22 The rise of "One Person Companies" and AI-powered entrepreneurship
  • 30:02 Faculty perspectives, academic integrity, and the return of the written blue book
  • 34:58 The human elements AI can't replace: critical thinking and engaging with opposing views
  • 36:31 The danger of perfectionism and the necessity of learning through failure
  • 40:01 How AI shifted Freddy's consultancy at Atomic Tango toward high-level strategy
  • 42:43 Why "authentic" is a banned word and the real value of "relatability"
  • 48:30 Guiding quotes from David Ogilvy and Martin Luther King Jr.

 

Key Insights & Takeaways

 

Insight 1: AI is the New "C" Average

 

Before AI, average work might have included structural issues or grammatical errors. Today, AI provides a perfectly polished, entirely generic baseline. If a student or professional submits work that sounds like ChatGPT, they are delivering "average" work. To stand out in the modern marketplace, you must use AI's output as the floor, not the ceiling, injecting unique perspective, emotion, and strategy to earn an "A."

 

Insight 2: The Death of the Entry-Level Task

 

Companies are actively eliminating basic junior roles (like writing social media captions) in favor of AI-enhanced professionals. Today's graduates must bypass the traditional entry-level mindset. Instead of aiming to be just a writer or a designer, they need to act as editors and art directors—capable of managing multiple AI tools to execute a higher-level vision faster than a traditional team.

 

Insight 3: Portfolios Speak Louder Than Resumes

 

With AI making it incredibly easy to generate a flawless cover letter and resume, hiring managers are looking straight past the paperwork. Freddy encourages students to show initiative by starting their own micro-businesses, podcasts, or e-commerce sites (One Person Companies). Proving you can independently leverage AI to build something tangible is far more impressive to modern employers than a passive corporate internship.

 

Insight 4: The Backlash Against "Ultra-Processed" Media

 

AI creates flawless, safe, and often boring content. However, human connection and persuasion rely heavily on emotion, relatability, and vulnerability. The pressure to be perfect is resulting in a sea of "ultra-processed" digital plastic that audiences are beginning to tune out. The creators and brands that will thrive are those willing to show a little rawness and reality.

 

Insight 5: Growth Requires the Freedom to Fail

 

By offering instant perfection, AI robs young professionals of the trial-and-error process crucial for long-term success. Making mistakes on low-stakes, entry-level projects used to be how professionals learned the realities of the market. Over-relying on AI to prevent failure creates a sterile environment where true innovation—which requires risk and "creative maladjustment"—is stifled.

 

Resources & Links Mentioned

 

  • Atomic Tango (Freddy's consultancy)
  • USC Annenberg MS in Digital Social Media
  • Xiaohongshu (Chinese social media platform)
  • Riverside.fm

 

About Freddy Tran Nager

 

Freddy Tran Nager is a digital media pioneer, strategist, and educator. Since editing one of the first entertainment websites in 1994, he has built a career staying ahead of digital trends, including working as a Senior Creative at Saatchi & Saatchi on Toyota's interactive media. Today, he runs the consultancy Atomic Tango and serves as a Clinical Associate Professor and Associate Director for the MS in Digital Social Media program at USC Annenberg. He is passionate about preparing students for the realities of the modern workforce by requiring AI proficiency, encouraging entrepreneurial initiative, and championing the "creatively maladjusted."

 

Connect with Freddy

 

Website: AtomicTango.com

Program: USC Annenberg MS in Digital Social Media

]]> Escaping Ultra-Processed Media: Strategic Relatability in a Synthetic World with Freddy Tran Nager Anika Jackson 00:52:10 Having witnessed the evolution of digital media from the commercial inception of the web in 1994 through the rise of social platforms and generative tools, Freddy Tran Nager views artificial intelligence not as an existential threat, but as a catalyst that fundamentally redefines acceptable performance. In an era where automated algorithms can generate polished essays, write code, and draft marketing plans in seconds, the baseline for generic work has drastically shifted. What once passed as acceptable entry-level production now represents the absolute floor of value—a baseline equivalent to a generic average. Having witnessed the evolution of digital media from the commercial inception of the web in 1994 through the rise of social platforms and generative tools, Freddy Tran Nager views artificial intelligence not as an existential threat, but as a catalyst that fundamentally redefines acceptable performance. In an era where automated algorithms can generate polished essays, write code, and draft marketing plans in seconds, the baseline for generic work has drastically shifted. What once passed as acceptable entry-level production now represents the absolute floor of value—a baseline equivalent to a generic average. false full 6 1a7d9efb-99e2-42d5-bf74-d374bd0845cb Shannon Franklin on Navigating AI Bias and Authenticity Shannon Franklin on Navigating AI Bias and Authenticity 

Anika sat down with Shannon Franklin, a digital marketing strategist and student in USC’s Master’s in Digital Media Management program, to get a dual perspective on generative AI in both the workforce and higher education. The conversation revealed the stark realities of AI integration—from it becoming a mandatory workplace KPI to the alarming biases it perpetuates regarding race and underrepresented communities. Shannon’s experience bridging the gap between a gritty corporate creative role and higher education offers a practical look at why critical thinking, authenticity, and reading comprehension are the most vital skills in the AI era.

 

In This Episode

  • The shock of realizing AI wasn't just a trend, but a mandatory workplace KPI
  • Why the human brain still searches for humanity in AI-generated imagery
  • The stark contrast between brands forcing AI adoption and global brands banning it
  • Confronting AI bias firsthand and the decision to train the model rather than give up
  • The environmental impact of generative AI and the "carbon criminal" narrative
  • Why reading comprehension and critical thinking are the ultimate safeguards against AI hallucinations
  • Practical advice for students using AI: assigning roles and setting boundaries
  • Navigating higher education in the AI era within USC's DMM program

 

Timestamps

 

  • 00:00 Introduction: The student perspective on AI in the classroom and workforce
  • 01:30 The "floating logo" moment: Discovering AI’s capabilities and flaws in a creative role
  • 04:32 When AI goes from a cool tool to a mandatory performance KPI
  • 07:54 Shannon’s litmus test for AI usability and preserving the human touch
  • 10:35 The initial shock of USC encouraging AI usage in higher education
  • 13:07 Confronting and correcting AI biases against Black-owned and underrepresented businesses
  • 17:44 Weighing the environmental footprint of generative AI and data centers
  • 23:09 Why critical thinking and independent research are more crucial than ever
  • 26:35 Best practices for students: Assigning AI a role without losing your voice
  • 29:24 Guiding principles for the digital age: Authenticity and transparency

 

Key Insights & Takeaways

 

Insight 1: AI is Now a Workplace KPI, Not Just a Novelty

 

For many growth-minded brands, AI is no longer optional—it is a metric of performance. Shannon experienced a rapid shift where her marketing team went from experimenting with AI to actively measuring employees on how they used it to cut costs, scale graphics, and bypass traditional agency work.

 

Insight 2: The Human Brain is Wired to Detect Inauthenticity

 

Despite how advanced generative AI has become, the human eye still searches for humanity. If an AI-generated image causes a visual "glitch" in the brain—a missing finger, an overly stretched face, or distorted text—it breaks trust. True creative professionals know when to lean on AI for speed and when to rely on traditional tools like Photoshop to maintain a brand's integrity.

 

Insight 3: Avoiding AI Means Accepting Its Biases

 

AI models are heavily biased based on the data they scrape. Shannon experienced this firsthand when generating mood boards for curly hair brands and Black creators, receiving highly stereotypical or inaccurate outputs. Instead of abandoning the tools, she highlights the necessity of actively pushing back and training the models to output more inclusive, accurate representations.

 

Insight 4: Critical Thinking is Your Defense Against Hallucinations

 

As AI makes accessing and synthesizing information easier, independent reading and critical thinking become more important, not less. Relying entirely on AI overviews can lead to echo chambers or flat-out lies (hallucinations). Forming your own opinions before consulting AI ensures you aren't just adopting a machine's synthesized conclusion.

 

Insight 5: Assign AI a Specific Role to Protect Your Voice

 

When using AI for academic or professional writing, leaving the prompt too broad allows the AI to strip away your personal voice. The best safeguard is to write out your initial thoughts on paper first, then prompt the AI with strict parameters—assigning it a specific role and explicitly telling it not to change your tone, words, or core opinions.

 

Resources & Links Mentioned

 

USC Master's in Digital Media Management (DMM) Program

Canva AI

Adobe Premiere & Photoshop

 

About Shannon Franklin

 

Shannon Franklin is a digital marketing strategist, content creator, and current student in USC's Master's in Digital Media Management program. With eight years of experience across social media, creative strategy, and performance marketing, she has worked extensively in the beauty and lifestyle spaces. Shannon is deeply passionate about connecting storytelling with scalable growth, particularly for Black-owned and underrepresented businesses, and advocates for transparency and authenticity in the age of generative AI.

 

Connect with Shannon

LinkedIn: https://www.linkedin.com/in/shannonafranklin/

]]> Thu, 30 Jul 2026 12:00:00 +0000 anika@yourbrandamplified.com (Anika Jackson) https://practical-pedagogy-the-art-of-teaching-for-the-future-of-wo.simplecast.com/episodes/shannon-franklin-on-navigating-ai-bias-and-authenticity-JJ33gmK6 Shannon Franklin on Navigating AI Bias and Authenticity 

Anika sat down with Shannon Franklin, a digital marketing strategist and student in USC’s Master’s in Digital Media Management program, to get a dual perspective on generative AI in both the workforce and higher education. The conversation revealed the stark realities of AI integration—from it becoming a mandatory workplace KPI to the alarming biases it perpetuates regarding race and underrepresented communities. Shannon’s experience bridging the gap between a gritty corporate creative role and higher education offers a practical look at why critical thinking, authenticity, and reading comprehension are the most vital skills in the AI era.

 

In This Episode

  • The shock of realizing AI wasn't just a trend, but a mandatory workplace KPI
  • Why the human brain still searches for humanity in AI-generated imagery
  • The stark contrast between brands forcing AI adoption and global brands banning it
  • Confronting AI bias firsthand and the decision to train the model rather than give up
  • The environmental impact of generative AI and the "carbon criminal" narrative
  • Why reading comprehension and critical thinking are the ultimate safeguards against AI hallucinations
  • Practical advice for students using AI: assigning roles and setting boundaries
  • Navigating higher education in the AI era within USC's DMM program

 

Timestamps

 

  • 00:00 Introduction: The student perspective on AI in the classroom and workforce
  • 01:30 The "floating logo" moment: Discovering AI’s capabilities and flaws in a creative role
  • 04:32 When AI goes from a cool tool to a mandatory performance KPI
  • 07:54 Shannon’s litmus test for AI usability and preserving the human touch
  • 10:35 The initial shock of USC encouraging AI usage in higher education
  • 13:07 Confronting and correcting AI biases against Black-owned and underrepresented businesses
  • 17:44 Weighing the environmental footprint of generative AI and data centers
  • 23:09 Why critical thinking and independent research are more crucial than ever
  • 26:35 Best practices for students: Assigning AI a role without losing your voice
  • 29:24 Guiding principles for the digital age: Authenticity and transparency

 

Key Insights & Takeaways

 

Insight 1: AI is Now a Workplace KPI, Not Just a Novelty

 

For many growth-minded brands, AI is no longer optional—it is a metric of performance. Shannon experienced a rapid shift where her marketing team went from experimenting with AI to actively measuring employees on how they used it to cut costs, scale graphics, and bypass traditional agency work.

 

Insight 2: The Human Brain is Wired to Detect Inauthenticity

 

Despite how advanced generative AI has become, the human eye still searches for humanity. If an AI-generated image causes a visual "glitch" in the brain—a missing finger, an overly stretched face, or distorted text—it breaks trust. True creative professionals know when to lean on AI for speed and when to rely on traditional tools like Photoshop to maintain a brand's integrity.

 

Insight 3: Avoiding AI Means Accepting Its Biases

 

AI models are heavily biased based on the data they scrape. Shannon experienced this firsthand when generating mood boards for curly hair brands and Black creators, receiving highly stereotypical or inaccurate outputs. Instead of abandoning the tools, she highlights the necessity of actively pushing back and training the models to output more inclusive, accurate representations.

 

Insight 4: Critical Thinking is Your Defense Against Hallucinations

 

As AI makes accessing and synthesizing information easier, independent reading and critical thinking become more important, not less. Relying entirely on AI overviews can lead to echo chambers or flat-out lies (hallucinations). Forming your own opinions before consulting AI ensures you aren't just adopting a machine's synthesized conclusion.

 

Insight 5: Assign AI a Specific Role to Protect Your Voice

 

When using AI for academic or professional writing, leaving the prompt too broad allows the AI to strip away your personal voice. The best safeguard is to write out your initial thoughts on paper first, then prompt the AI with strict parameters—assigning it a specific role and explicitly telling it not to change your tone, words, or core opinions.

 

Resources & Links Mentioned

 

USC Master's in Digital Media Management (DMM) Program

Canva AI

Adobe Premiere & Photoshop

 

About Shannon Franklin

 

Shannon Franklin is a digital marketing strategist, content creator, and current student in USC's Master's in Digital Media Management program. With eight years of experience across social media, creative strategy, and performance marketing, she has worked extensively in the beauty and lifestyle spaces. Shannon is deeply passionate about connecting storytelling with scalable growth, particularly for Black-owned and underrepresented businesses, and advocates for transparency and authenticity in the age of generative AI.

 

Connect with Shannon

LinkedIn: https://www.linkedin.com/in/shannonafranklin/

]]> Shannon Franklin on Navigating AI Bias and Authenticity Anika Jackson 00:33:57 Shannon Franklin’s journey through the digital marketing landscape and higher education perfectly encapsulates this modern tightrope walk. Her experience transitioning from early skepticism to actively navigating AI’s capabilities reveals a profound truth about the future of work: technology must remain a collaborative tool rather than a replacement for original human thought. When AI shifted almost overnight from a novelty to a mandatory performance metric in the corporate world, it forced a sudden adaptation. This rapid adoption highlighted the tension between producing content at an unprecedented scale and maintaining the genuine storytelling that connects with audiences on a human level. Shannon Franklin’s journey through the digital marketing landscape and higher education perfectly encapsulates this modern tightrope walk. Her experience transitioning from early skepticism to actively navigating AI’s capabilities reveals a profound truth about the future of work: technology must remain a collaborative tool rather than a replacement for original human thought. When AI shifted almost overnight from a novelty to a mandatory performance metric in the corporate world, it forced a sudden adaptation. This rapid adoption highlighted the tension between producing content at an unprecedented scale and maintaining the genuine storytelling that connects with audiences on a human level. false full 5 8a6fb77d-0946-4f5a-bcb9-39937e3d7361 Offline-First Learning: Ryan Ross on the AI Infrastructure Crisis Offline-First Learning: Ryan Ross on the AI Infrastructure Crisis

 

Anika sat down with Ryan Ross to explore a critical, often-overlooked question in the education technology debate: Can your school's infrastructure actually run AI? The conversation revealed a sobering reality regarding the global digital divide and the massive data requirements of modern AI. Ryan’s background in edge computing and fintech at Visa offered a practical blueprint for offline-first learning, highlighting how Small Language Models (SLMs) and edge networks are the true key to bringing digital resources to the students the internet forgot.

 

In This Episode

  • Transitioning from fintech at Visa to edtech and what education can learn from global payment networks
  • The creation of the Olivia Education Edge Network and the power of offline-first learning
  • Early deployment in East Texas and Hawaii, and the surprising "walled garden" benefit for classroom focus
  • The impending AI infrastructure crisis: how token consumption and broadband limits will break school budgets
  • Why Small Language Models (SLMs) solve the data sovereignty and policy compliance issues for districts
  • Partnering with Utah Tech to deliver associate degrees to incarcerated youth inside secure juvenile facilities
  • Scaling digital access across Africa and fixing internet-less computer labs
  • Key takeaways from the UN's "AI for Good" summit in Geneva regarding global infrastructure disparities
  • Practical, low-budget steps for educators to begin adopting AI this semester
  • The guiding philosophy of putting "teachers first" in any technology rollout

 

Timestamps

  • 00:00 Introduction: Can your school's infrastructure even run AI?
  • 01:18 The Visa connection: Applying payment terminal edge networks to classrooms
  • 04:18 Early use cases: Bridging the home broadband gap in East Texas and Hawaii
  • 08:10 Scaling to enterprise and realizing the impending AI data crisis
  • 10:27 Token consumption and why policy means nothing without infrastructure
  • 14:49 Why Small Language Models (SLMs) are the safest path for school districts
  • 16:57 The Utah Tech partnership: Bringing digital education into secure juvenile facilities
  • 20:39 Deploying in Africa: The reality of scaling digital resources with minimal bandwidth
  • 26:39 Why AI will never replace teachers and the realities of K-12 adoption
  • 29:42 Insights from the UN "AI for Good" summit: The massive global infrastructure deficit
  • 34:36 Practical steps for educators feeling behind on the AI curve
  • 38:05 The guiding principle: Why successful edtech must put teachers first

 

Key Insights & Takeaways

 

Insight 1: Infrastructure Precedes Policy 

School districts and legislators can draft all the AI policies they want regarding data sovereignty and usage, but without the broadband to support it, the policies are useless. Global estimates discussed at the UN summit show that 80% of schools worldwide lack the infrastructure for viable AI, meaning the real frontier of educational technology is access, not algorithms.

 

Insight 2: Edge Computing is the Education Solution 

Drawing from Visa's global payment terminal model, offline-first networks allow schools to sync data locally. This middleware approach allows a school of 500 students to access digital resources, videos, and learning management systems on a localized network without crippling the school's limited live bandwidth.

 

Insight 3: The Hidden Threat of Token Consumption 

Adding generative AI to schools isn't just a broadband issue—it's a massive, unpredictable budget issue. A single school of 500 students could burn through up to 5 billion tokens in a year. Traditional OpenAI models are financially and logistically unscalable for the average, under-resourced public school district.

 

Insight 4: Small Language Models (SLMs) Offer Total Control 

Large language models pose massive data privacy and intellectual property risks for universities and K-12 schools alike. By utilizing Small Language Models managed at the district or state level, schools can strictly control the ingested content, perfectly align it with state standards, and safeguard student data in a closed environment.

 

Insight 5: EdTech Must Put Teachers First 

AI will not replace educators, because teaching is fundamentally rooted in human interaction. True AI adoption in the classroom will only happen when tools are explicitly designed to reduce educator workload, assist in curriculum alignment, and increase teacher productivity before being pushed to the students.

 

Resources & Links Mentioned

 

Olivia Technologies (Olivia Education Edge Network)

Utah Tech University (Juvenile justice education partnership)

UN "AI for Good" Summit in Geneva

 

About Ryan Ross

 

Ryan Ross is the founder and CEO of Olivia Technologies and the creator of the Olivia Education Edge Network. With a deep background in edge computing, fintech, and biometric authentication at Visa, he transitioned into edtech to solve the digital divide. His offline-first platforms bring critical digital learning and AI capabilities to students in under-connected environments—from rural American school districts and secure juvenile justice facilities to schools across Africa.

 

His core mission, Ryan notes: 

"Two projects I am particularly passionate about are Olivia's work with Utah Tech University supporting justice-impacted and incarcerated youth, and our efforts across Africa to improve access to digital learning resources for schools with limited connectivity. Both initiatives reinforce a core belief: technology should expand educational opportunity, not create new barriers. Whether supporting students in secure learning environments or schools that lack reliable internet access, our focus is on delivering equitable access to learning, empowering teachers, and ensuring that every student has the opportunity to succeed regardless of their circumstances or location."

 

Connect with Ryan

LinkedIn: https://www.linkedin.com/in/rossrr3/

Olivia Technologies Website: https://www.olivia.school/

]]> Thu, 23 Jul 2026 12:00:00 +0000 anika@yourbrandamplified.com (Anika Jackson) https://practical-pedagogy-the-art-of-teaching-for-the-future-of-wo.simplecast.com/episodes/offline-first-learning-ryan-ross-on-the-ai-infrastructure-crisis-Jyi01y9v Offline-First Learning: Ryan Ross on the AI Infrastructure Crisis

 

Anika sat down with Ryan Ross to explore a critical, often-overlooked question in the education technology debate: Can your school's infrastructure actually run AI? The conversation revealed a sobering reality regarding the global digital divide and the massive data requirements of modern AI. Ryan’s background in edge computing and fintech at Visa offered a practical blueprint for offline-first learning, highlighting how Small Language Models (SLMs) and edge networks are the true key to bringing digital resources to the students the internet forgot.

 

In This Episode

  • Transitioning from fintech at Visa to edtech and what education can learn from global payment networks
  • The creation of the Olivia Education Edge Network and the power of offline-first learning
  • Early deployment in East Texas and Hawaii, and the surprising "walled garden" benefit for classroom focus
  • The impending AI infrastructure crisis: how token consumption and broadband limits will break school budgets
  • Why Small Language Models (SLMs) solve the data sovereignty and policy compliance issues for districts
  • Partnering with Utah Tech to deliver associate degrees to incarcerated youth inside secure juvenile facilities
  • Scaling digital access across Africa and fixing internet-less computer labs
  • Key takeaways from the UN's "AI for Good" summit in Geneva regarding global infrastructure disparities
  • Practical, low-budget steps for educators to begin adopting AI this semester
  • The guiding philosophy of putting "teachers first" in any technology rollout

 

Timestamps

  • 00:00 Introduction: Can your school's infrastructure even run AI?
  • 01:18 The Visa connection: Applying payment terminal edge networks to classrooms
  • 04:18 Early use cases: Bridging the home broadband gap in East Texas and Hawaii
  • 08:10 Scaling to enterprise and realizing the impending AI data crisis
  • 10:27 Token consumption and why policy means nothing without infrastructure
  • 14:49 Why Small Language Models (SLMs) are the safest path for school districts
  • 16:57 The Utah Tech partnership: Bringing digital education into secure juvenile facilities
  • 20:39 Deploying in Africa: The reality of scaling digital resources with minimal bandwidth
  • 26:39 Why AI will never replace teachers and the realities of K-12 adoption
  • 29:42 Insights from the UN "AI for Good" summit: The massive global infrastructure deficit
  • 34:36 Practical steps for educators feeling behind on the AI curve
  • 38:05 The guiding principle: Why successful edtech must put teachers first

 

Key Insights & Takeaways

 

Insight 1: Infrastructure Precedes Policy 

School districts and legislators can draft all the AI policies they want regarding data sovereignty and usage, but without the broadband to support it, the policies are useless. Global estimates discussed at the UN summit show that 80% of schools worldwide lack the infrastructure for viable AI, meaning the real frontier of educational technology is access, not algorithms.

 

Insight 2: Edge Computing is the Education Solution 

Drawing from Visa's global payment terminal model, offline-first networks allow schools to sync data locally. This middleware approach allows a school of 500 students to access digital resources, videos, and learning management systems on a localized network without crippling the school's limited live bandwidth.

 

Insight 3: The Hidden Threat of Token Consumption 

Adding generative AI to schools isn't just a broadband issue—it's a massive, unpredictable budget issue. A single school of 500 students could burn through up to 5 billion tokens in a year. Traditional OpenAI models are financially and logistically unscalable for the average, under-resourced public school district.

 

Insight 4: Small Language Models (SLMs) Offer Total Control 

Large language models pose massive data privacy and intellectual property risks for universities and K-12 schools alike. By utilizing Small Language Models managed at the district or state level, schools can strictly control the ingested content, perfectly align it with state standards, and safeguard student data in a closed environment.

 

Insight 5: EdTech Must Put Teachers First 

AI will not replace educators, because teaching is fundamentally rooted in human interaction. True AI adoption in the classroom will only happen when tools are explicitly designed to reduce educator workload, assist in curriculum alignment, and increase teacher productivity before being pushed to the students.

 

Resources & Links Mentioned

 

Olivia Technologies (Olivia Education Edge Network)

Utah Tech University (Juvenile justice education partnership)

UN "AI for Good" Summit in Geneva

 

About Ryan Ross

 

Ryan Ross is the founder and CEO of Olivia Technologies and the creator of the Olivia Education Edge Network. With a deep background in edge computing, fintech, and biometric authentication at Visa, he transitioned into edtech to solve the digital divide. His offline-first platforms bring critical digital learning and AI capabilities to students in under-connected environments—from rural American school districts and secure juvenile justice facilities to schools across Africa.

 

His core mission, Ryan notes: 

"Two projects I am particularly passionate about are Olivia's work with Utah Tech University supporting justice-impacted and incarcerated youth, and our efforts across Africa to improve access to digital learning resources for schools with limited connectivity. Both initiatives reinforce a core belief: technology should expand educational opportunity, not create new barriers. Whether supporting students in secure learning environments or schools that lack reliable internet access, our focus is on delivering equitable access to learning, empowering teachers, and ensuring that every student has the opportunity to succeed regardless of their circumstances or location."

 

Connect with Ryan

LinkedIn: https://www.linkedin.com/in/rossrr3/

Olivia Technologies Website: https://www.olivia.school/

]]> Offline-First Learning: Ryan Ross on the AI Infrastructure Crisis Anika Jackson 00:41:13 Ryan Ross, founder and CEO of Olivia Technologies, brings a unique perspective to the intersection of fintech innovation and educational equity. His journey from Visa's innovation group, where he worked extensively on edge computing and biometric authentication, reveals a critical insight: the infrastructure patterns that revolutionized payments can solve education's most pressing accessibility challenges. At Visa, payment terminals deployed globally operate on an edge network model, calling home only when necessary to move data. This same principle, Ross recognized, could transform how schools deliver digital resources in environments constrained by limited or expensive broadband connectivity. Ryan Ross, founder and CEO of Olivia Technologies, brings a unique perspective to the intersection of fintech innovation and educational equity. His journey from Visa's innovation group, where he worked extensively on edge computing and biometric authentication, reveals a critical insight: the infrastructure patterns that revolutionized payments can solve education's most pressing accessibility challenges. At Visa, payment terminals deployed globally operate on an edge network model, calling home only when necessary to move data. This same principle, Ross recognized, could transform how schools deliver digital resources in environments constrained by limited or expensive broadband connectivity. false full 4 3c3a8c99-67f1-4e4b-ae65-bdf0bf8cc7be Non-Negotiable Rules for AI in Education with Dave Oates Anika sat down with Dave Oates to explore a counterintuitive truth: in an era of AI disruption, critical thinking has become your most defensible asset. Dave shares his transformational journey from Navy public affairs officer to crisis PR expert to educator—revealing why asking the right questions is the only intellectual differentiator AI cannot replace. He introduces three non-negotiable conditions for AI in the classroom—citation, source validation, and the why behind every answer—and discusses why institutions that swing from banning AI to embracing it overnight are doing students a disservice. The conversation challenges how universities teach responsible technology use alongside critical thinking, and exposes why most educators remain trapped in memorization-based curricula built on fear instead of passion.

 

In This Episode

 

  • The origin of Dave's crisis PR expertise: 30 years navigating institutional reputational crises 
  • Why institutions overestimate AI risk and the calculator debate of the 1960s  
  • Making AI your employee, not your boss: a student's brilliant reframe 
    The San Diego State pivot: from banning AI mid-semester to embracing it  
  • Why AI is a "dumb machine" that hallucinates and can't evaluate truth 
  • The three non-negotiable conditions for AI in the classroom: citation, source validation, and the why  
  • How assignments that demand reasoning expose AI misuse immediately  
  • The "learn-do model": why application and mastery require more than AI-generated answers  
  • Real-world engagement: interviews, surveys, and relationships that AI cannot replace 
  • The experiential imperative: why showing up and being confidently vulnerable transforms learning  
  • Why memorization-based education is dead and critical thinking is essential 
  • Trust through accessibility: responding within one business day and personal connection 
  • Your identity is your differentiator: the closing philosophy on what matters most  

 

Timestamps

 

  • 01:25-02:31 The calculator debate of the 1960s: what tech panic teaches us about today's AI fears
  • 03:11-03:53 "Make it your employee, not your boss"—a student's brilliant reframe that changed everything
  • 04:46-06:24 San Diego State's radical shift: banning AI to embracing it mid-semester and the confusion that followed
  • 06:42-08:48 Why AI is fundamentally limited: it hallucinates and can't evaluate truth
  • 12:12-12:51 The three non-negotiable conditions: citation, source validation, and explaining your reasoning
  • 15:38-18:25 The learn-do model: why mastery requires application to what you're passionate about
  • 19:21-20:31 Nothing beats real relationships: interviews, surveys, and human engagement that AI can't replace
  • 21:51-22:47 Redefining failure: it's only when you don't show up and don't engage
  • 36:25-37:06 Memorization is dead: when you have AI, critical thinking becomes the only differentiator
  • 38:12-40:07 Trust is built through accessibility: one business day response time and genuine enthusiasm
  • 41:25-42:17 "You still matter if you show up"—the mantra that transcends AI and education

 

Key Insights & Takeaways

 

Insight 1: We've Been Here Before—And We Survived

The calculator debate of the 1960s mirrors today's AI panic. People feared calculators would make us dumb. Fifty years later, we know tools don't diminish us when we understand how they work. As Dave explains: "The calculator didn't make us dumb. It is a tool set...people who are operating the calculator have to know the fundamental workings and engine on that to back up the reasoning for the calculations." AI is the same. The question isn't whether to use it—it's whether we know what we're doing when we do.

 

Insight 2: AI Is a Dumb Machine That Looks Smart

AI synthesizes information eloquently but doesn't rank it, evaluate truth, or catch its own hallucinations. It makes things up when it doesn't know answers. Dave warns: "It's not evaluating whether something is true or not...probably the biggest thing I think it does that we've all been talking about even more so is it just makes shit up. If it doesn't have something, it just hallucinates." An organization that hands an AI-generated crisis statement to executives without human review will create more damage than the original crisis.

 

Insight 3: Assignments That Ask "Why" Expose AI Misuse Immediately

If your assignment asks students to regurgitate facts, AI wins and you won't know. If your assignment demands reasoning, conviction, and original thought backed by research, cheating becomes obvious. Dave illustrates: "If we have as instructors, assignments that basically want students to just regurgitate facts...AI is going to be fine...But the common theme with all of those is I'm teaching critical thinking, I'm teaching why, and I'm teaching them to take chances." The problem isn't AI—it's how we design learning.

 

Insight 4: Citation and Rationale Transform AI From Crutch to Tool

Students must cite when they use AI and explain why they chose to use it. Dave's framework: "A, you have to cite that you used it...B, you have to tell me why I think it's okay for you to use AI." This teaches professional accountability: in the real world, you'll need to defend every choice you made, including which tools you used to make it.

 

Insight 5: Mastery Requires Application Beyond Information 

AI can provide information instantly. But retention, understanding, and mastery come through the "learn-do model"—learning something and then applying it to what you're passionate about. Dave requires students to conduct real interviews, do surveys, and engage with actual professionals. This real-world data often contradicts what AI suggests—and that's the learning moment.

 

Insight 6: Nothing Beats the Art of Relationships 

AI can't conduct interviews. It can't do surveys. It can't build the trust that comes from showing up in person and being vulnerable. Dave emphasizes: "Nothing still beats the art of relationships...You got to get out there and actually talk to people." That human data often contradicts what AI suggests—and that's where real learning happens.

 

Insight 7: Redefining Failure Transforms Student Engagement 

Dave's philosophy: "The second thing that we teach above all else is the imperative art of showing up...Failure is only when you decide not to show up and not engage, because now you didn't even try." Students engage because they see an instructor who cares. Trust isn't built through policy—it's built through showing up, being accessible, and demonstrating genuine enthusiasm.

 

Insight 8: Memorization Is Dead; Critical Thinking Is Essential

The old model of teaching facts is obsolete. Dave declares: "I don't need memorization anymore. When I have at my FingerTips a generative LLM model and even a Boolean search model...I'm teaching critical thinking, and my assignments are architected accordingly." This shift isn't optional—it's survival.

 

Insight 9: Trust Is Built Through Presence and Passion 

Dave's secret to building trust with 116 students: "I am accessible to you outside of class...I promise you I will respond within one business day, no later...If I'm not passionate about what I'm teaching, the kids are going to follow suit...I have name cards for every one of the kids...I'm trying to break that distance, that barrier between the instructor and the students." This transforms large classes into intimate learning communities.

 

Resources & Links

San Diego State University School of Journalism & Media Studies: https://journalism.sdsu.edu/

Dave's Teaching Focus Areas:

Advertising

Media Studies

Public Relations

 

About Dave Oates

 

Dave Oates is a crisis PR expert with 30 years of experience across military, corporate, nonprofit, and education sectors. He served as a U.S. Navy public affairs officer before building a career helping institutions navigate reputational crises through transparency and accountability. For the past three years, he has been a part-time lecturer at San Diego State University, teaching advertising, media studies, and PR to undergraduate and graduate students.

 

His guiding principle—"Respect tradition, embrace tomorrow"—defines his strategic, thoughtful approach to emerging technologies like AI, viewing them not as threats but as tools that amplify great teaching.

 

His mission: Help students and professionals understand that AI is a tool to enhance thinking, not replace it—and that showing up with passion and conviction is the only economic differentiator that matters.

 

Connect with Dave Oates

 

San Diego State University: https://www.sdsu.edu/ 

LinkedIn: https://www.linkedin.com/in/davidoates/

]]> Thu, 16 Jul 2026 12:00:00 +0000 anika@yourbrandamplified.com (Anika Jackson) https://practical-pedagogy-the-art-of-teaching-for-the-future-of-wo.simplecast.com/episodes/non-negotiable-rules-for-ai-in-education-with-dave-oates-kTHH7nUF Anika sat down with Dave Oates to explore a counterintuitive truth: in an era of AI disruption, critical thinking has become your most defensible asset. Dave shares his transformational journey from Navy public affairs officer to crisis PR expert to educator—revealing why asking the right questions is the only intellectual differentiator AI cannot replace. He introduces three non-negotiable conditions for AI in the classroom—citation, source validation, and the why behind every answer—and discusses why institutions that swing from banning AI to embracing it overnight are doing students a disservice. The conversation challenges how universities teach responsible technology use alongside critical thinking, and exposes why most educators remain trapped in memorization-based curricula built on fear instead of passion.

 

In This Episode

 

  • The origin of Dave's crisis PR expertise: 30 years navigating institutional reputational crises 
  • Why institutions overestimate AI risk and the calculator debate of the 1960s  
  • Making AI your employee, not your boss: a student's brilliant reframe 
    The San Diego State pivot: from banning AI mid-semester to embracing it  
  • Why AI is a "dumb machine" that hallucinates and can't evaluate truth 
  • The three non-negotiable conditions for AI in the classroom: citation, source validation, and the why  
  • How assignments that demand reasoning expose AI misuse immediately  
  • The "learn-do model": why application and mastery require more than AI-generated answers  
  • Real-world engagement: interviews, surveys, and relationships that AI cannot replace 
  • The experiential imperative: why showing up and being confidently vulnerable transforms learning  
  • Why memorization-based education is dead and critical thinking is essential 
  • Trust through accessibility: responding within one business day and personal connection 
  • Your identity is your differentiator: the closing philosophy on what matters most  

 

Timestamps

 

  • 01:25-02:31 The calculator debate of the 1960s: what tech panic teaches us about today's AI fears
  • 03:11-03:53 "Make it your employee, not your boss"—a student's brilliant reframe that changed everything
  • 04:46-06:24 San Diego State's radical shift: banning AI to embracing it mid-semester and the confusion that followed
  • 06:42-08:48 Why AI is fundamentally limited: it hallucinates and can't evaluate truth
  • 12:12-12:51 The three non-negotiable conditions: citation, source validation, and explaining your reasoning
  • 15:38-18:25 The learn-do model: why mastery requires application to what you're passionate about
  • 19:21-20:31 Nothing beats real relationships: interviews, surveys, and human engagement that AI can't replace
  • 21:51-22:47 Redefining failure: it's only when you don't show up and don't engage
  • 36:25-37:06 Memorization is dead: when you have AI, critical thinking becomes the only differentiator
  • 38:12-40:07 Trust is built through accessibility: one business day response time and genuine enthusiasm
  • 41:25-42:17 "You still matter if you show up"—the mantra that transcends AI and education

 

Key Insights & Takeaways

 

Insight 1: We've Been Here Before—And We Survived

The calculator debate of the 1960s mirrors today's AI panic. People feared calculators would make us dumb. Fifty years later, we know tools don't diminish us when we understand how they work. As Dave explains: "The calculator didn't make us dumb. It is a tool set...people who are operating the calculator have to know the fundamental workings and engine on that to back up the reasoning for the calculations." AI is the same. The question isn't whether to use it—it's whether we know what we're doing when we do.

 

Insight 2: AI Is a Dumb Machine That Looks Smart

AI synthesizes information eloquently but doesn't rank it, evaluate truth, or catch its own hallucinations. It makes things up when it doesn't know answers. Dave warns: "It's not evaluating whether something is true or not...probably the biggest thing I think it does that we've all been talking about even more so is it just makes shit up. If it doesn't have something, it just hallucinates." An organization that hands an AI-generated crisis statement to executives without human review will create more damage than the original crisis.

 

Insight 3: Assignments That Ask "Why" Expose AI Misuse Immediately

If your assignment asks students to regurgitate facts, AI wins and you won't know. If your assignment demands reasoning, conviction, and original thought backed by research, cheating becomes obvious. Dave illustrates: "If we have as instructors, assignments that basically want students to just regurgitate facts...AI is going to be fine...But the common theme with all of those is I'm teaching critical thinking, I'm teaching why, and I'm teaching them to take chances." The problem isn't AI—it's how we design learning.

 

Insight 4: Citation and Rationale Transform AI From Crutch to Tool

Students must cite when they use AI and explain why they chose to use it. Dave's framework: "A, you have to cite that you used it...B, you have to tell me why I think it's okay for you to use AI." This teaches professional accountability: in the real world, you'll need to defend every choice you made, including which tools you used to make it.

 

Insight 5: Mastery Requires Application Beyond Information 

AI can provide information instantly. But retention, understanding, and mastery come through the "learn-do model"—learning something and then applying it to what you're passionate about. Dave requires students to conduct real interviews, do surveys, and engage with actual professionals. This real-world data often contradicts what AI suggests—and that's the learning moment.

 

Insight 6: Nothing Beats the Art of Relationships 

AI can't conduct interviews. It can't do surveys. It can't build the trust that comes from showing up in person and being vulnerable. Dave emphasizes: "Nothing still beats the art of relationships...You got to get out there and actually talk to people." That human data often contradicts what AI suggests—and that's where real learning happens.

 

Insight 7: Redefining Failure Transforms Student Engagement 

Dave's philosophy: "The second thing that we teach above all else is the imperative art of showing up...Failure is only when you decide not to show up and not engage, because now you didn't even try." Students engage because they see an instructor who cares. Trust isn't built through policy—it's built through showing up, being accessible, and demonstrating genuine enthusiasm.

 

Insight 8: Memorization Is Dead; Critical Thinking Is Essential

The old model of teaching facts is obsolete. Dave declares: "I don't need memorization anymore. When I have at my FingerTips a generative LLM model and even a Boolean search model...I'm teaching critical thinking, and my assignments are architected accordingly." This shift isn't optional—it's survival.

 

Insight 9: Trust Is Built Through Presence and Passion 

Dave's secret to building trust with 116 students: "I am accessible to you outside of class...I promise you I will respond within one business day, no later...If I'm not passionate about what I'm teaching, the kids are going to follow suit...I have name cards for every one of the kids...I'm trying to break that distance, that barrier between the instructor and the students." This transforms large classes into intimate learning communities.

 

Resources & Links

San Diego State University School of Journalism & Media Studies: https://journalism.sdsu.edu/

Dave's Teaching Focus Areas:

Advertising

Media Studies

Public Relations

 

About Dave Oates

 

Dave Oates is a crisis PR expert with 30 years of experience across military, corporate, nonprofit, and education sectors. He served as a U.S. Navy public affairs officer before building a career helping institutions navigate reputational crises through transparency and accountability. For the past three years, he has been a part-time lecturer at San Diego State University, teaching advertising, media studies, and PR to undergraduate and graduate students.

 

His guiding principle—"Respect tradition, embrace tomorrow"—defines his strategic, thoughtful approach to emerging technologies like AI, viewing them not as threats but as tools that amplify great teaching.

 

His mission: Help students and professionals understand that AI is a tool to enhance thinking, not replace it—and that showing up with passion and conviction is the only economic differentiator that matters.

 

Connect with Dave Oates

 

San Diego State University: https://www.sdsu.edu/ 

LinkedIn: https://www.linkedin.com/in/davidoates/

]]> Non-Negotiable Rules for AI in Education with Dave Oates Anika Jackson 00:45:30 Dave Oates has spent three decades telling the truth when institutions least wanted to hear it. As a crisis PR expert across military, corporate, nonprofit, and education sectors, he learned early that transparency and accountability aren't optional luxuries—they're survival strategies. Now, as a educator at San Diego State University, he applies the same principles that guided his crisis communication work to a fundamentally different challenge: how do we teach students to use AI responsibly when the stakes of getting it wrong keep rising? His answer is both simple and profound: we stop fearing the tool and start teaching people to think critically about it. Dave Oates has spent three decades telling the truth when institutions least wanted to hear it. As a crisis PR expert across military, corporate, nonprofit, and education sectors, he learned early that transparency and accountability aren't optional luxuries—they're survival strategies. Now, as a educator at San Diego State University, he applies the same principles that guided his crisis communication work to a fundamentally different challenge: how do we teach students to use AI responsibly when the stakes of getting it wrong keep rising? His answer is both simple and profound: we stop fearing the tool and start teaching people to think critically about it. false full 3 a6f06f66-e154-44c6-a59d-ccd25e15f42a Vocating Your Way Through AI with Florian Kemmerich Anika sat down with Florian Kemmerich to explore a counterintuitive truth: in an era of AI disruption, your identity has become your most defensible asset. Florian shares his transformational journey from bullied child to judo champion, paratrooper, and impact investor—revealing why self-knowledge is the only economic differentiator AI cannot replace. He introduces "vocating," a framework for aligning professional life with authentic identity, and discusses the Vocating AI platform designed to help students and professionals discover their true calling in minutes rather than years. The conversation challenges how universities teach purpose alongside technology, and exposes why most people remain trapped in careers built on fear instead of love.

 

In This Episode

 

  • The connective tissue: How a childhood imprint at age 5 shaped every major life decision  
  • Confronting fear: Why Florian chose judo, then paratroopers, then impact investing—always putting himself at risk  
  • Leaving the golden handcuffs: The moment at age 33 when inner child work revealed he was living someone else's life 
  • The vocating framework: How ikigai became livable through four components—identity, meaning, impact, and livelihood 
  • The Vocating AI platform: Using agentic AI with agents trained on psychology, transactional analysis, and Enneagram to compress years of self-discovery into minutes  
  • Real-time testing: 100 students from 20 universities currently testing the app, providing feedback for scientific validation 
  • The cost of misalignment: How organizations lose money and talent when people aren't aligned with their work  
  • Three exercises to start: Cut out the noise, remember your earliest childhood memory, imagine your deathbed, then bring it to today  
  • The AI disruption moment: When Florian automated 70% of jobs and realized millions would face the same displacement
  • The second book: Vocating Organizations coming September/October, focused on how business leaders can leverage vocating for competitiveness  

 

Key Insights & Takeaways

 

Insight 1: Your Imprint Shapes Your Life's Meaning

Between ages 2-6, something happens to you that gives your life meaning and stays with you forever. For Florian, bullying at age 5 became his imprint: not fear, but a question: "Why are they mean to me?" That single moment connected every major decision that followed—from judo to paratroopers to impact investing. The connective tissue isn't luck. It's confronting the fear that defines you.

 

Insight 2: Vocating Is a Verb—Do Both Things at Once

Most people think "job," "career," or "calling." Florian reframes it entirely. Vocating means dedicating yourself professionally to your vocate—your identity, personality, and inner calling—while making a living. Education teaches the opposite: succeed first (fame, fortune, power), then give back. But that path feeds only your ego and leads to burnout. When you vocate, you do both things simultaneously.

 

Insight 3: Self-Knowledge Is the Economic Differentiator in the AI Era

AI disrupts knowledge work, entry-level jobs, and linear careers. The one thing AI cannot replace is your identity. When you don't know who you are, you ask the machine. When the machine decides your fate, an algorithm—not you—controls your life. Your identity has become a key economic value driver. That's why vocating education is now essential.

 

Insight 4: Burnout Signals Misalignment Between Fear and Love

You make decisions based on fear (ego, fame, fortune, power) or based on love (intuition, authenticity, contribution). A doctor who became one because their parent was a doctor will burn out. A musician chasing rock star status will end up in drugs. The same job, done from love instead of fear, becomes fulfilling. Burnout isn't a productivity problem—it's a signal you're living someone else's life.

 

Insight 5: Misalignment in Organizations Costs Real Money

When people aren't aligned with their work, organizations suffer. Shifting from shareholder value to stakeholder value—where egos come down and empathy goes up, where diverse teams matter, where intrinsic motivation drives performance—changes everything. Net promoter scores go up. Business performance improves. It doesn't matter what sector you're in.

 

Insight 6: The Future Belongs to Purpose-Driven People

Only two groups will succeed economically in the AI era: neurodivergent people (who always knew they were different) and purpose-driven people (who know what they want). Everyone else will ask technology to solve their problem. Technology becomes either a tool or a crutch. The differentiator is knowing your vocate first.

 

Resources & Links

Vocating AI Platform: Testing phase with 100 students from 20 universities

First Book: Published by Routledge (available on Amazon, Apple Books)

Second Book: Vocating Organizations (September/October 2026)

 

About Florian Kemmerich

 

Florian is a Swiss-based impact investor, author, and founder of the Vocating AI platform. Over 25+ years, he has deployed close to a billion dollars in impact capital across Africa, Asia, and Latin America, served on multiple boards across four continents, and guided 200+ people toward discovering their vocate. He's authored the first book on vocating and is completing a second on vocating organizations. He's also a father of five, multilingual, and operates across four continents.

 

His mission: Help millions discover who they are and how to make a living aligned with their authentic identity—before AI makes that choice for them.

 

Connect with Florian

LinkedIn: https://www.linkedin.com/in/floriankemmerich/

Vocating Platform: https://vocating.ai/

Books: https://on-vocation.com/

 

]]> Thu, 9 Jul 2026 12:00:00 +0000 anika@yourbrandamplified.com (Anika Jackson) https://practical-pedagogy-the-art-of-teaching-for-the-future-of-wo.simplecast.com/episodes/vocating-your-way-through-ai-with-florian-kemmerich-XXBw_dWV Anika sat down with Florian Kemmerich to explore a counterintuitive truth: in an era of AI disruption, your identity has become your most defensible asset. Florian shares his transformational journey from bullied child to judo champion, paratrooper, and impact investor—revealing why self-knowledge is the only economic differentiator AI cannot replace. He introduces "vocating," a framework for aligning professional life with authentic identity, and discusses the Vocating AI platform designed to help students and professionals discover their true calling in minutes rather than years. The conversation challenges how universities teach purpose alongside technology, and exposes why most people remain trapped in careers built on fear instead of love.

 

In This Episode

 

  • The connective tissue: How a childhood imprint at age 5 shaped every major life decision  
  • Confronting fear: Why Florian chose judo, then paratroopers, then impact investing—always putting himself at risk  
  • Leaving the golden handcuffs: The moment at age 33 when inner child work revealed he was living someone else's life 
  • The vocating framework: How ikigai became livable through four components—identity, meaning, impact, and livelihood 
  • The Vocating AI platform: Using agentic AI with agents trained on psychology, transactional analysis, and Enneagram to compress years of self-discovery into minutes  
  • Real-time testing: 100 students from 20 universities currently testing the app, providing feedback for scientific validation 
  • The cost of misalignment: How organizations lose money and talent when people aren't aligned with their work  
  • Three exercises to start: Cut out the noise, remember your earliest childhood memory, imagine your deathbed, then bring it to today  
  • The AI disruption moment: When Florian automated 70% of jobs and realized millions would face the same displacement
  • The second book: Vocating Organizations coming September/October, focused on how business leaders can leverage vocating for competitiveness  

 

Key Insights & Takeaways

 

Insight 1: Your Imprint Shapes Your Life's Meaning

Between ages 2-6, something happens to you that gives your life meaning and stays with you forever. For Florian, bullying at age 5 became his imprint: not fear, but a question: "Why are they mean to me?" That single moment connected every major decision that followed—from judo to paratroopers to impact investing. The connective tissue isn't luck. It's confronting the fear that defines you.

 

Insight 2: Vocating Is a Verb—Do Both Things at Once

Most people think "job," "career," or "calling." Florian reframes it entirely. Vocating means dedicating yourself professionally to your vocate—your identity, personality, and inner calling—while making a living. Education teaches the opposite: succeed first (fame, fortune, power), then give back. But that path feeds only your ego and leads to burnout. When you vocate, you do both things simultaneously.

 

Insight 3: Self-Knowledge Is the Economic Differentiator in the AI Era

AI disrupts knowledge work, entry-level jobs, and linear careers. The one thing AI cannot replace is your identity. When you don't know who you are, you ask the machine. When the machine decides your fate, an algorithm—not you—controls your life. Your identity has become a key economic value driver. That's why vocating education is now essential.

 

Insight 4: Burnout Signals Misalignment Between Fear and Love

You make decisions based on fear (ego, fame, fortune, power) or based on love (intuition, authenticity, contribution). A doctor who became one because their parent was a doctor will burn out. A musician chasing rock star status will end up in drugs. The same job, done from love instead of fear, becomes fulfilling. Burnout isn't a productivity problem—it's a signal you're living someone else's life.

 

Insight 5: Misalignment in Organizations Costs Real Money

When people aren't aligned with their work, organizations suffer. Shifting from shareholder value to stakeholder value—where egos come down and empathy goes up, where diverse teams matter, where intrinsic motivation drives performance—changes everything. Net promoter scores go up. Business performance improves. It doesn't matter what sector you're in.

 

Insight 6: The Future Belongs to Purpose-Driven People

Only two groups will succeed economically in the AI era: neurodivergent people (who always knew they were different) and purpose-driven people (who know what they want). Everyone else will ask technology to solve their problem. Technology becomes either a tool or a crutch. The differentiator is knowing your vocate first.

 

Resources & Links

Vocating AI Platform: Testing phase with 100 students from 20 universities

First Book: Published by Routledge (available on Amazon, Apple Books)

Second Book: Vocating Organizations (September/October 2026)

 

About Florian Kemmerich

 

Florian is a Swiss-based impact investor, author, and founder of the Vocating AI platform. Over 25+ years, he has deployed close to a billion dollars in impact capital across Africa, Asia, and Latin America, served on multiple boards across four continents, and guided 200+ people toward discovering their vocate. He's authored the first book on vocating and is completing a second on vocating organizations. He's also a father of five, multilingual, and operates across four continents.

 

His mission: Help millions discover who they are and how to make a living aligned with their authentic identity—before AI makes that choice for them.

 

Connect with Florian

LinkedIn: https://www.linkedin.com/in/floriankemmerich/

Vocating Platform: https://vocating.ai/

Books: https://on-vocation.com/

 

]]> Vocating Your Way Through AI with Florian Kemmerich Anika Jackson 00:57:37 The most dangerous moment in human history may not be when artificial intelligence becomes smarter than us. It's when we stop knowing who we are. Florian Kemmerich, a Swiss impact investor who has deployed nearly a billion dollars across four continents, offers a counterintuitive thesis about survival in the AI economy: your identity has become your most defensible economic asset. Not your skills. Not your credentials. Not your ability to code or analyze data. Your identity. The most dangerous moment in human history may not be when artificial intelligence becomes smarter than us. It's when we stop knowing who we are. Florian Kemmerich, a Swiss impact investor who has deployed nearly a billion dollars across four continents, offers a counterintuitive thesis about survival in the AI economy: your identity has become your most defensible economic asset. Not your skills. Not your credentials. Not your ability to code or analyze data. Your identity. ai, ai pedagogy, ai ethics, ai career, ai in education false full 2 7d220d3f-3955-4496-9ae1-e9835e475a7d Kirk Spahn on AI and the Future of Learning Kirk Spahn has spent 25 years building schools around passion and character—long before AI became the conversation everyone's having. What struck me in talking with him is that he's not afraid of AI or naive about it. He's asking a different question than most educators: instead of "How do we protect students from AI?" he's asking "How do we prepare students to think critically while using it?" His framework—passion-based learning, character development, real-world application—actually gets stronger with AI, not weaker. If you're a parent, educator, or leader trying to figure out what education should actually look like right now, this is essential listening.

 

In This Episode

  • The origin of ICL Academy in 2001 and passion-based learning
  • Why traditional education was designed for a different era (and why that matters now)
  • How personalization at scale becomes possible through technology—without replacing teachers
  • The "learn-do model": why application and mastery require more than AI-generated answers
  • Why he's building curriculum with "find the flaws" assignments instead of banning AI
  • The immersive potential of VR/XR in education—and why it still needs a human guide
  • His three-pillar framework: inspire, educate, impact
  • Why "dare to dream" and "courage to risk" are non-negotiable for the next generation

 

Timestamps

  • 00:00 Introduction: Education and AI in the modern era
  • 02:12 The founding of ICL Academy in 2001 and passion-based learning
  • 05:37 ICL Academy's educational approach and personalization
  • 13:40 Early stage AI use in education and critical thinking
  • 20:51 Balancing AI and human elements in learning
  • 22:17 Building curriculum with "find the flaws" AI exercises
  • 26:16 Emerging technologies: XR/VR for immersive learning
  • 27:37 Exploring and piloting virtual labs and simulations
  • 31:32 Core educational principles: "Respect tradition, embrace tomorrow"
  • 34:15 Dare to dream, courage to risk, and leadership through action
  • 38:25 Closing thoughts on preparing the next generation

 

Key Insights & Takeaways

 

Insight 1: AI Amplifies Great Teaching—It Doesn't Replace It

 

The fear that AI will make teachers irrelevant misses the point entirely. What AI actually does is free great teachers from administrative burden so they can spend time in meaningful one-on-one conversations with students. The human elements—mentorship, dialogue, knowing your students deeply—remain irreplaceable. Technology is a stage; the teacher is still the performer.

 

Insight 2: Engagement Is the Single Greatest Detriment (and Opportunity) in Modern Education

 

Students don't disengage because education is too hard. They disengage because it's disconnected from what they care about. When a tennis player learns physics through serving, when a musician explores math through acoustics, engagement transforms. Personalization isn't innovative—it's obvious. The barrier was always logistics, which technology can now solve.

 

Insight 3: We're in AI 1.0—Teaching Critical Thinking Matters More Than Banning It

 

Comparing AI to the early internet or the first calculators, Kirk argues we're at day one. Yes, students can use it to cheat. Yes, it gets things wrong. But the answer isn't restriction—it's teaching students to interrogate AI outputs, to find flaws, to understand both its power and its limitations. This generation will work with AI their entire careers; they need to learn how to use it as a tool, not a shortcut.

 

Insight 4: Mastery Requires Application Beyond Information

 

AI can provide information instantly. But retention, understanding, and mastery come through the "learn-do model"—learning something and then applying it to what you're passionate about. A student can get an AI-generated answer to a math problem; mastery happens when they apply that math to solve a real problem in their life.

 

Insight 5: Certain Subjects Require Limiting AI to Protect Authentic Learning

 

Just as some math classes prohibit calculators while others require them, some courses at ICL intentionally limit AI use. Leadership classes, for example, require deep personal reflection that can't be outsourced. The strategy isn't "no AI ever"—it's thoughtful decisions about when technology serves learning and when it gets in the way.

 

Insight 6: The Future of Education Is Hybrid, Not Either/Or

 

Traditional schools won't disappear. But the future includes more flexibility, more personalization, more opportunities for students to learn outside four walls. Athletes need training time. Musicians need practice schedules. Why force all learning into an 8am-3pm box? Technology makes hybrid models possible—but only if we design them around student identity, not efficiency.

 

Why This Matters Now

Education is at an inflection point. We can double down on the industrial model—standardized tests, one-size-fits-all curriculum, AI as a replacement for teachers. Or we can use technology to finally do what we've always known works: meet students where they are, connect learning to their passions, and develop not just their minds but their character. Kirk's 25-year track record suggests the second path isn't just more humane—it's more effective.

 

Resources & Links Mentioned

  • ICL Academy — Passion-based online learning for students with demanding schedules 
  • ICL Foundation — Character development and educational innovation 
  • Virtual Reality in Education — Meta Campus and XR/VR learning experiences
  • International Baccalaureate (IB) — Global educational framework

 

About Kirk Spahn

A fourth-generation educator and founder of ICL Academy and the ICL Foundation, Kirk Spahn has spent over 25 years pioneering passion-based learning models that prioritize student identity and character alongside academics. Growing up in an International Baccalaureate family, he recognized early that education must look at the person first—creating critical thinkers prepared for real-world challenges. As one of the earliest pioneers of online private education in the U.S., Kirk built ICL to serve high-performing students (junior athletes, musicians, performers) whose passions demand flexibility traditional schools cannot provide. His guiding principle—"Respect tradition, embrace tomorrow"—defines his strategic, thoughtful approach to emerging technologies like AI, VR, and XR, viewing them not as threats but as tools that amplify great teaching.

 

Connect with Kirk Spahn

 

ICL Academy 

ICL Foundation 

LinkedIn 

 

]]> Thu, 2 Jul 2026 12:00:00 +0000 anika@yourbrandamplified.com (Anika Jackson) https://practical-pedagogy-the-art-of-teaching-for-the-future-of-wo.simplecast.com/episodes/kirk-spahn-on-ai-and-the-future-of-learning-6fhhOrZz Kirk Spahn has spent 25 years building schools around passion and character—long before AI became the conversation everyone's having. What struck me in talking with him is that he's not afraid of AI or naive about it. He's asking a different question than most educators: instead of "How do we protect students from AI?" he's asking "How do we prepare students to think critically while using it?" His framework—passion-based learning, character development, real-world application—actually gets stronger with AI, not weaker. If you're a parent, educator, or leader trying to figure out what education should actually look like right now, this is essential listening.

 

In This Episode

  • The origin of ICL Academy in 2001 and passion-based learning
  • Why traditional education was designed for a different era (and why that matters now)
  • How personalization at scale becomes possible through technology—without replacing teachers
  • The "learn-do model": why application and mastery require more than AI-generated answers
  • Why he's building curriculum with "find the flaws" assignments instead of banning AI
  • The immersive potential of VR/XR in education—and why it still needs a human guide
  • His three-pillar framework: inspire, educate, impact
  • Why "dare to dream" and "courage to risk" are non-negotiable for the next generation

 

Timestamps

  • 00:00 Introduction: Education and AI in the modern era
  • 02:12 The founding of ICL Academy in 2001 and passion-based learning
  • 05:37 ICL Academy's educational approach and personalization
  • 13:40 Early stage AI use in education and critical thinking
  • 20:51 Balancing AI and human elements in learning
  • 22:17 Building curriculum with "find the flaws" AI exercises
  • 26:16 Emerging technologies: XR/VR for immersive learning
  • 27:37 Exploring and piloting virtual labs and simulations
  • 31:32 Core educational principles: "Respect tradition, embrace tomorrow"
  • 34:15 Dare to dream, courage to risk, and leadership through action
  • 38:25 Closing thoughts on preparing the next generation

 

Key Insights & Takeaways

 

Insight 1: AI Amplifies Great Teaching—It Doesn't Replace It

 

The fear that AI will make teachers irrelevant misses the point entirely. What AI actually does is free great teachers from administrative burden so they can spend time in meaningful one-on-one conversations with students. The human elements—mentorship, dialogue, knowing your students deeply—remain irreplaceable. Technology is a stage; the teacher is still the performer.

 

Insight 2: Engagement Is the Single Greatest Detriment (and Opportunity) in Modern Education

 

Students don't disengage because education is too hard. They disengage because it's disconnected from what they care about. When a tennis player learns physics through serving, when a musician explores math through acoustics, engagement transforms. Personalization isn't innovative—it's obvious. The barrier was always logistics, which technology can now solve.

 

Insight 3: We're in AI 1.0—Teaching Critical Thinking Matters More Than Banning It

 

Comparing AI to the early internet or the first calculators, Kirk argues we're at day one. Yes, students can use it to cheat. Yes, it gets things wrong. But the answer isn't restriction—it's teaching students to interrogate AI outputs, to find flaws, to understand both its power and its limitations. This generation will work with AI their entire careers; they need to learn how to use it as a tool, not a shortcut.

 

Insight 4: Mastery Requires Application Beyond Information

 

AI can provide information instantly. But retention, understanding, and mastery come through the "learn-do model"—learning something and then applying it to what you're passionate about. A student can get an AI-generated answer to a math problem; mastery happens when they apply that math to solve a real problem in their life.

 

Insight 5: Certain Subjects Require Limiting AI to Protect Authentic Learning

 

Just as some math classes prohibit calculators while others require them, some courses at ICL intentionally limit AI use. Leadership classes, for example, require deep personal reflection that can't be outsourced. The strategy isn't "no AI ever"—it's thoughtful decisions about when technology serves learning and when it gets in the way.

 

Insight 6: The Future of Education Is Hybrid, Not Either/Or

 

Traditional schools won't disappear. But the future includes more flexibility, more personalization, more opportunities for students to learn outside four walls. Athletes need training time. Musicians need practice schedules. Why force all learning into an 8am-3pm box? Technology makes hybrid models possible—but only if we design them around student identity, not efficiency.

 

Why This Matters Now

Education is at an inflection point. We can double down on the industrial model—standardized tests, one-size-fits-all curriculum, AI as a replacement for teachers. Or we can use technology to finally do what we've always known works: meet students where they are, connect learning to their passions, and develop not just their minds but their character. Kirk's 25-year track record suggests the second path isn't just more humane—it's more effective.

 

Resources & Links Mentioned

  • ICL Academy — Passion-based online learning for students with demanding schedules 
  • ICL Foundation — Character development and educational innovation 
  • Virtual Reality in Education — Meta Campus and XR/VR learning experiences
  • International Baccalaureate (IB) — Global educational framework

 

About Kirk Spahn

A fourth-generation educator and founder of ICL Academy and the ICL Foundation, Kirk Spahn has spent over 25 years pioneering passion-based learning models that prioritize student identity and character alongside academics. Growing up in an International Baccalaureate family, he recognized early that education must look at the person first—creating critical thinkers prepared for real-world challenges. As one of the earliest pioneers of online private education in the U.S., Kirk built ICL to serve high-performing students (junior athletes, musicians, performers) whose passions demand flexibility traditional schools cannot provide. His guiding principle—"Respect tradition, embrace tomorrow"—defines his strategic, thoughtful approach to emerging technologies like AI, VR, and XR, viewing them not as threats but as tools that amplify great teaching.

 

Connect with Kirk Spahn

 

ICL Academy 

ICL Foundation 

LinkedIn 

 

]]> Kirk Spahn on AI and the Future of Learning Anika Jackson 00:39:58 Kirk Spahn's vision fundamentally challenges the traditional education model, which he argues was designed for a different era and fails to meet the needs of modern learners with diverse passions and ways of engaging with knowledge. At the heart of Spahn's mission lies a conviction that transformative education requires three interconnected pillars: inspire, educate, and impact. He believes the greatest challenge facing modern education is not technology but engagement—the ability to connect students to learning that matters to them personally. Kirk Spahn's vision fundamentally challenges the traditional education model, which he argues was designed for a different era and fails to meet the needs of modern learners with diverse passions and ways of engaging with knowledge. At the heart of Spahn's mission lies a conviction that transformative education requires three interconnected pillars: inspire, educate, and impact. He believes the greatest challenge facing modern education is not technology but engagement—the ability to connect students to learning that matters to them personally. ai, ai pedagogy, ai ethics, ai career, ai in education false full 1 00434c58-ebe1-447a-a0f1-fd2a37059a7d Trailer Thank you for finding the show! Please save and subscribe to listen to our first episode, coming out July 2!

]]> Sat, 27 Jun 2026 01:48:37 +0000 anika@yourbrandamplified.com (Anika Jackson) https://practical-pedagogy-the-art-of-teaching-for-the-future-of-wo.simplecast.com/episodes/trailer-FTholaq8 Thank you for finding the show! Please save and subscribe to listen to our first episode, coming out July 2!

]]> Trailer Anika Jackson 00:00:36 Welcome to Practical Pedagogy. I'm Professor Anika Jackson. The question isn't whether AI belongs; it's already here. The real question is: how do we guide students and workers to use it thoughtfully, ethically, and strategically? Every week, I'll interview students, educators, researchers, and industry voices to explore the real strategies, frustrations, and breakthroughs happening in classrooms and beyond. We'll talk through what the art of teaching for the future of work actually looks like. Welcome to Practical Pedagogy. I'm Professor Anika Jackson. The question isn't whether AI belongs; it's already here. The real question is: how do we guide students and workers to use it thoughtfully, ethically, and strategically? Every week, I'll interview students, educators, researchers, and industry voices to explore the real strategies, frustrations, and breakthroughs happening in classrooms and beyond. We'll talk through what the art of teaching for the future of work actually looks like. false full 0