<p>Machine learning is everywhere, yet rarely understood. In this episode of <em>A Beginner’s Guide to AI</em>, we strip away the hype and explain how machine learning actually works, why it’s so powerful, and where it quietly goes wrong.</p><br><p>You’ll learn how machines are trained on data rather than rules, why predictions are not understanding, and how real-world systems can produce unfair outcomes even when they look accurate. A real healthcare case shows how a cost-based algorithm systematically underestimated medical need, revealing the hidden dangers of proxy metrics.</p><br><p>This episode covers machine learning basics, ethical AI, algorithmic bias, fairness, and transparency in a way that is accessible to beginners and useful for professionals.</p><br><p>📧💌📧</p><p>Tune in to get my thoughts and all episodes, don’t forget to subscribe to our Newsletter: <a href="https://beginnersguide.nl" rel="noopener noreferrer" target="_blank">beginnersguide.nl</a></p><p>📧💌📧</p><br><p><strong>Quotes from the Episode</strong></p><ul><li>“Machine learning gives you what you measure, not what you value.”</li><li>“The algorithm didn’t invent bias. It learned it efficiently.”</li><li>“A perfect prediction of the wrong thing is still failure.”</li></ul><p><br></p><p><strong>Chapters</strong></p><p>00:00 Machine Learning Without the Myth</p><p>04:12 How Machines Learn From Data</p><p>10:45 Types of Machine Learning</p><p>18:30 The Cake Example</p><p>26:05 Healthcare Case Study</p><p>36:40 Ethics, Bias, and Proxies</p><p>45:50 Final Takeaways</p><br><p><strong>About Dietmar Fischer: </strong></p><p>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.</p><br><p>Music credit: Modern Situations by Unicorn Heads</p><hr><p style='color:grey; font-size:0.75em;'> Hosted on Acast. See <a style='color:grey;' target='_blank' rel='noopener noreferrer' href='https://acast.com/privacy'>acast.com/privacy</a> for more information.</p>