What does the Catholic Church actually think about artificial intelligence? A lot more than you might expect.

In this episode of A Beginner’s Guide to AI, Prof. GepHardT explores the Vatican’s surprisingly sharp position on AI ethics, human dignity, deepfakes, truth, and the growing risk of letting machines replace judgment rather than support it. This is not a sermon against technology, and it is not a blessing over every shiny new model either. It is a serious look at AI as a human tool that can do real good, but only if it stays in its place.

For business professionals, founders, marketers, and executives, this conversation goes far beyond religion. It gets to the core of responsible AI, AI governance, human centered AI, and the hidden cost of outsourcing thought. We look at why the Catholic Church and AI belong in the same debate, what the Vatican says about simulation, synthetic media, and trust, and why overreliance on AI can slowly reshape how people think, decide, communicate, and relate to one another.

You will hear why the Church draws such a hard line between human intelligence and artificial intelligence, why dignity matters more than efficiency, why deepfakes are about more than online deception, and why concentrated AI power should concern anyone who cares about work, leadership, media, or democracy. The episode also touches on healthcare, education, autonomous weapons, and the broader anthropological challenge of AI: not just what machines can do, but what humans become while building and using them.

If you are interested in Catholic Church and AI, Vatican AI ethics, AI and human dignity, deepfakes and trust, AI overreliance, and AI governance, this episode gives you a clear and provocative framework for thinking about the future.

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• “Servant, not master; instrument, not idol; support act, not replacement.”
• “Tools always train their users.”
• “Use the machine, do not become like it.”

00:00 Why the Vatican Takes AI Seriously

02:34 Human Intelligence vs Artificial Intelligence

05:21 Human Dignity in an Age of Optimization

08:07 Deepfakes, Voices, Faces, and the Crisis of Trust

11:02 Why AI Overreliance Changes How We Think

14:06 Power, Warfare, and the Human Future of AI

Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com

🎧 Thanks for listening to A Beginner’s Guide to AI.

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In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with Jonathan Fraine and Raja Amelung about why human knowledge still matters in the age of LLMs. Together they explore Wikipedia, Wikimedia, AI hallucinations, trust in AI, free knowledge, and the future of reliable information online.

This is not another generic AI hype conversation. It is a grounded discussion about what happens when people confuse fluent machine output with verified truth. Jonathan and Raja explain why Wikipedia still depends on human editors, why source verification matters, how Wikimedia thinks about AI, where small language models may actually be useful, and why the future of knowledge should not be left to black box systems alone.

✨ Why Wikipedia cannot simply be replaced by generative AI

✨ What AI hallucinations reveal about trust and knowledge

✨ How Wikidata and small language models can support search without pretending to be truth

✨ Why free knowledge and attribution matter in an AI economy

✨ What younger users may value about Wikipedia in an age of tracking and AI summaries

✨ Why critical thinking matters more than ever

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💬 “Knowledge is human.”

💬 “You can always start your research on Wikipedia, but you should never end there.”

💬 “The biggest problem is the trust in the source.”

00:00 Why Human Knowledge Still Matters in the Age of AI

03:17 Small Language Models, Wikidata, and Better Search

06:14 Why Wikipedia Does Not Want AI Written Articles

13:49 Free Knowledge, Attribution, and AI Companies Using Wikipedia

21:06 Trust, Search, and the Future of Wikipedia in an AI World

35:43 Personal AI Use Cases, Risks, and the Limits of Automation

40:08 Worst Case Scenarios for AI, Trust, Bias, and Human Judgment

🔗 Jonathan Fraine: linkedin.com/in/jonathan-fraine

🔗 Raja Amelung: linkedin.com/in/raja-amelung-088890a

🔗 Wikimedia Deutschland: wikimedia.de

🔗 Wikimedia World: commons.wikimedia.org

Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com

Hosted on Acast. See acast.com/privacy for more information.

AI is no longer just a chatbot that helps you write emails faster. In this episode of Beginner’s Guide to AI, Dietmar Fischer sits down with Ethan Ouyang to explore how agentic AI is changing the way businesses are built, managed, and scaled. Ethan is publicly identified with ATOMS, and the platform’s official site is atoms.dev, where it is described as a multi-agent AI workflow for building products without code.

This conversation goes far beyond simple prompting. Ethan explains how AI agents can work together like a business team, handling research, planning, product creation, workflow automation, iteration, and even revenue optimization. The result is a shift from “vibe coding” to something much bigger: building real businesses with AI.

✨ Why ChatGPT-level use cases are only the beginning

✨ How AI agents can support founders, solo operators, and managers

✨ Why judgment, taste, and domain knowledge still matter

✨ What it means to become an AI native company

✨ How leadership changes when your team includes AI workers

✨ Why custom AI tools may beat bloated SaaS products

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Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com

“Atoms is fundamentally different. This is not code. It is decision.”

“You have a team, not just an engineer.”

“The trivial work, the tedious work, should belong to AI.”

00:00 Welcome and what ATOMS actually does

02:26 From prompting AI to building a real business

05:33 Why AI agents matter more than coding alone

10:18 Who uses ATOMS: founders, managers, and operators

13:03 How to integrate AI agents into real workflows

23:22 Leadership, hiring, and managing AI workers

27:13 The future of agentic AI and autonomous systems

31:37 What an AI native company looks like

35:18 China, the US, and the AI application race

40:03 Safety, the Terminator question, and responsible AI

42:14 Where to find Ethan and ATOMS

Platform: ATOMS.dev

Company: DeepWisdom.AI

X: com/atoms_dev

YouTube: youtube.com/@atoms_dev

LinkedIn: Ethan Ouyang

🎵 Music credit: "Modern Situations" by Unicorn Heads

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Human-Centered AI at Work with Monica Marquez: A Practical Adoption Playbook

If you’re still treating AI like a shiny gadget, this episode will be a polite intervention.Monica Marquez (Flipwork) shows how to build a human-centered AI adoption playbook that actually sticks.We dig into AI as a partner, not a tool; psychological safety for teams; and the one-workflow-per-month rule that turns experimentation into measurable AI ROI.You’ll learn how to avoid work slop, build agentic workflows, and translate machine output into authentic intelligence that reflects your expertise. 🤖

What you’ll learn

• Shift identity first: “I experiment with AI daily.”
• Redesign workflows before adding tools.
• Create psychological safety so teams can try, fail, and improve.
• Kill work slop and layer your context for quality.
• Build agentic workflows that scale judgment and consistency.
• Track time saved and quality gains to prove ROI.

📧💌📧 Tune in to get my thoughts and all episodes, don’t forget to subscribe to our Newsletter.📧💌📧

Quotes from the Episode

• “The real danger isn’t killer robots. It’s disengaged humans.”
• “Don’t ship work slop. Turn artificial intelligence into your authentic intelligence.”
• “Redesign your workflow first, then layer AI. Otherwise you just automate the old mess.”
• “Stop treating AI like a tool. Treat it like a partner.”
• “Adoption starts with identity: I experiment with AI every day.”
• “Use AI for five-dollar tasks so you can solve five-thousand-dollar problems.”

Chapters

00:00 Welcome, who is Monica Marquez and what is Flipwork

02:59 AI as a partner, not a tool

05:34 Practical example: recruiting, prompts, and human judgment

07:02 Generational beliefs, “artificial intern,” and mindset shifts

11:24 From effort to impact: redefining success with AI

12:46 Redesigning workflows before layering AI

14:44 Psychological safety and daily experiments

16:55 Leaders model usage, run side-by-side experiments

18:37 Avoiding “work slop” and building authentic intelligence

21:44 Doing more of your “zone of genius” with AI

24:39 The one-workflow-per-month rule

29:25 Industry adoption patterns, lessons from Blockbuster vs Netflix

33:12 Personal AI use cases and voice-based workflows

36:32 Matrix, Terminator, and Monica’s real fear: disengaged humans

37:58 Where to find Monica and Flipwork

Where to find Monica Marquez

• Her Agency: Flipwork
• Monica’s site: themonicamarquez.com
• Newsletter: Ay Ay Ay, AI

• 
  

About Dietmar Fischer

Host of Beginner’s Guide to AI. Economist and digital marketer helping teams turn AI from hype into workflows.Training, talks, and courses with thousands of participants. 🎙️

Go to argoberlin.com to see how we can help you!

Music credit: “Modern Situations” by Unicorn Heads 🎵

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In this episode of A Beginner’s Guide to AI, Dietmar Fischer talks with Alex Levin, the Co-Founder and CEO of Regal.io, about how Voice AI is bringing real human conversation back to customer service.

For years, businesses have been hiding behind IVRs and chatbots - cutting off the personal touch that customers crave. Alex explains how AI voice agents are transforming the experience, allowing brands to actually talk to their customers again, at scale, with empathy, emotion, and precision.

We dive into what’s behind this transformation - from the technology (OpenAI, Google, Anthropic, ElevenLabs, Deepgram) to the psychology of trust and emotion in customer communication. Alex shares how Regal.io helps enterprises in healthcare, insurance, and finance use AI-powered voice agents that can outperform human representatives while lowering costs and improving satisfaction.

From replacing call center frustration with warm, natural conversations to the rise of empathetic AI agents, this episode explores what happens when voice meets intelligence.

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Tune in to get my thoughts and all episodes — and don’t forget to subscribe to our Newsletter: beginnersguide.nl

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Quotes from the Episode

“If a customer wants to talk to you, you’re lucky - and if they want to do it by voice, you should let them.”

“The personalization possible with AI agents is more human than humans.”

“Everyone told me voice was dead - they were wrong.”

CHAPTERS

00:00 Introduction - Why Voice AI Is Making a Comeback

00:54 Alex Levin’s Journey from Startups to Voice AI

03:42 “Voice Isn’t Dead” - The Moment That Sparked Regal.io

06:25 How Voice AI Actually Works Behind the Scenes

08:47 Using AI Agents to Talk to Customers at Scale

10:58 Data, Scripts, and What Makes a “Good” AI Conversation

13:33 Legal Hurdles and Privacy in Voice AI

15:50 Why Healthcare and Insurance Are Early Adopters

18:26 How Customers React When They Realize It’s an AI

21:12 Real Use Cases - From Banks to Everyday Services

24:19 Human in the Loop: When AI Hands Over to People

26:55 Can Small Businesses Afford Voice AI Yet?

28:48 The AI Startup Boom and Smarter Investment Strategies

32:20 Leadership in the Age of AI - New Skills, New Metrics

35:12 Why Young Professionals Must Learn AI Tools Now

37:45 How Alex Personally Uses AI (and Where It Saves Time)

39:24 The “Terminator Question” - Should We Be Worried?

42:08 Closing Reflections and Where to Find Regal.io

Where to Find Alex Levin

🌐 Website: www.regal.io

🧑🏻 LinkedIn: Alex Levin

🎙 About Dietmar Fischer:

Dietmar is a podcaster, AI marketer, and economist from Berlin.

If you want to get your AI or your digital marketing going - just contact him at Argoberlin.com!

🎵 Music credit: “Modern Situations” by Unicorn Heads

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In this episode, Dietmar Fischer talks with Tallulah Le Merle, a humanist technologist and investor, about how to think clearly in the age of AI without falling into doomsday panic or blind optimism. You’ll get a practical mental model of the AI stack, a grounded take on AI alignment risk, and a refreshing argument for hope as a strategic posture that shapes what gets built. 🤖🌍🧠

What you’ll learn

✅ Why fear based AI narratives can freeze action and distort decisions

✅ How the future of work may shift from routine cognitive tasks to deeper human capabilities

✅ The overlooked forms of intelligence AI cannot easily replace somatic, ecological, communal

✅ How AI investing works in early stage startups and what responsible due diligence looks like

✅ The AI stack explained simply infrastructure, model layer, application layer

✅ What agentic AI means today and where it is heading

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About Dietmar Fischer

Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com 🌱🚀

Chapters

00:00 Meet Tallulah Le Merle and why “hope” is her AI stance

03:52 Fear narratives vs hope as a practical posture

08:06 Disruptive to what Rethinking modern work and human thriving

10:14 Jobs replaced vs jobs created and the transition problem

12:36 What’s left for humans Somatic ecological and communal intelligence

18:47 The humanist builder and why ethics should unlock capital

28:55 The AI stack explained infrastructure model layer application layer

32:30 Why apps and agents are the near-term investment boom

40:32 The alignment problem Terminator narratives and the futures we build

46:12 Fantasy, imagination, and why it matters for tech trajectories

49:36 Where to find Tallulah and the upcoming book

Quotes from the Episode

💬 “AI is a tool. And like a hammer. Hammer, you could use it to build a house or as a murder weapon.”

💬 “Hope is this sliver of openness to the possibility that something good could happen.”

💬 “Disruptive to what Actually, a lot of the way we live and work and operate as humans today is dystopian.”

💬 “It forces us to ask these existential questions, like, what is a human”

💬 “I actually think it should be a prerequisite for unlocking capital.”

💬 “We are so early We’re in inning one of a nine inning baseball game.”

Where to find Tallulah

🔗 LinkedIn: linkedin.com/in/tallulahlemerle

🔗 Website: tallulahlemerle.com

🔗 Updates on her book: don't forget to follow her on LinkedIn 🚀

Music credit: "Modern Situations" by Unicorn Heads

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🎙️ In this episode of Beginner’s Guide to AI, Dietmar Fischer sits down with Torrey Leonard, CEO of Thoughtly, to unpack the real business use case for voice AI agents: follow up with every lead, qualify fast, and hand the best conversations to humans.

If your funnel generates thousands of leads, the bottleneck is not “lack of interest.” It’s speed, timing, and the grind of dialing. Torrey explains how Thoughtly’s AI phone agents call inbound leads, answer initial questions, build rapport, and then transfer the call to a licensed human closer. Humans stay in the loop for the big life decisions. The AI handles the repetitive first steps that burn out teams.

You will also learn:

✅ Why voice beats typing as the fastest interface for human communication

✅ Why customer service voice AI is harder than sales and lead qualification

✅ How onboarding works with CRM integrations like Salesforce and HubSpot

✅ Why A/B testing matters before ramping to 100% lead volume

✅ Why the “moat” is orchestration, workflows, and guardrails, not just a great voice model

✅ What agentic AI and omni-channel “next best action” looks like next

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About Dietmar Fischer: Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com

Chapters

00:00 From Minecraft to voice first AI and the origin of Thoughtly

02:44 What Thoughtly does AI calls that qualify and transfer to humans

07:45 Trust, disclosure, and why customer service voice AI is so hard

12:50 Scaling across verticals dialects and the model orchestration stack

18:12 Onboarding CRM integrations and A/B testing to 100% volume

28:21 The next wave autonomous agents OpenClaw and a sane take on AI risk

Quotes from the Episode

• “After 90 seconds we’ve got a great rapport built. Boom, transferred over to a licensed agent.”
• “The voice isn’t the unique selling proposition. It’s the orchestration of the whole stuff.”
• “Nobody needs to worry about the Terminator scenario, unless we humans build Terminator.”

Where to find the Guest

🌐 Thoughtly: thoughtly.com

🔗 Torrey Leonard on LinkedIn: linkedin.com/in/torrey-leonard/

Music credit: “Modern Situations” by Unicorn Heads

Hosted on Acast. See acast.com/privacy for more information.

🎧 What makes us human in the age of AI?

This episode of A Beginner’s Guide to AI explores one of the most important questions for business leaders today. As AI becomes more capable, the real challenge is not what it can do, but what we should never outsource.

We explore The Blurring Test, a fascinating experiment where thousands of people tried to prove their humanity to a chatbot. What they revealed changes how we should think about AI, business, and identity.

You will learn why AI can mimic humans but cannot experience reality, why human judgment becomes more valuable in an automated world, and how to use AI without losing authenticity and meaning.

📧💌📧

Tune in to get my thoughts and all episodes, don't forget to ⁠subscribe to our Newsletter⁠: ⁠beginnersguide.nl⁠

📧💌📧

👤 About Dietmar Fischer:

Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at https://argoberlin.com/

• "AI can follow the recipe, but it cannot taste the cake."
• "Your humanity is not what you do, but why you do it."
• "The real risk is not AI replacing us, but us becoming more like AI."

00:00 The Question That Changes Everything

04:30 The MrMind Experiment

11:20 AI vs Human Identity

19:10 The Cake Test Explained

26:40 AI in Business and Decision Making

34:00 What Makes Us Human

🚀 This episode challenges how you think about AI, business, and yourself. The future will not be about replacing humans. It will be about understanding what makes us irreplaceable.

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