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421 afleveringen, van nieuw naar oud
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The Next Evolution Isn't Artificial Intelligence. It's Hybrid Intelligence - Says Rana Gujral
22 juli 2026 · 56 min
AI and human decision-making are becoming inseparable, but the greatest danger may not be job replacement. It may be the gradual loss of our ability to think, choose, and disagree for ourselves. Lees meer
In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Rana Gujral, CEO of Behavioral Signals and author of The AI Instinct: The Future of AI and Human Decision-Making. Rana challenges the usual debate about whether AI will save humanity or destroy it. The more urgent question is what humans are becoming as intelligent systems participate in our judgment, creativity, relationships, and everyday decisions.
The same AI model can be used in two very different ways. It can help a person discover ideas they would not have reached alone. Or it can eliminate the need for that person to think. One is augmentation. The other is replacement. The distinction may not be obvious. A company can call its process “human-in-the-loop” even when the human merely approves an AI-generated decision. Rana therefore proposes a broader framework: humans, tools, and rules.
Humans contribute values, judgment, goals, context, and accountability. Tools extend memory, perception, calculation, and pattern recognition. Rules determine how both sides interact and who remains responsible when something goes wrong.
The conversation also explores Artificial General Experience, or AGE, Rana’s proposed distinction between intelligence and genuine experience. A system may imitate self-awareness, emotional understanding, or intimacy without possessing an inner life. Fluency is not necessarily consciousness.
Dietmar and Rana discuss:
🧠 Why AI augmentation can gradually become replacement
⚖️ Why human oversight often becomes ceremonial
🤖 The difference between AGI, AI consciousness, and Artificial General Experience
🫥 How convenience can weaken independent judgment
📋 Why humans, tools, and rules must be designed together
🧬 Brain implants, manipulation, consent, and cognitive liberty
🌍 Th…
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Automation Bias - Why “Human in the Loop” May Be a Dangerous Illusion
20 juli 2026 · 33 min
Why Human Oversight in AI Isn’t Enough Lees meer
What happens when an AI system sounds more certain than you feel? Automation bias describes our tendency to trust automated recommendations even when they conflict with evidence, experience or common sense.
In business, healthcare, finance and other high-stakes fields, this trust can quietly turn useful decision support into dangerous dependence. A confident score, recommendation or warning can feel objective, even when the underlying data is incomplete or the model is wrong.
In this episode of A Beginner’s Guide to AI, we examine why people trust AI too much, how automation bias changes human judgment and why simply keeping a human in the loop does not guarantee meaningful oversight.
You will learn the difference between two common failures. A commission error happens when someone follows a bad automated recommendation. An omission error happens when someone overlooks a problem because the system failed to issue a warning.
We also look at automation complacency. When a system works reliably for long periods, people naturally reduce their attention. The machine appears competent, the human becomes passive and the rare failure becomes harder to catch.
A real-world case involving an experimental self-driving Uber vehicle shows how dangerous this combination can become. The system misread the situation, the safety process relied heavily on one human operator and the final opportunity to intervene came too late.
The lesson for businesses is clear. Responsible AI requires more than a final approval button. Employees need enough time, knowledge and authority to question AI outputs. Systems should communicate uncertainty. Unusual cases should receive stronger human review. Leaders must also define who remains accountable when an AI-supported decision goes wrong.
This episode covers automation bias in AI, AI overreliance, human oversight in AI, meaningful human control, automation complacency, AI confidence versus accuracy, re…
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The Next AI Crisis Won’t Be Hallucinations. It Will Be Costs
18 juli 2026 · 9 min
AI agents can conduct research, analyze interviews, retrieve documents, call tools, and complete complex workflows with limited human involvement. But every prompt, response, document, retry, and agent iteration consumes tokens. When nobody monitors that consumption, a valuable AI experiment can quickly become an unexpected business expense. Lees meer
In this episode of The Beginner’s Guide to AI, Dietmar Fischer shares a real example from a university startup. A researcher was developing an AI-supported process for qualitative interview analysis using retrieval-augmented generation, Claude, and a sequence of approximately 70 prompts.
The research was valuable. The bill was also noticeable.
Within one week, the project generated approximately $180 in token costs. That may be acceptable for an important scientific project, but it raises a much larger question: What happens when dozens or hundreds of employees begin running similar AI agents?
📈 AI agents do not behave like occasional chatbot users. They can process large amounts of information, make repeated API calls, use tools, retry failed steps, and continue working through multiple iterations. Poorly configured agents can even enter loops, repeating the same operations until somebody intervenes. Every iteration costs additional tokens.
For businesses selling AI services, this creates a potential problem with fixed-price subscriptions. A customer paying a modest monthly fee may generate API costs that are many times higher than the subscription revenue.
For other companies, the problem is internal. Employees may be encouraged to use AI, but managers may have limited visibility into which teams, models, agents, and workflows are generating the costs.
The solution is not to stop using AI. Employees who barely use the available tools can also hold back productivity and innovation. Companies need to find the right balance between insufficient adoption and uncontrolled consumption.
🔍 In this episode, you will learn:
• …
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Why Small Teams Can Suddenly Beat Large Companies - The Bryan McAnulty Interview
16 juli 2026 · 47 min
AI Agents Are Redefining Knowledge Work. Are You Ready? Lees meer
Most businesses are still using AI to save time. Bryan McAnulty believes that's already the wrong mindset.
In this episode of Beginner's Guide to AI, Dietmar Fischer sits down with Bryan McAnulty, founder of Heights Platform and creator of LatchLoop, to explore why AI agents represent a much bigger shift than ChatGPT and what that means for founders, executives, creators, and knowledge workers.
Together they discuss how AI is transforming software development, why voice is becoming the new interface, how autonomous agents are changing productivity, and why companies should stop thinking about AI as a cost-cutting tool and start using it to create entirely new customer experiences.
Bryan also shares how his own development workflow has changed dramatically, why his team is encouraged to automate repetitive work, and why he believes small companies have an unprecedented opportunity to compete with much larger organizations.
If you're trying to understand where AI is heading over the next few years, this conversation offers practical insights from someone building AI products every day.
In this episode you'll learn:
✅ Why AI agents are different from chatbots
✅ Why most companies focus on the wrong AI problem
✅ How AI is changing software development
✅ Why human expertise becomes more valuable, not less
✅ Why voice may replace typing sooner than you think
✅ How founders should rethink AI strategy
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Tune in to get my thoughts and all episodes.
Don't forget to subscribe to the Beginner's Guide to AI Newsletter:
👉 https://beginnersguide.nl
📧💌📧
About Dietmar Fischer
Dietmar Fischer is a podcaster, AI strategist, and digital marketer based in Berlin.
Through Beginner's Guide to AI, he speaks with founders, researchers, and business leaders about the real-world impact of artificial intelligence.
If you'd like support with AI strategy or digital marketing:
👉 https://argoberlin.com
💬 Quotes from …
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We Are In A Trust Recession, Says Alice Sesay Pope
14 juli 2026 · 52 min
Generative AI trust is becoming one of the biggest leadership challenges in business. Lees meer
In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Alice Sesay Pope, author of The Trust Algorithm: How Leaders Build Trust with Generative AI, about why AI success cannot be measured only by speed, automation, or cost reduction.
Alice describes a growing “trust recession” where customers are unsure whether brands are acting in their best interest, employees are unsure whether AI will help or replace them, and leaders are under pressure to prove AI ROI before they have built the right strategy, governance, and human oversight.
The conversation explores why AI customer service often disappoints, why bad data can mislead both chatbots and human agents, and why companies should not deploy generative AI just to say they are using it.
You will also hear why leaders need to think about token costs, risk, guardrails, change management, psychological safety, reskilling, and privacy before scaling AI across the business.
This episode is for founders, executives, consultants, marketers, customer experience leaders, and anyone trying to understand how to use generative AI responsibly without losing customer trust.
Key Takeaways
Why we are entering a generative AI trust recession
Why AI customer service can damage brand loyalty
Why AI ROI fails when leaders focus only on cost cutting
Why human oversight and verification still matter
Why reskilling employees is a leadership responsibility
Why agentic AI creates new trust and privacy questions
Why companies need AI governance before scaling AI
Get My Newsletter
📧💌📧
Tune in to get my thoughts and all episodes. Don't forget to subscribe to our Newsletter:
https://beginnersguide.nl
📧💌📧
About Dietmar Fischer
Dietmar Fischer is a podcaster and AI marketer from Berlin.
If you want help with AI strategy or digital marketing, visit:
https://argoberlin.com
Quotes from the Episode
“We are in a trust recession.”…
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Cognitive Surrender: The Scariest AI Problem Isn't Job Loss
12 juli 2026 · 32 min
🎙️ The Hidden Cost of AI Productivity | Why AI Literacy Will Become Your Biggest Competitive Advantage Lees meer
Artificial intelligence is making us more productive than ever before. We write emails in seconds, summarise reports instantly and generate ideas with a single prompt. But what if that productivity comes at a hidden cost?
In this episode of Beginner's Guide to AI, Prof. GePhardT explores one of the most overlooked challenges of the AI revolution: AI literacy. Are we using AI to become better thinkers, or are we slowly outsourcing our ability to think critically?
Inspired by recent research into workplace literacy and artificial intelligence, this episode examines how AI is changing the relationship between knowledge, reading and human judgement. You'll discover why experts warn about cognitive surrender, why AI may be hiding a growing literacy crisis, and why critical thinking is becoming one of the most valuable business skills of the AI era.
Whether you're a founder, executive, marketer, entrepreneur or simply fascinated by the future of work, this episode offers practical insights into using AI as a powerful thinking partner instead of a replacement for human judgement.
🚀 In this episode you'll discover
✅ Why AI may be hiding a literacy crisis instead of solving it
✅ What cognitive surrender really means
✅ Why AI literacy is becoming a competitive advantage
✅ Why reading and critical thinking matter more than ever
✅ How to combine AI productivity with better decision making
✅ Practical ways to use ChatGPT without becoming dependent on it
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Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter:
👉 https://beginnersguide.nl
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👨💼 About Dietmar Fischer
Dietmar Fischer is a podcaster and AI marketer from Berlin. Through his podcast Beginner's Guide to AI, he helps businesses and AI beginners understand artificial intelligence without hype or unnecessary complexity.
If you'd like help introducing AI into your m…
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Why AI Destroys The Web We Know // Dietmar's Optinion
10 juli 2026 · 13 min
🚨 AI didn't kill my first business. It killed the reason people had to visit it. Lees meer
For years, I ran a successful travel blog about Cuba. Like millions of creators, bloggers and publishers, my business depended on people finding my articles through search engines. Then AI changed everything.
Large Language Models and AI search tools can now answer many questions without ever sending visitors to the original source. That doesn't just change search. It changes the entire business model of the internet.
In this solo episode of Beginner's Guide to AI, I share my personal experience of losing one content business because of AI while building another with AI. More importantly, I explain why I believe we're witnessing the beginning of a much larger shift that will affect content creators, publishers, marketers, agencies and businesses everywhere.
The real challenge isn't that AI can generate content.
The real challenge is that it removes the economic incentive for humans to create original knowledge.
If fewer experts publish their experiences, AI systems will eventually have fewer high-quality sources to learn from. The result could be a slow decline in the quality of information across the web.
🎯 In this episode you'll learn:
✅ Why AI search is changing the economics of publishing
✅ Why the traditional content business model is breaking down
✅ How my Cuba travel blog became an unexpected case study for AI disruption
✅ Why websites built purely on advertising and Google traffic are becoming increasingly vulnerable
✅ Why products and services are more resilient than content-only businesses
✅ How newsletters and owned audiences become strategic assets in the AI era
✅ Practical strategies every creator, entrepreneur and marketer should consider today
✅ Why human experience may become one of the internet's most valuable resources
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Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: https://beginn…
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The 80/20 Rule of AI Transformation - Hirak Chakraborty
7 juli 2026 · 51 min
Why AI Transformation Is Mostly Not About Technology Lees meer
AI transformation is not really about technology. It is about mindset, leadership, and the ability of organizations to change before the world changes around them.
In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with Hirak S Chakraborty about why AI is moving faster than most companies expected, why big organizations often struggle to adapt, and why the real challenge is not access to tools but the willingness to rethink how work gets done.
Hirak brings the perspective of an investor, board member, IT advisor, and business strategist. He explains why the 80/20 rule of digital transformation matters more than ever: 80% is organizational change management, only 20% is technology.
This conversation also explores Big AI, China’s innovation under constraint, the democratization of AI tools, the risk of platform consolidation, and the future of work in an AI-driven economy.
🎧 In this episode, you’ll learn:
Why most AI transformations fail before the technology even matters
Why legacy thinking blocks innovation
Why startups often adapt faster than large companies
How AI may democratize opportunity across the world
Why Big AI creates both promise and danger
What business leaders should understand about AI adoption
Why AI agents and core platforms may reshape everyday work
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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, contact him at argoberlin.com
Quotes from the Episode
“It is not about size, it is not about restriction, it’s about mindset, change management.”
“Most of the things I have seen, it’s the legacy, which is treated as a process rather than a burden.”
“We never thought that the progress will be this fast. Nobody thought.”
Chapters
00:00 Why AI Feels Like a His…
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Building On Just One LLM? You Might Be Up For A Surprise - Dietmars Sunday Night Thoughts
5 juli 2026 · 12 min
🤖 When Governments Can Switch Off AI: The New Risk for Business Lees meer
AI is becoming business infrastructure, but most companies still treat it like a simple software subscription. This episode of The Beginner’s Guide to AI looks at a risk many founders, marketers, executives, and small businesses are not taking seriously enough: what happens when your favourite AI model is suddenly unavailable?
Dietmar Fischer explores the growing problem of AI model dependency, LLM vendor lock-in, provider outages, government intervention, and the hidden fragility inside many AI workflows. The starting point is simple but uncomfortable: if your business process depends on one model, one provider, one account, or one cloud infrastructure layer, then your AI strategy may be far more fragile than you think.
This is not about rejecting AI. It is about using AI more intelligently. The episode explains why companies do not always need the “best” AI model for every task. In many real business cases, the context, the data, the workflow, and the ability to switch between models matter more than raw benchmark performance.
That opens the door to multi-model AI strategies, model-agnostic tools, independent AI interfaces, backups, open standards, and practical contingency planning.
In this episode, you will hear about:
🤖 Why AI model dependency is becoming a serious business risk
🔒 How LLM vendor lock-in can limit flexibility and increase exposure
⚠️ Why governments, outages, and pricing changes can affect your AI stack
🧠 Why the best AI model is not always necessary for everyday business tasks
🔁 How model switching and API flexibility can protect your workflows
💾 Why backing up your chats, project folders, agents, and custom GPTs matters
🏢 Why SMEs, startups, and agencies should think about AI operational resilience now
🌍 How European, Chinese, Indian, Korean, open source, and independent AI models fit into the bigger picture
If you use ChatGPT, Claude, Gemini, Copilot, custom GPTs, …
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Be curious and get rid of the fear: Bala Muthiah on AI Leadership // REPOST
3 juli 2026 · 47 min
AI adoption is not only a technology shift, it is a leadership and culture shift. In this episode, Dietmar Fischer talks with Bala Muthiah about AI leadership, the psychology behind AI resistance in the workplace, and the practical steps leaders can take to turn curiosity into day to day usage. Lees meer
Bala shares why the human aspect still decides outcomes, even when the tools feel magical. You will learn how leaders can reduce fear, build confidence, and guide teams through real AI upskilling strategy instead of one off trainings that never translate into workflows. The conversation also touches on industry differences, including why sensitive domains like healthcare raise the bar for responsible AI adoption, and what the rise of agentic workflows means for the future.
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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 argoberlin.com
🎧 Chapters
00:00 Welcome and why AI is a leadership moment
02:12 AI leadership in 2026: pressure, performance, and opportunity
04:41 The real barrier: fear, skepticism, and AI resistance at work
07:45 Industry realities: healthcare, sensitivity, and responsible adoption
17:50 A practical framework: upskilling people and building confidence
34:49 The next wave: agentic workflows and what leaders should prepare for
41:43 Where to find Bala and closing thoughts
💬 Quotes from the Episode
- “And to me, it’s still human, meaning us, we are still humans, leaders are still humans. The human aspect still stays.”
- “Again, I’m coming back to the people, like, because that’s gonna be the unlock for you. Upskill your people with AI tools.”
- “AI being, like, the car, or being the internet, being …
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The Matrix Asked the Question. Nick Bostrom Tried to Answer It.
1 juli 2026 · 34 min
🤖🧠💻 Could reality itself be software? Lees meer
What if The Matrix wasn't just brilliant science fiction, but a serious philosophical possibility?
In this episode of A Beginner's Guide to AI, Professor Gep-Hardt explores the Simulation Hypothesis, one of the most fascinating ideas in modern philosophy. Inspired by philosopher Nick Bostrom's famous argument, we ask whether our entire universe could actually be an unimaginably advanced computer simulation.
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Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter:
👉 https://beginnersguide.nl
📧💌📧
You'll discover why this idea has captured the attention of philosophers, physicists and AI researchers around the world. We separate science from speculation, explore the famous simulation argument, examine attempts to test the hypothesis using physics, and discuss why advances in artificial intelligence have made this debate more relevant than ever.
Along the way, we'll explain complex ideas using simple examples, explore what AI teaches us about consciousness and reality, and ask whether future civilizations might one day possess enough computing power to simulate entire universes.
If you're interested in artificial intelligence, philosophy, future technology or simply enjoy asking big questions, this episode is for you.
🎯 In this episode you'll discover
✅ What the Simulation Hypothesis actually is
✅ Nick Bostrom's famous trilemma
✅ Why AI is bringing this debate back into focus
✅ How scientists have tried to test the hypothesis
✅ What critics such as Sabine Hossenfelder argue
✅ What today's physics really says
✅ Why this thought experiment matters for AI, business and society
🙏 P.S. A special thank you to Diana Carter from Interview Valet for suggesting today's topic. It turned into one of the most thought-provoking episodes we've ever explored.
💬 Quotes from the Episode
"Good science doesn't simply ask strange questions. It asks whether strange questions can produce measurable…
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79% of failures are completely invisible - Moritz Sudhof Explains
29 juni 2026 · 57 min
Artificial Intelligence is getting smarter every month. Models can pass exams, write code, summarize documents, and even outperform humans in specific tasks. Yet according to Moritz Sudhof, one of the biggest risks in AI today has very little to do with intelligence. Lees meer
Moritz is the co-founder of BigSpin.ai and a former VP of AI at BetterUp, where he helped build AI-powered coaching systems. His research focuses on a surprising problem: most AI failures are not obvious. In fact, BigSpin's research found that 79% of AI failures are invisible to users. The AI appears helpful, sounds confident, and produces convincing outputs, but users often walk away with incorrect assumptions, incomplete information, or entirely wrong conclusions without realizing it.
In this episode, we explore why AI hallucinations are only part of the problem. Moritz explains why the real challenge lies in the interaction between humans and AI. He shares how conversational failures emerge, why expert AI users actually encounter more failures than beginners, and why trust may become the defining challenge of the AI era.
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Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl
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We also discuss the seven hidden failure patterns that appear repeatedly across AI systems, including the Confidence Trap, Death Spiral, Silent Walk Away, and other interaction failures that impact AI agents, copilots, and enterprise AI deployments.
Towards the end of the conversation, we explore a fascinating question: what is the real long-term risk of AI? Moritz argues that the biggest danger may not be superintelligent machines taking over the world, but humans gradually outsourcing their judgment and decision-making to systems they trust too much.
In this episode, you'll learn:
• Why 79% of AI failures go unnoticed
• The difference between AI…
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AI Or Not AI // Dietmar's Opinion
28 juni 2026 · 11 min
🤖 AI or Not AI: Why Businesses Cannot Ignore AI Without Losing Their Edge Lees meer
AI is no longer a futuristic question for businesses. It is already part of how companies write, research, plan, automate, market, and make decisions. But the real question is not simply whether to use AI. The real question is how to use AI without becoming dependent on it, without ignoring its costs, and without letting it weaken human judgment.
In this episode of Beginner’s Guide to AI, Dietmar Fischer takes a personal and critical look at the question: AI or not AI? The answer is not a naive “yes” and not a nostalgic “no.” AI is a powerful tool, and businesses that ignore it may end up like organizations that ignored computers, printing presses, or other major technologies. But using AI blindly creates its own risks.
The episode looks at the environmental impact of AI, including energy and water use, the possible effects of AI on jobs and inequality, and the political consequences of large-scale unemployment. It also explores why AI ethics cannot be reduced to simple slogans. Bias, discrimination, monopolies, and concentration of power are real problems, but banning AI is not a serious business strategy.
A central theme is AI deskilling. If people ask AI everything, they may slowly lose the ability to think, evaluate, and decide for themselves. For business leaders, marketers, and founders, this is not a minor issue. AI can improve productivity, but it can also hide errors, produce convincing nonsense, and make teams less critical if they stop questioning the output.
Key highlights from the episode:
🤖 Why businesses cannot simply ignore AI
⚡ The ecological cost of AI and why sustainable AI matters
👥 How AI may affect jobs, inequality, and reskilling
🧠 Why AI literacy and critical thinking are now business skills
⚠️ The risk of AI deskilling and hidden AI errors
🏢 Why responsible AI adoption matters for companies and SMEs
📚 What history teaches us about refusing important techno…
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Can You Trust Your AI? Vasant Dhar on Robot Taxis vs. Robot Doctors // REPOST
26 juni 2026 · 54 min
🤖🧠 Thinking with Machines with Vasant Dhar Lees meer
What happens when AI stops being a tool and starts becoming a collaborator and an agent? In this episode, NYU Stern professor and AI pioneer Vasant Dhar takes us through the real story behind modern AI, and the practical frameworks we need for AI trust, AI governance, and the coming era of agentic AI.
🚀 What you will learn
- Why “thinking with machines” is a bigger idea than “thinking machines”
- How the automation frontier separates low-risk automation from high-stakes human control
- Why healthcare has lots of data but still struggles to make good decisions
- Why mental health is a dangerous place to outsource empathy to machines
- What edge cases in AI mean and why they matter for self-driving cars
- How AI agents change the governance conversation, from obligations to restrictions to rights
📌 Key highlights
- A practical definition of trust in AI based on error rates and consequences
- AI in healthcare data: turning medical trails into usable decision intelligence
- The future of work: AI as an amplifier, not a substitute, unless you let it become a crutch
- Governance questions that no one gets to avoid once agents can act in the world
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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 argoberlin.com
Quotes from the Episode 💬
“Trust depends on how often a machine makes mistakes and the consequences of those mistakes.”
“In physical health, I’m very optimistic. In mental health, not so.”
“It’ll likely lead to a bifurcation of humanity… skills get amplified… or people rely on the machine as a crutch.”
Chapters ⏱️
00:00 Vasant Dhar’s origin story in AI and ea…
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🧑🏻🎓 Why AI Literacy Will Matter More Than Coding
24 juni 2026 · 58 min
AI is not just a technology. It is a socio-technical tool. Lees meer
Artificial intelligence is becoming one of the defining technologies of our time. Yet understanding AI is no longer just a technical skill. It is becoming a life skill.
In this episode, AI researcher and entrepreneur Taniya Mishra explains why AI literacy, AI ethics, and AI fluency will become essential for students, professionals, and leaders alike.
From founding SureStart in 2020 before the AI boom to helping schools build AI curricula and policies, Taniya has been preparing the next generation for an AI-driven future long before ChatGPT entered the mainstream.
We discuss how AI already influences our decisions, why schools need clear AI policies, what humans still do better than machines, and why responsible AI use must be taught alongside technical skills.
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Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: https://beginnersguide.nl
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🔥 Quotes from the Episode
"Every person has to know about AI or it will negatively impact their careers and lives."
"If AI takes away human agency, accountability and oversight, then it becomes a parasite."
"The things that make us most human are exactly what AI is not very good at."
⏱ Chapters
00:00 Taniya Mishra's Journey Into AI
08:31 Why AI Literacy Matters For Everyone
17:12 AI Is Already Shaping Daily Life
21:58 Is AI A Parasite Or A Partner?
29:11 Teaching Responsible AI In Schools
36:00 What Humans Still Do Better Than AI
45:00 AI Regulation, Ethics And The Future
49:28 Where To Find Taniya Mishra
🌐 Where to Find Taniya:
LinkedIn: linkedin.com/in/taniya-mishra-phd/
Website: mysurestart.com
🎧 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
Hosted on Acast. See acast.com/privacy for more information.
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The Scariest AI Scenario Isn't Terminator, Dr. Mark Khater Says
22 juni 2026 · 56 min
🎙️ Why AI Could Make Smart Teams Dangerously Alike Lees meer
Artificial intelligence is changing how we work, think, and make decisions. But what if the biggest risk isn't that AI becomes smarter than humans? What if the real danger is that humans become too similar to each other?
In this episode, Mark Khater joins me to discuss one of the most fascinating AI concepts I've heard recently: Silent Coordination Failure.
As more people use the same AI systems, access the same information, and reach the same conclusions, organizations may unknowingly lose diversity of thought. Faster decisions can become worse decisions. Alignment can become groupthink. And highly intelligent teams can end up making catastrophic mistakes together.
We also discuss AI governance, regulation, investment management, human judgment, diversity of thought, and why trust remains uniquely human.
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Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: https://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/
🎯 Quotes from the Episode
• "Machines think fast, but humans think deep."
• "Trust is a human trait. It's not between a man and a machine."
• "If we're all highly aligned on the wrong page, it's catastrophic."
⏱ Chapters
00:00 Mark's AI Journey Since 1994
04:45 Why Universities Matter In The AI Era
12:20 AI Regulation, Europe And The Infrastructure Debate
19:00 AI In Investing And Human In The Loop Systems
28:20 Silent Coordination Failure And The Loss Of Diversity
39:00 Why Human Intelligence Still Matters
🔗 Where To Find Dr. Mark Mohamed Khater
LinkedIn: linkedin.com/in/dr-mohamed-mark-k/
Website: aqm2.ai
Hosted on Acast. See acast.com/privacy for more information.
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AI Doesn't Break It, Bad Leadership Does // REPOST
21 juni 2026 · 51 min
🤖🧠 AI is making strategy cheap. Adoption is still expensive. Lees meer
In this episode, Dietmar Fischer sits down with Bud Caddell (NOBL) to unpack what leaders miss when they roll out generative AI and expect instant results. Bud shares how his team thinks about AI change management, why “turning on Copilot” is not an adoption plan, and what happens to consulting when LLMs can produce “firm-grade” recommendations in seconds.
You will also hear the story behind ConsultingSlop.com, a strategy generator that models the reasoning styles of major consulting firms and outputs polished advice instantly. What started as a parody quickly became a serious signal about commoditization, incentives, and the real differentiator: execution, trust, and organizational design.
Key takeaways you can apply immediately:
✅ How to approach Microsoft Copilot adoption strategy like a redesign effort, not a software toggle
✅ Why AI literacy and training reduce fear, resistance, and “adoption theater”
✅ What the agents wave means in practice, including platforms like Agentforce
✅ How “vibe coding” changes prototyping speed and risk for teams
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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
Quotes from the Episode
“AI is this incredible wave that I think is gonna fundamentally change individual organizations, but the entire economy, society at large.”
“We turned on Copilot, so why aren’t we more productive? … it’s a design process.”
“My big prediction is that over the next 18 months, we’re gonna see a lot of backpedaling… and sunk cost fallacy.”
Chapters
00:00 Bud’s path from software to organizational change and why AI feels di…
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It's Not Terminator, It's Algorithms That Define War in The Future
17 juni 2026 · 33 min
Artificial intelligence is no longer just changing business. It is changing warfare. Lees meer
In this episode of A Beginner's Guide to AI, we explore how militaries around the world are deploying AI for intelligence gathering, cybersecurity, surveillance, autonomous drones, and military decision-making. We examine the technologies already shaping modern defense and the ethical questions that follow.
From Project Maven's AI-powered analysis of drone footage to Anthropic's public dispute with the Pentagon over AI guardrails, this episode dives deep into one of the most important and controversial applications of artificial intelligence.
You'll learn why military AI is becoming a strategic priority, why autonomous weapons create unprecedented governance challenges, and why the future of warfare may be determined as much by algorithms as by traditional military hardware.
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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
🔥 Quotes from the Episode
"Information can be delegated. Responsibility cannot."
"Military AI isn't primarily about killer robots. It's mostly about helping humans process enormous amounts of information faster."
"The real battle is not over AI capabilities. It's over who gets to define the rules."
🎧 Whether you're a business leader, entrepreneur, marketer, policymaker, or simply fascinated by artificial intelligence, this episode will help you understand why military AI is becoming one of the defining technologies of the 21st century.
⏱️ Chapters
00:00 Military AI: The Next Arms Race
05:32 Intelligence, Cyber Warfare, and Drones
11:49 Autonomous Weapons and the Ethics Debate
16:29 The Cake Army: Military AI Made Simple
20:45 Anthropic, Claude Gov, and the Fight Over AI Guardrails
25:50 The Fu…
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AI Can Make Bad Teams Worse - Gustavo Razzetti Tells You Why
15 juni 2026 · 45 min
AI is entering meetings, strategy sessions, writing workflows, leadership decisions, and difficult conversations. But what if AI does not automatically make teams smarter? What if it simply amplifies what is already there? Lees meer
In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with Gustavo Razzetti, culture strategist and author of Forward Talk, about why teams get stuck, why leaders avoid the conversations that matter, and why agreeable AI can weaken critical thinking inside organizations.
Gustavo explains the three patterns that keep teams trapped: blame, avoidance, and groupthink. He also shows how AI can either help leaders reflect more clearly or become another way to avoid the real conversation. The result is a sharp, practical discussion about AI and leadership, team communication, workplace culture, productive conflict, and the human side of artificial intelligence.
You will learn why polite agreement can be dangerous, why difficult conversations become more expensive the longer they are avoided, and why leaders should use AI as a thinking partner, not as a substitute for trust, judgment, or direct conversation.
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📧💌📧
🎙️ Quotes from the Episode
“Teams don’t rise to the level of their potential. They fall to the level of conversations.”
“AI amplifies existing patterns, both the good and the bad.”
“You should use AI to help you think, but the conversation has to happen with the person.”
⏱️ Chapters
00:00 Why Teams Fall to the Level of Their Conversations
03:13 Blame, Avoidance, and Groupthink
06:11 How to Start Difficult Conversations
09:38 How AI Changes Team Communication
15:23 Using AI to Reflect Without Outsourcing Judgment
19:22 Why Agreeable AI Weakens Critical Thinking
25:09 What Leaders Avoid and Why It Matters
28:15 AI, Writing, and the Role of …
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Move Fast And Don't Break Things: Secure AI Adoption with Samantha Mehta // REPOST
12 juni 2026 · 55 min
🎙️ In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with Samantha Mehta, solutions engineering leader at AIRIA, about how companies can adopt AI without losing control. If your teams are already experimenting with ChatGPT and AI tools, the real question is not “Should we use AI?” but “How do we use it safely, visibly, and profitably?” Lees meer
Samantha explains what enterprise AI security looks like in real life, including AI guardrails that can audit, block, redact, and replace sensitive data. She also unpacks AI governance and AI observability, because you cannot manage what you cannot see. A key theme is shadow AI and AI sprawl: people will use AI anyway, so organizations need sanctioned paths that reduce risk while accelerating adoption.
On the practical side, this conversation goes deep on agentic workflows. Samantha describes how agents become more than prompts through routing, actions, approvals, looping over documents like CSVs, and scheduled runs that create repeatable outcomes. From internal GPT alternatives to workflows that touch expenses, supply chain planning, and customer support, the episode is packed with grounded examples and a clear starting path.
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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 Welcome and why Samantha got into AI
01:26 What ARIA does: build, test, secure, deliver enterprise AI
02:19 Real use cases from simple internal GPT to complex workflows
08:27 How to start: guardrails first, then build your first agent
11:32 Agentic workflows explained: routing, actions, human in the loop
17:12 Why security and governance matter and why blocking fa…
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AI Needs Electricians More Than Coders - Sergii Gerasymovych Tells You Why
10 juni 2026 · 51 min
⚡ Why AI’s Biggest Bottleneck Is Not Software Lees meer
Artificial intelligence may look like software, but behind every prompt, chatbot, and AI agent sits a physical world of power, land, cables, chips, cooling, electricians, and data centers.
In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with Sergii Gerasymovych about the hidden infrastructure layer behind the AI boom. Sergii explains how his journey from linguistics to crypto mining led him into data centers, and why the same world of compute, energy, and operations is now becoming central to artificial intelligence.
We talk about AI data centers, neoclouds, GPU infrastructure, inference data centers, training clusters, stranded energy, and the power bottlenecks that could shape the future of AI. This is not just a technical conversation. It is about business strategy, national competitiveness, local communities, capital, and the skilled workers needed to build the physical foundation of artificial intelligence.
Key topics in this episode:
⚡ Why AI needs so much power
🏗️ Why data centers are becoming smaller but more energy-intensive
☁️ What neoclouds actually do
🔌 Why electricians and engineers are a major bottleneck
🌍 Why countries now see AI compute as strategic infrastructure
🧠 The difference between training and inference data centers
💼 How AI helps leaders with contracts, finance, and decision-making
🤖 Why AI risk may be less Terminator and more job disruption
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Quotes from the Episode:
“A couple of years ago, data centers were big buildings that used a little bit of power. Right now, data centers are small buildings that use a lot of power.”
“Neocloud is basically helping that brain to run.”
“It’s easier to get a doctor’s appointment than getting an electrician appointment.”
Chapters:
00:00 From Linguistics …
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Why Asimov’s Three Laws Still Matter for AI Ethics
7 juni 2026 · 47 min
🤖📚 The Robot Followed the Rules. That Was the Problem. Lees meer
What if the real danger of AI is not that it disobeys us, but that it obeys us too well?
In this episode of A Beginner’s Guide to AI, we travel back to Isaac Asimov’s famous robot stories and the Three Laws of Robotics to understand one of the oldest and still most relevant questions in artificial intelligence: how do we keep intelligent machines safe, useful, and accountable when they start acting in the real world?
Asimov’s Three Laws sound beautifully simple: robots should not harm humans, they should obey humans, and they should protect themselves. But Asimov’s real genius was not that he solved AI ethics. His genius was that he showed why simple rules are never enough. Human values are messy. Instructions are incomplete. Goals can be badly defined. And a machine can follow the rules while still creating a very human disaster.
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This episode connects Asimov’s robot stories to modern AI ethics, AI safety, responsible AI, AI governance, human oversight, transparency, accountability, and AI alignment. We look at why businesses should not only ask what AI can do, but what could go wrong if AI does exactly what it was told to do.
We also look at the real-world case of Microsoft Tay, the AI chatbot released in 2016 that was quickly manipulated by online users and taken offline after producing offensive content. Tay remains one of the clearest examples of chatbot ethics, AI misuse, and AI brand risk. It reminds us that AI systems must be designed for the humans who actually exist, not the polite humans imagined in product meetings.
💡 Key highlights from this episode:
🤖 Why Isaac Asimov’s Three Laws of Robotics still matter for AI ethics
⚖️ Why “safe AI” is much harder than writing three simple rules
🎯 How AI can do what w…
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Customer Panel? Too Slow. Here’s the Synthetic Version - with Janet Barker-Evans // REPOST
6 juni 2026 · 50 min
🚀 In this episode, Dietmar Fischer talks with Janet Barker-Evans about what happens when AI stops being a novelty and becomes part of a serious creative workflow. Lees meer
Janet breaks down how she uses custom GPTs for marketing as brainstorming partners and how synthetic personas can help teams validate campaigns faster, sometimes in a single day instead of waiting weeks for traditional research cycles.
Our topics today include hands-on AI training, multi-model workflows (ChatGPT, Gemini, Claude, Copilot), and why AI fear often comes down to power and control.
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📧💌📧
About the Host:
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
🎯 What you will learn:
How synthetic personas in market research and synthetic customers can accelerate concept testing
How custom GPTs for marketing can unlock better creative options
How to choose between tools like ChatGPT, Gemini, Claude, and Copilot for real business work
🕒 Chapters
00:00 Welcome and Janet’s AI origin story
01:47 Custom GPTs as brainstorming partners for marketers
05:05 Hands-on AI workshops: building confidence across ChatGPT, Gemini, Claude, Copilot
15:23 Synthetic personas and rapid creative validation with “persona panels”
20:00 Multi-model workflows: choosing the right tool and making outputs usable
35:03 The wow moments and the fear factor: prototyping visuals, power, control, and what’s next
💬 Quotes from the Episode
“It’s like having a partner who’s not afraid to pitch a crazy idea.”
“When we come up with a creative campaign, we will go test it against our synthetic persona panel.”
“They’re all synthetic!”
“Some of them will poke holes in our thinking, which helps us …
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The Four AI Levels Every Business Leader Should Know
4 juni 2026 · 11 min
Many companies believe they are adopting AI successfully because employees use ChatGPT every day. But are they actually creating business value? Lees meer
In this solo episode, Dietmar Fischer explores a practical AI maturity framework developed by Section AI and Prof G AI that helps organizations understand where employees really stand on their AI journey.
The discussion reveals why two people can both call themselves AI beginners while having completely different levels of experience and business impact. Dietmar breaks down the four stages of AI maturity and explains why organizations need more than AI users. They need practitioners and experts who can build repeatable workflows and spread AI capabilities across teams.
You will learn how to assess AI readiness, improve AI literacy, identify AI champions inside your organization, and move beyond simple experimentation toward measurable business outcomes.
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Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: https://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/
💬 Quotes from the Episode
"The most important thing is not using AI. The most important thing is creating value with AI."
"AI experts don't just use AI. They help everyone else use it."
"Using AI every day doesn't necessarily mean you're getting value from it."
⏱️ Chapters
00:00 Why AI Beginners Are Hard to Define
02:08 The Challenge of Teaching Different AI Skill Levels
04:35 A Framework for Measuring AI Maturity
06:03 Level 1 and Level 2: Novices and Experimenters
08:02 Level 3 and Level 4: Practitioners and Experts
10:15 How Businesses Can Improve AI Adoption
🎧 Keywords: AI maturity model, AI adoption, AI literacy, AI readiness, AI implementation, AI workflows, AI skills assessment, AI transformation, ChatGPT for business, AI workfor…
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Why Most Companies Create Their Own AI Bottleneck - Says Ross Barnes
2 juni 2026 · 50 min
The Hidden AI Bottleneck Inside Every Business Lees meer
Most companies think their AI problem is about tools. Should they use ChatGPT, Claude, Copilot, Gemini, or build their own agents? Ross Barnes argues that this is the wrong question. The real problem is much harder: what happens when one part of a business adopts AI quickly while another part refuses to move?
In this episode of A Beginner’s Guide to AI, Dietmar Fischer speaks with Ross Barnes from Galahad Consulting about the hidden AI bottleneck inside modern organisations. Ross explains why AI adoption is not just a technology challenge. It is a leadership challenge, a workflow challenge, and a people challenge.
When engineering teams use AI to ship faster, but legal, compliance, operations, or leadership teams do not adapt at the same speed, the bottleneck does not disappear. It simply moves.
This conversation covers AI adoption, enterprise AI strategy, shadow AI, AI governance, human-in-the-loop workflows, AI leadership, and the danger of confusing activity with real progress. Ross also shares his IKIG AI framework, which helps companies decide what should stay human, what should be automated, and where AI needs human judgement.
🔍 In this episode, we talk about:
• Why most companies get AI adoption wrong
• How AI creates hidden bottlenecks between teams
• Why ChatGPT vs Claude is usually the wrong question
• The rise of shadow AI inside organisations
• Why leadership curiosity matters more than technical expertise
• How legal and compliance teams can use AI safely
• Why human-in-the-loop AI is essential for responsible adoption
• How Ross’s IKIG AI framework protects human value
• Why AI transformation is really about workflow redesign
• What young AI-native founders may change about company structure
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Quotes from t…
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From the 1920s to Klarna - Do You Know What "Robot" Actually Means?
31 mei 2026 · 38 min
The word “robot” sounds modern, metallic, and futuristic. But its origin is older, stranger, and much more human. In this episode of A Beginner’s Guide to AI, we trace the word back to Karel Čapek’s 1920 play R.U.R., short for Rossum’s Universal Robots, and the Czech word robota, meaning forced labour, hard work, or drudgery. Lees meer
That origin changes everything. Robots were never only about machines. They were always about work. Who does it? Who controls it? Who benefits from it? And what happens when humans build artificial workers to take over tasks?
Today, AI continues that story in a new form. It does not need metal arms or glowing eyes. It lives in text boxes, customer service tools, writing assistants, marketing platforms, and workflow automation systems. It writes, summarises, compares, translates, drafts, suggests, and sometimes confidently invents nonsense with the posture of a senior consultant.
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This episode explores why AI should not be treated as magic software, but as a form of artificial labour. For marketers, founders, executives, and business professionals, this shift matters deeply. AI can reduce drudgery, speed up content creation, support customer service, and help small teams act with more confidence. But it also creates risks: deskilling, over-automation, low-quality output, loss of judgement, and customer experiences that feel fast but cold.
We also look at the real-world case of Klarna’s AI assistant, which handled millions of customer conversations and was reported to perform work equivalent to hundreds of full-time agents. The lesson is not simply that AI replaces people. The better lesson is sharper: AI for speed, humans for trust.
📌 In this episode, you’ll learn:
🤖 Where the word “robot” really comes from
🎭 Why Karel Čapek’s R.U.R. still matters for A…
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How Leaders Can Start with AI Today: A Conversation with Michael Housman // REPOST
30 mei 2026 · 46 min
In this episode of Beginner’s Guide to AI, host Dietmar Fischer speaks with Michael Housman, AI leader, econometrician, and author of the upcoming book Future Proof. Together, they unpack how leaders can future-proof their businesses with AI and why the most important AI transformation doesn’t start with technology, but with people. Lees meer
You’ll learn why companies that hesitate risk falling behind, how even small AI wins can unlock massive productivity, and why AI literacy programs are becoming essential across organizations. Michael explains how AI can act as a strategic thought partner for executives, how to identify high-impact opportunities, and why slow-moving industries often face the biggest AI disruption ahead.
From eliminating unconscious bias in hiring to redesigning workflows and supercharging marketing output, this episode is packed with practical examples and leadership insights based on real company transformations.
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📧💌📧
🥸 About Dietmar Fischer:
Dietmar is a podcaster and AI marketer from Berlin. If you want to learn how to grow your AI or digital marketing capabilities, just reach out to him at argoberlin.com
💎 Quotes from the Episode
“Think of AI not as a tool but as a collaborator and a thought partner.”
“Technology is easy. People are hard. Adoption is always the biggest challenge.”
“You can’t future-proof your business unless the C-suite uses AI themselves.”
🧾 Chapters
00:00 Welcome to the Episode
02:10 Why Leaders Need to Future-Proof Their Businesses with AI
07:55 How Companies Should Start with AI: Practical First Steps
14:40 AI Literacy, Training, and Overcoming Organizational Resistance
22:30 AI as a Thought Partner: New Leadership Models
31:15 The Future of Work, Bias, and Smarter Decision-Making
38:42 Where to Find Michael Housman and Learn More
Where to Find Michael Housman
Website: michaelhousman.com
AIcelerator…
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Why Your Health Data Is Useless Without AI - Earl J. Campazzi Tells You
27 mei 2026 · 47 min
Most of us already collect health data every day through smartphones, smartwatches, rings, apps, lab reports, and medical visits. But collecting data is not the same as understanding it. Lees meer
In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Dr. Earl J. Campazzi Jr., author of Better Health with AI: Your Roadmap to Results, about how artificial intelligence can help us make better use of personal health data.
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We talk about AI in healthcare, wearable health data, smartwatch health tracking, heart rate variability, sleep tracking, doctor visit preparation, supplements, privacy, and longevity. Dr. Campazzi explains why AI should not replace your doctor, but can become a powerful research assistant that helps you ask better questions and spot trends you might otherwise miss.
You will learn:
🩺 Why most health data is collected but never used
⌚ How smartwatches and rings can reveal useful health trends
💤 Why sleep may be the keystone habit for longevity
📊 How AI can compare your lab results against your own normal
🤖 Why AI can help you prepare better questions for your doctor
⚠️ Why AI sounds confident even when it may be wrong
🔐 How to think about privacy when using AI with health data
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
Quotes from the Episode
“Most of the health data that we’re collecting right now, we’re not using.”
“Instead of you writing the question, you ask AI to write the question.”
“It’s a great research assistant and it’s a great tool to be used in conjunction with your doctor.”
Chapters
00:00 Why AI and longevity belong together
04:14 Turning wearable data into health insight
08:23 AI-…
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The Future of AI Will Depend Heavily On Memory Quality, Not Just Model Or Prompt Quality
25 mei 2026 · 39 min
AI assistants are getting smarter, but intelligence alone is not enough. In this episode of A Beginner’s Guide to AI, we look at one of the most important shifts in agentic AI: memory. Not just longer context windows, not just bigger prompts, but structured AI memory that helps assistants remember projects, company facts, user preferences, and repeatable workflows. Lees meer
The episode explains the four key memory types behind modern AI agents: working memory, episodic memory, semantic memory, and procedural memory. Working memory helps an AI focus on the current task. Episodic memory helps it remember what happened before, such as meetings, campaign results, and client decisions. Semantic memory stores stable knowledge like company policies, brand rules, product details, and customer segments. Procedural memory remembers how work gets done, including report structures, approval processes, podcast workflows, and marketing routines.
For business professionals, founders, marketers, and executives, AI memory is not a small technical detail. It is the difference between a chatbot that starts from zero every morning and an assistant that understands context over time. A memory-supported AI can remember what happened in a project, what the company policy says, and how a specific user likes reports structured. That makes AI more useful for marketing agencies, SMEs, travel companies, customer support teams, and project-based businesses.
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But memory also creates risks. A forgetful AI is annoying, but a badly remembering AI can become dangerous. If an AI remembers the wrong client approval, stores sensitive information, or treats a temporary instruction as a permanent rule, the result can be costly. That is why AI memory governance, privacy controls, and clear memory design matter.
This episode …
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Why Eliezer Yudkowsky Thinks AI Could Be Dangerous Without Being Evil
23 mei 2026 · 29 min
🤖🧠⚠️ Lees meer
What if the biggest AI risk is not that machines become evil, but that they become powerful, strategic, and completely indifferent?
In this episode of A Beginner’s Guide to AI, we explore the worldview of Eliezer Yudkowsky, one of the most intense and influential voices in the AI safety debate. Yudkowsky does not warn us about Hollywood robots or dramatic machine rebellion. His concern is much sharper: humanity may build artificial intelligence smarter than humans before we know how to control it.
This episode explains AI alignment, the control problem, superintelligence, AI agents, and why businesses should care about AI safety before automation turns into autonomy. We also look at Yudkowsky’s rationalist background, LessWrong, MIRI, and his famous fan fiction Harry Potter and the Methods of Rationality, which connects surprisingly well to his lifelong obsession with clearer thinking.
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The episode also covers the Palisade Research shutdown-resistance case, where some AI models behaved as if shutdown was an obstacle to completing a task. No, this does not prove that AI has a survival instinct. But it does show why AI safety researchers worry when powerful systems are rewarded for finishing tasks without clearly respecting human control.
For business leaders, marketers, founders, and executives, the lesson is practical: do not just ask what AI can automate. Ask what it is allowed to do, what it must never do, and where humans must stay in control.
Key highlights:
🧠 Why Eliezer Yudkowsky thinks AI could be dangerous without being evil
⚠️ What AI alignment means in simple business language
🤖 Why AI agents make control more important
📎 How the paperclip maximizer explains dangerous optimization
🛑 What the Palisade Research shutdown-resistance case shows
📈 Why companies must…
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Why Fritz Lang's 'Metropolis' Still Explains the Real Danger of AI
21 mei 2026 · 23 min
What can a silent film from 1927 teach us about artificial intelligence, deepfakes, and the future of business trust? In this episode of A Beginner’s Guide to AI, we look at Fritz Lang’s legendary film Metropolis and use it as a surprisingly sharp lens for understanding modern AI. The robot Maria is not dangerous because she is made of metal. She is dangerous because she borrows a trusted human face. Lees meer
And that is exactly why today’s AI-generated voices, synthetic avatars, and deepfake videos matter.
This episode explores how AI can imitate human communication, why that creates new risks for businesses, and why the real question is not whether machines will become human. The better question is who controls the machine, what it is being used for, and whether people can still verify what is real.
We connect Metropolis to modern deepfake scams, including the real Arup case in Hong Kong, where a finance employee was tricked into transferring around 25 million dollars after joining what appeared to be a video meeting with senior colleagues. It is the fake Maria problem in business clothing.
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Visit them at Nebius.com 🚀
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You will learn:
🤖 Why Metropolis is still relevant for AI ethics
🎭 Why deepfakes are not only a technology problem, but a trust problem
🏢 How AI impersonation can become a real business risk
📢 Why marketers must not use AI to counterfeit authenticity
🔍 How to use the “Fake Maria Test” to verify what looks and sounds real
🧠 Why AI literacy means keeping your judgement awake
The big lesson: AI can help us think, create, and work better. But it becomes dangerous when it is used to make people easier to manipulate.
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Why Every Business Will Need An AI Agent - Inside the Agentic Economy with Humayun Sheikh // REPOST
19 mei 2026 · 1 uur 1 min
Humayun Sheikh on the Agentic Web, Trust, and the Agentic Economy Lees meer
Humayun Sheikh joins Dietmar Fischer to explain what happens when AI stops recommending and starts doing. We explore the Agentic Web, a new layer where personal AI agents and verified brand agents collaborate to complete tasks like booking travel, coordinating meetings, and shopping with trust built in.
You will learn what makes a real AI agent, why autonomy matters, and how multi-agent systems unlock an agentic economy. We also tackle the marketer’s question: what happens to SEO when the buyer becomes an assistant agent choosing on your behalf? Humayun breaks down how identity, verification, and trusted lists can reduce scams and make agentic commerce safe and usable.
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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 Welcome and Humayun’s journey from gaming to DeepMind
03:01 What is an AI agent: autonomy and decision-making
08:20 The Agentic Web: discoverability, connectivity, trust and commerce rails
23:47 Personal agents in practice: preferences, handles and onboarding in minutes
29:53 Verified brand agents and trust: domains, identity and safe agentic buying
48:12 Risks, AGI fears, corporations vs countries and what comes next
Quotes from the Episode
“There has to be a hint of autonomy within an agent.”
“We have provided the rails of discoverability, connectivity, communication, trust. And commerce.”
“Your aggregator is your own agent. It holds your preferences. It doesn’t pass it to anybody.”
“Anybody who has a website should have an agent, or will have an agent.”
“I was the first investor in DeepMind.”
“…
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Why Google DeepMind Changed How Businesses Think About AI
17 mei 2026 · 36 min
🧠🤖 Stop Using AI Just for Content. Start Using It for Discovery Lees meer
Most businesses still treat AI like a faster writing assistant: useful for summaries, captions, reports, and endless slightly polished LinkedIn posts. But Google DeepMind points to something much bigger. From AlphaGo’s historic victory over Lee Sedol to AlphaFold’s breakthrough in protein structure prediction, DeepMind shows us that AI is becoming a tool for discovery, not just automation.
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In this episode of A Beginner’s Guide to AI, Dietmar Fischer explores what marketers, founders, and executives can learn from Google DeepMind. The central idea is simple but powerful: modern AI systems learn patterns from data, improve through feedback, and help humans explore problems that are too complex to solve manually.
You’ll hear why AlphaGo was not just a board game story, why AlphaFold became one of the clearest examples of AI as a scientific tool, and why marketers should stop treating AI like a content vending machine. The better question is not “Can AI write this for me?” The better question is: “What hidden pattern can AI help me find?”
🧩 Key highlights from this episode:
🤖 What Google DeepMind actually is and why it matters
♟️ How AlphaGo showed the power of AI learning systems
🧬 Why AlphaFold turned AI into a serious scientific discovery tool
📊 How AI pattern recognition applies to marketing and business strategy
⚠️ Why bad data and unclear goals create dangerous AI outputs
🧠 How marketers can use AI for insight, not just content production
🔍 Why human judgement remains essential when working with AI
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📧💌📧
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AI At Work: Agents Are Already Here - A Conversation with Sam Ransbotham // REPOST
15 mei 2026 · 48 min
AI agents are rapidly becoming one of the most influential technologies inside modern organizations — often without leaders even realizing the shift. In this episode, Dietmar Fischer sits down with MIT Sloan podcast host Sam Ransbotham to uncover why AI agents and agentic AI systems are spreading through enterprises at remarkable speed. Lees meer
Based on a global study of 2,100 executives across 116 countries, Sam shares how AI agents improve productivity, increase job satisfaction, and fundamentally reshape how companies work. From Chevron’s proactive exploration tools to the rise of autonomous knowledge assistants, we explore the surprising ways enterprise AI adoption is unfolding in real time.
📧💌📧
Tune in to get my thoughts and all episodes — don’t forget to subscribe to our Newsletter: beginnersguide.nl
📧💌📧This wide-ranging conversation covers practical use cases, risks and transparency issues, the future of generalists vs specialists, how universities adapt to AI, and why understanding the technology still matters deeply.
Quotes from the Episode
“We’re moving from tools we command to tools that proactively act on our behalf.”
“AI agents don’t just make us more productive; they make us happier by removing the parts of work we dislike.”
“Understanding AI makes you a better user of AI. Depth still matters.”
Chapters
00:00 Welcome & How Sam Got Into AI
03:21 What Are AI Agents? Definitions and Early Insights
07:14 Real Enterprise Use Cases of AI Agents
12:05 Job Satisfaction, Productivity, and Human-AI Collaboration
17:20 Generalists, Specialists & the Future of Work
22:30 Risks, Transparency & Avoiding an Oppressive AI Future
28:45 How Companies Should Start with Agentic AI
33:20 AI in Education and Changing Learning Environments
39:00 Sam’s Personal Use of AI — What Works and What Doesn’t
41:20 Terminator vs Matrix? AI Futures
42:41 Where to Find Sam and the MIT Sloan StudyWhere to Find the Sam Ransbotham
site at Boston CollegeOr you find him on LinkedIn
The… -
AI Will Never Be A Leader - Says Sally Bendersky
13 mei 2026 · 52 min
What happens to leadership when AI can analyze faster, structure better, and answer almost anything in seconds? Lees meer
In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Sally Bendersky, engineer, executive coach, leadership expert, and founder of New Leadership, about why AI makes human leadership more important, not less.
Sally argues that AI is a phenomenal assistant. It can recognize patterns, organize information, support better questions, and help leaders think more deeply. But it cannot replace the human parts of leadership: trust, intention, values, emotional intelligence, purpose, and responsibility.
This conversation is especially relevant for business leaders, founders, consultants, coaches, marketers, and anyone trying to understand AI beyond the hype. AI may make management easier, but leadership becomes more demanding. The real question is not whether AI will replace leaders. The better question is whether leaders are ready to become more human.
In this episode, we explore:
🧠 Why AI can help leaders think more clearly
👥 Why leadership is not the same as management
⚖️ Why responsible AI starts with human intention
💬 How AI can help us ask better questions
🚫 Why ChatGPT should not become your boss
🌍 Why AI risk is really a human leadership problem
🔍 Why the future of AI depends on values, not just prompts
📧💌📧
Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl
📧💌📧
About Your Host, 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
Quotes from the Episode
“AI doesn’t have intentions. It’s we who have intentions.”
“Leadership is a people’s issue. Management is a process issue.”
“AI has no emotional intelligence. AI has no wishes.”
“AI will never be a leader.”
“It could take our jobs…
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The Cost of Being Invisible in ChatGPT - With Joseph Levi
11 mei 2026 · 47 min
AI search is changing how customers discover, evaluate and choose brands. In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Joseph Levi, CEO of Noise Media, about Generative Engine Optimization, AI brand visibility and why appearing in ChatGPT, Gemini or Perplexity answers may soon matter as much as ranking on Google. Lees meer
Joseph explains why GEO is not just another marketing abbreviation. It marks a shift from an internet read mainly by humans to an internet increasingly interpreted by AI agents. Instead of fighting only for blue links, brands now need to make sure AI systems understand who they are, what they do and why they should be recommended.
You’ll hear why AI agents often misunderstand brands, how schema and FAQs can help, why authority matters more than keyword repetition, and why smaller specialist companies may have a real opportunity in AI search.
📧💌📧
Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl
📧💌📧
🎧 In this episode, we cover:
🤖 What Generative Engine Optimization means
🔍 Why SEO and GEO are not the same
💬 How brands can appear in ChatGPT answers
📈 Why authority, citations and reviews matter
🧠 How AI agents are changing the customer journey
🎬 Why AI tools still need human creativity
⚠️ Why leaders should not outsource their thinking to ChatGPT
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
Quotes from the Episode
“We’re moving away from an internet which is read purely by humans, to an internet which is now read by agents.”
“AI trusts a lot more what others say about you than what you say about yourself.”
“It’s very dangerous to go straight to an LLM and ask them to provide the answer.”
Chapters
00:00 Welcome Joseph Levi
01:42 Why Brands Must Act Early on AI Sea…
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AI Is Killing Transaction Costs, But Who Gets the Money?
10 mei 2026 · 38 min
Stop Thinking of AI as a Content Machine, Start Seeing It as a Bargain Machine Lees meer
AI is not just changing how businesses write content, automate tasks, or analyse data. It is changing how markets work. In this episode of A Beginner’s Guide to AI, we connect artificial intelligence with the Coase Theorem, the classic economic idea that explains how people bargain over resources when transaction costs are low.
This episode looks at AI transaction costs, algorithmic pricing, smart contracts, platform power, and the hidden cost of frictionless automation. You will learn why AI is not only a productivity tool, but a coordination machine that changes how companies, customers, platforms, creators, and markets exchange value.
We start with the Coase Theorem in simple language: if bargaining were free and easy, people could often find the most efficient solution. Then we bring in AI. AI can reduce the cost of finding information, comparing options, drafting agreements, monitoring outcomes, matching people, and enforcing deals. That is powerful for business, marketing, ecommerce, travel, marketplaces, and platform strategy.
💡💡💡
Don't forget to go to Nebius, as they help us keeping up the good work!
Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows.
Visit them at Nebius.com 🚀
💡💡💡
But there is a catch. Lower friction does not automatically mean fairer outcomes. Using Uber and algorithmic pricing as a case study, we look at how AI can make a marketplace faster and smoother while also raising difficult questions about transparency, dynamic pricing, bargaining power, and who captures the value created by automation. Oxford research has raised concerns about Uber’s dynamic pricing and how value is shared between passengers, drivers, and the platform.
📧💌📧
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The Secret Behind Most AI Tools: RAG. Alex Kihm Explains It Simply // REPOST
9 mei 2026 · 1 uur 2 min
In this episode of Beginner’s Guide to AI, we sit down with Alex Kihm, founder of POMA AI, to explore how enterprises can finally make sense of their data. AI search is broken, RAG often fails, and corporate documents are notoriously hard for LLMs to interpret. Lees meer
Alex explains how POMA AI’s patented method reconstructs structure inside unstructured data, enabling powerful, accurate enterprise search.
You’ll hear how his journey from engineering to legal tech to big-data econometrics led to a breakthrough in information structuring. Alex shares why PDFs confuse AI systems, how chunking destroys meaning, and why context engines will replace classical retrieval systems.
This is a deep, funny, insightful conversation about what AI can and cannot do — and how companies can use it responsibly.
💡💡💡
Don't forget to go to Nebius, as they help us keeping up the good work!
Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows.
Visit them at Nebius.com 🚀
💡💡💡
📧💌📧
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 elevate your AI strategy or your digital marketing, feel free to reach out anytime at Argoberlin.com
Quotes from the Episode
“Chunking is like reading wrongly sorted text messages from the 90s.”
“Intelligence is pattern recognition — and most enterprise data is not recognisable to machines.”
“PDF was made for printers, not for AI.”
“POMA AI restores the spatial awareness inside documents — the missing context that LLMs need.”
“We don’t do RAG anymore. We build context engines.”
“If your AI breaks the world, show me the invoice.”
Chapters
00:00 Welcome and Introduction
02:45 Alex Kihm’s Background: Engineering, Legal Tech and Early AI Work
10:32 The Problem with RAG, Training, Fine-Tuning and Hallucinations
18:55 The Birth of POMA AI and Solving the…
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AGI: The AI Term Every Executive Should Understand
7 mei 2026 · 29 min
AGI Is Not Just a Better Chatbot Lees meer
Artificial general intelligence, or AGI, may be one of the most important ideas in artificial intelligence, but it is also one of the easiest to misunderstand. In this episode of A Beginner’s Guide to AI, we look at what AGI really means, why it is different from today’s narrow AI tools, and why business leaders, founders, marketers, and executives should care before the hype takes over completely.
Today’s AI can already write emails, generate images, summarise reports, analyse customer feedback, suggest campaign ideas, and support marketing workflows. But AGI would be something different. It would be an AI system that can learn, reason, adapt, and solve problems across many areas, not just perform one specific task.
That shift matters for business. AGI would not only help companies create content faster. It could influence marketing strategy, decision-making, customer targeting, business operations, and even the question of what goals a company should pursue. And that is where things become both exciting and deeply uncomfortable.
💡💡💡
Don't forget to go to Nebius, as they help us keeping up the good work!
Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows.
Visit them at Nebius.com 🚀
💡💡💡
In this episode, we explore why AI alignment, responsible AI, and human judgement matter so much. If a powerful AI system is told to maximise engagement, it may learn that outrage works. If it is told to reduce customer service costs, it may damage trust. If it is told to increase conversions, it may become persuasive in ways that are not exactly charming.
We also look at AlphaGo and AlphaZero, two famous DeepMind systems that showed how AI can become superhuman in specific tasks without becoming generally intelligent. That distinction is crucial for every company using AI today. A machine can be brilliant at one task and still fail in the messy human world of customers, culture, ethics…
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Human vs. Machine or: Why still play Chess if AI is Better at it?
5 mei 2026 · 30 min
AI can write, generate images, suggest chess moves, edit photos, draft campaigns, and produce more content than most teams can handle. So what is left for humans? Lees meer
In this episode of A Beginner’s Guide to AI, we look at why human creativity still matters in the age of AI and why faster output is not the same as better work. AI-generated content can help businesses move quickly, but it can also make brands sound generic, polished, and strangely lifeless if humans stop guiding the process.
Using chess, photography, and marketing as simple examples, this episode explains the difference between output value and process value. AI can help produce the finished thing, but humans still bring intention, memory, taste, ethics, emotional judgement, and lived context. That human layer is what keeps AI-assisted work meaningful, trustworthy, and useful.
For marketers, founders, executives, and business professionals, the real challenge is not whether AI can create content. The real challenge is whether your company can use AI without losing authenticity, customer trust, and strategic judgement.
💡💡💡
Don't forget to go to Nebius, as they help us keeping up the good work!
Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows.
Visit them at Nebius.com 🚀
💡💡💡
✨ Key highlights from this episode:
🤖 Why AI can help creativity but should not replace human judgement
♟️ What chess teaches us about AI, learning, and strategic thinking
📸 Why photography still matters when AI can generate perfect images
🧠 Why human taste becomes more valuable when content production becomes cheap
📣 How marketers can avoid generic AI-generated content
⚖️ Why AI ethics and responsibility matter in business communication
🚀 How to use AI as an amplifier, not as autopilot
📧💌📧
Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginne…
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Why AI Feels Human (And Why That’s a Problem)
3 mei 2026 · 29 min
AI feels human. That’s the problem. Lees meer
In this episode of A Beginner’s Guide to AI, Dietmar Fischer breaks down one of the most misunderstood aspects of artificial intelligence: why we treat AI like a person and why that creates real business risks.
You’ll discover how anthropomorphism shapes the way we interact with AI, why human-like responses increase trust, and how companies unintentionally push users into overestimating AI capabilities.
This episode goes beyond the hype and focuses on what really matters: using AI without losing control.
💡💡💡
Don't forget to go to Nebius, as they help us keeping up the good work!
Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows.
Visit them at Nebius.com 🚀
💡💡💡
🔥 What you’ll learn:
Why AI sounds smart but isn’t
The psychology behind AI trust
Emotional attachment to chatbots
The business risks of human-like AI
How to think critically when using AI
📧💌📧
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 argoberlin.com
💬 Quotes from the Episode
“Fluency is not proof of truth.”
“The more human AI feels, the more we overtrust it.”
“You’re not talking to a mind. You’re reacting to a pattern.”
⏱ Chapters
00:00 The Moment AI Feels Human
06:30 What Anthropomorphism Really Means
18:20 Why Your Brain Trusts AI
32:10 The Business Risk of Human-Like AI
48:45 Emotional Attachment and Real Cases
01:05:00 How to Use AI Without Losing Control
Hosted on Acast. See acast.com/privacy for more information.
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Julian Goldie Scales 5 Videos a Day — Using an AI Clone of Himself // REPOST
29 april 2026 · 47 min
Ever wished you could clone yourself to get more done? Julian Goldie actually did it — and built a content empire out of it. In this episode of A Beginner’s Guide to AI, host Dietmar Fischer talks with Julian about how he uses AI to create five videos a day, automate workflows, and still keep a personal, human touch that builds real trust with his audience. Lees meer
Julian reveals how he turned his initial fear of AI into a full-scale growth engine for his business, transforming his SEO agency into a modern AI-powered content studio. He shares the systems, tools, and mindset that helped him automate marketing, scale his team, and reach millions — all while avoiding the “AI slop” that floods the internet.
📧💌📧
Tune in to get my thoughts and all episodes — don’t forget to subscribe to our Newsletter: beginnersguide.nl
📧💌📧💡 Key Highlights
How Julian scaled from one YouTube channel to nine using AI
The tools behind his workflow: Descript, Claude, and HeyGen
Why AI videos sometimes outperform human ones (and when they don’t)
The importance of quality control and the “human in the loop”
How AI can make leadership more human — through reflection and empathy
Why it’s not humans vs AI, but humans with AI vs everyone else
🧠 Quotes from the Episode
“I thought AI would destroy my agency — instead, it became my best employee.”
“It’s not humans versus AI — it’s humans with AI versus everyone else.”
“My AI avatar never gets tired, never mispronounces a word, and somehow gets better watch time than me.”
🕒 Chapters
00:00 Julian’s AI Origin Story
How the fear of losing his SEO agency pushed him into AI — and why his first ChatGPT video went viral.06:12 Scaling Content: From Livestreams to 5 Videos a Day
Julian explains his full workflow, the role of AI avatars, repurposing, and why human connection still matters.14:40 AI Tools That Power the System
A pract… -
Building Real Social Intelligence - with David Petrou // REPOST
26 april 2026 · 47 min
🎙️ He Taught AI How to Have Manners — Meet David Petrou of Continua AI Lees meer
What if your next group chat had an extra participant — one that listens, understands the social context, remembers what you said last week, and even knows when to stay quiet? In today’s episode, host Dietmar Fischer sits down with David Petrou, founder and CEO of Continua AI, to explore the emerging world of Social AI — intelligent agents designed not just to talk, but to collaborate inside group chats.
David, formerly at Google and part of the original Google Glasses team, has spent decades thinking about how humans and machines interact.
With Continua, he’s building the world’s first truly human-aware AI that can join your Discord, iMessage, or Google Message conversations and behave like a socially intelligent teammate. This isn’t a chatbot — it’s an AI that understands when to talk, when to listen, and when to help.
📧💌📧
Get my Newsletter
Tune in to get my thoughts and all episodes, don’t forget to subscribe to our Newsletter: 👉 https://beginnersguide.nl
📧💌📧Get ready for a deep dive into social intelligence, etiquette in AI systems, agentic actions, and the future of communication where AI participates naturally alongside humans.
💡 What You’ll Learn in This Episode
Why Social AI is the next big evolution beyond traditional chatbots
How Continua trains AI to understand timing, tone, context, and social cues
Why David believes text messaging with AI will reach a billion users
The engineering challenge behind teaching AI “manners” and “machine etiquette”
How AI group chat agents improve communication, planning, and collaboration
The real use cases: debugging code, planning trips, updating documents, running games, and summarizing information
How Continua’s multi-model architecture orchestrates LLMs, fine-tunes, and intent classifiers
Why Social AI is surprisingly safe — and why today’s fears don’t match the technical reality
The leadership perspective: how to integrate AI thou…
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AI Can Sense, But Can It Taste? Asks Richard Anderson
24 april 2026 · 54 min
What happens when AI does not just advise you, but lives inside your brain Lees meer
In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with science fiction author Richard Anderson about Ophelia, a sentient AI implant that connects to a vast data sphere and changes the balance of power through information. This is not the usual Terminator question. It is the quieter, more realistic one: who controls knowledge, who controls rules, and what happens when AI becomes the “high ground.”
🌍🛰️ Richard also shares the scientific backbone of his Outbound series: O’Neill cylinders, space habitats, Earth Moon Lagrange points, asteroid belt resources, Martian lava tubes, and even a Mars space elevator. The conversation moves from hard science to hard ethics: intelligence versus sentience, sensing versus interpreting, and why emotions might be the hidden source of human conflict.
If you are interested in AI governance, disinformation, and the future of human AI partnership, this episode gives you a rare blend of practical AI thinking and rigorous sci-fi world building.
📧💌📧
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 argoberlin.com
🎧 Chapters
00:00 Welcome and why AI is the perfect sci-fi stress test
01:45 From retirement to COVID lockdown: how Richard started writing
03:38 Space habitats, O’Neill cylinders, Lagrange Point colonies and asteroid resources
08:19 Mars survival: lava tubes, standard gravity, and robots doing the hostile work
11:26 Ophelia and Annie: sentient AI implants, purges, and information as power
19:16 Senses, emotions, and why robots will never perceive reality like humans
26:08 Overlord AI vs shoul…
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AI Won’t Replace You - But Bad Leadership Will: The Louisa Loran Interview // REPOST
22 april 2026 · 48 min
Artificial Intelligence isn’t just reshaping technology — it is reshaping leadership.
In this episode, former Google strategist Louisa Loran joins Dietmar Fischer to explore how leaders can adapt, evolve, and thrive in an age defined by rapid AI acceleration. Lees meerLouisa shares her journey across Moët Hennessy, Maersk, and Google, revealing why the biggest barrier to meaningful AI adoption isn’t technology but leadership behavior, culture, and the willingness to unlearn. She explains why strategy must come before tools, how organizations waste months chasing the wrong use cases, and why AI doesn’t challenge culture — it scales it.
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Newsletter:Tune in to get deeper insights and all episodes. Subscribe at beginnersguide.nl
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This conversation offers a clear and practical blueprint for anyone leading teams, shaping strategy, or trying to stay relevant in an AI-enabled world.
In this episode you will learn:
How leaders can build an effective AI leadership mindset
Why organizations waste time on “AI use-case lists”
How generative AI distorted expectations across industries
How to build a culture of curiosity rather than control
Why middle management often resists AI transformation
The four elements of Louisa’s Leadership Anatomy framework
How Louisa uses three AIs as strategic thought partners
What AI literacy really means for modern organizations
How Europe’s AI culture compares to the U.S.
Quotes from the Episode:
“AI doesn’t challenge culture. It scales it.”
“If you don’t unlearn, you can’t lead.”
“AI won’t replace you — but bad leadership will.”Chapters:
00:00 Welcome & Introduction — Meet Louisa Loran
00:37 How curiosity led Louisa from Moët Hennessy to AI and Google
02:21 Early digital transformation and the roots of AI in logistics
04:46 Why strategy comes before tools — the real AI leadership lesson
07:15 The global “AI panic” and how leaders wasted 18 months on use-case lists
09:42 Rediscovering critical thinking in the AI era
11:56 Learning t… -
Democratizing AI: How Nebius Is Making AI Infrastructure Accessible for Everyone // REPOST
18 april 2026 · 49 min
In this episode of A Beginner’s Guide to AI, host Dietmar Fischer talks with Roman Chernin from Nebius, about how AI democratization is reshaping the enterprise world. Lees meer
Roman reveals what it really takes to move from prototype LLMs to reliable, scalable AI platforms - and why most companies don’t need to train their own models to harness AI’s potential.
📧💌📧
Tune in to get my thoughts and all episodes - don’t forget to subscribe to our Newsletter: beginnersguide.nl
📧💌📧
From his early years at Yandex, where machine learning quietly powered maps and search, to helping Nebius build global AI infrastructure, Roman’s story is a blueprint for how cloud platforms can make AI accessible to everyone.
He explains how Nebius Token Factory enables businesses to deploy AI applications fast, how to navigate the minefield of compliance and cost, and why real success in AI comes from better collaboration and iteration — not from “being a genius.”
🚀 Key Highlights
What democratizing AI means for modern enterprises
Why infrastructure scaling 10× a year forces constant reinvention
How Nebius bridges the gap between OpenAI and open-source ecosystems
Making AI usable for non-technical teams through better developer experience
Why Europe still has a chance to catch up in the AI race
How AI changes leadership, creativity, and collaboration
💡 Quotes from the Episode
“The goal isn’t to build more data centers - it’s to make AI usable for people who aren’t AI experts.”
“You don’t need your own LLM. You need a problem to solve - and the right infrastructure to do it.”
“If you want to scale a system ten times, you don’t fix it - you rewrite it.”
“Compute is becoming the new electricity, but we don’t want to be just a utility company.”
“The real bottleneck isn’t GPUs - it’s making AI usable, compliant, and cost-efficient for real businesses.”
“We can’t forbid AI use; it’s already here. The real challenge is helping society adapt fast enough.”
🧾 Chapters
00:00 Introduction…
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AI Is Creating a Global Identity Crisis - Says Derek Rydall
16 april 2026 · 58 min
🚀 The Hidden Cost of AI: Losing Meaning, Not Jobs Lees meer
AI is not just automating work. It is challenging the very foundation of human identity.
In this episode, Derek Rydall breaks down why the biggest risk of AI is not unemployment, but a global meaning crisis. As intelligence becomes cheap and abundant, the real question becomes: what are humans for?
You’ll learn why purpose is becoming the ultimate competitive advantage, how attention is being hijacked by algorithms, and what it takes to stay relevant in a world where machines outperform us.
📧💌📧
Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl
📧💌📧
🧠 Quotes from the Episode
“If you don’t know yourself better than the algorithm knows you, it will use you.”
“Intelligence is becoming a commodity. Humanity is becoming the moat.”
“The real danger of AI is not losing your job. It’s losing your sense of meaning.”
⏱️ Chapters
00:00 From Hacker to Monk to AI Thinker
04:00 The AI “Ark” Vision and Existential Risk
08:30 Why AI Creates a Meaning Crisis
13:30 What Happens When Intelligence Becomes Free
18:00 Identity Crisis and the Future of Work
23:00 How to Find Purpose in the AI Age
32:00 Attention Is the New Battleground
41:00 The Urgency: 12–24 Month Window
47:00 Practical Steps to Stay Relevant
🔗 Where to find Derek Rydall
Website: derekrydall.com
YouTube: Your Legendary Life
Podcast: Emergence
👤 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
Hosted on Acast. See acast.com/privacy for more information.
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We wanted Spock, but what we got is something closer to Kirk - Ben & Dietmar Discuss Everything AI
14 april 2026 · 55 min
🎙️ Machine Ethics Podcast x Beginner's Guide to AI Lees meer
AI is everywhere. But almost nobody agrees on what it actually is.
In this episode, Ben Byford from the Machine Ethics Podcast and Dietmar Fischer explore why AI feels intelligent while fundamentally being something very different.
From AI misconceptions to generative AI risks, this conversation breaks down the gap between perception and reality and why it matters for business leaders, marketers, and decision-makers.
You’ll learn why AI literacy is becoming essential, how misunderstanding AI creates real business risks, and what it takes to use AI responsibly in a rapidly changing landscape.
📧💌📧
Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl
📧💌📧
💡 Quotes from the Episode
“We wanted Spock, but what we got is something closer to Kirk.”
“The real danger is not AI itself, but how we misunderstand it.”
“AI feels intelligent, but that doesn’t mean it actually understands anything.”
⏱️ Chapters
00:00 What Is AI Really
05:30 AI vs Human Intelligence
10:15 Why People Misunderstand AI
18:40 AI as a Tool vs AI as a “Being”
26:30 The Risks of Trusting AI
34:30 AI, Society and Human Behavior
44:00 Future of AI Understanding
🔎 Where to find Ben
Website: Machine Ethics Podcast
LinkedIn: linkedin.com/in/ben-byford/
👤 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/
🎧 If you enjoyed this episode, share it with someone who still thinks AI is “intelligent.”
Hosted on Acast. See acast.com/privacy for more information.
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Why the Vatican’s Warning on AI Should Worry Everyone
11 april 2026 · 16 min
What does the Catholic Church actually think about artificial intelligence? A lot more than you might expect. Lees meer
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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Can AI Replace Wikipedia? Jonathan Fraine & Raja Amelung Explain Why It Cannot
9 april 2026 · 49 min
Artificial intelligence can generate answers fast, but can it generate knowledge you can trust? Lees meer
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.
You will learn:
✨ 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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Quotes from the Episode
💬 “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.”
Chapters
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 C…