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#81 - Is AI Outpacing Ethics? Machine Learning in the Real World | Marijn Markus cover
#81 - Is AI Outpacing Ethics? Machine Learning in the Real World | Marijn Markus cover
Let's Talk AI

#81 - Is AI Outpacing Ethics? Machine Learning in the Real World | Marijn Markus

#81 - Is AI Outpacing Ethics? Machine Learning in the Real World | Marijn Markus

1h15 |20/08/2025
Play
undefined cover
undefined cover
#81 - Is AI Outpacing Ethics? Machine Learning in the Real World | Marijn Markus cover
#81 - Is AI Outpacing Ethics? Machine Learning in the Real World | Marijn Markus cover
Let's Talk AI

#81 - Is AI Outpacing Ethics? Machine Learning in the Real World | Marijn Markus

#81 - Is AI Outpacing Ethics? Machine Learning in the Real World | Marijn Markus

1h15 |20/08/2025
Play

Description

AI is evolving fast, but are our systems, ethics, and infrastructure keeping up?


In this episode, Thomas Bustos and Marijn Markus break down the complex interplay between innovation and responsibility in artificial intelligence and machine learning. They examine current limitations in explainability and bias, and unpack what it will take to build scalable, transparent, and human-centric systems.


With examples from healthcare and finance, and a strong focus on aligning AI with social good, this episode offers both technical depth and strategic perspective. Whether you’re designing ML pipelines or debating LLM regulation, this conversation delivers insight you won’t want to miss.


Top Insights:

  • Ethical and Data Challenges: AI systems must navigate ethical considerations and data privacy concerns, ensuring transparency and accountability.

  • Innovation and Impact: AI has the potential to revolutionize industries, from healthcare to finance, by driving advancements and creating new opportunities.

  • Regulatory and Legacy Issues: Balancing innovation with necessary regulations and overcoming legacy systems are key challenges for AI adoption.

  • Bias and Misinformation: Addressing bias in AI models and combating misinformation are critical for ensuring AI's positive impact on society.

  • Job Market Evolution: While AI may automate some jobs, it also creates new opportunities, emphasizing the need for adaptability and skill diversification.

  • Human Responsibility: The importance of human oversight in AI systems is crucial, as technology should serve humanity's best interests.


Connect with Marijn Markus

Connect with Thomas Bustos & Let's Talk AI


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Description

AI is evolving fast, but are our systems, ethics, and infrastructure keeping up?


In this episode, Thomas Bustos and Marijn Markus break down the complex interplay between innovation and responsibility in artificial intelligence and machine learning. They examine current limitations in explainability and bias, and unpack what it will take to build scalable, transparent, and human-centric systems.


With examples from healthcare and finance, and a strong focus on aligning AI with social good, this episode offers both technical depth and strategic perspective. Whether you’re designing ML pipelines or debating LLM regulation, this conversation delivers insight you won’t want to miss.


Top Insights:

  • Ethical and Data Challenges: AI systems must navigate ethical considerations and data privacy concerns, ensuring transparency and accountability.

  • Innovation and Impact: AI has the potential to revolutionize industries, from healthcare to finance, by driving advancements and creating new opportunities.

  • Regulatory and Legacy Issues: Balancing innovation with necessary regulations and overcoming legacy systems are key challenges for AI adoption.

  • Bias and Misinformation: Addressing bias in AI models and combating misinformation are critical for ensuring AI's positive impact on society.

  • Job Market Evolution: While AI may automate some jobs, it also creates new opportunities, emphasizing the need for adaptability and skill diversification.

  • Human Responsibility: The importance of human oversight in AI systems is crucial, as technology should serve humanity's best interests.


Connect with Marijn Markus

Connect with Thomas Bustos & Let's Talk AI


Hosted by Ausha. See ausha.co/privacy-policy for more information.

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Description

AI is evolving fast, but are our systems, ethics, and infrastructure keeping up?


In this episode, Thomas Bustos and Marijn Markus break down the complex interplay between innovation and responsibility in artificial intelligence and machine learning. They examine current limitations in explainability and bias, and unpack what it will take to build scalable, transparent, and human-centric systems.


With examples from healthcare and finance, and a strong focus on aligning AI with social good, this episode offers both technical depth and strategic perspective. Whether you’re designing ML pipelines or debating LLM regulation, this conversation delivers insight you won’t want to miss.


Top Insights:

  • Ethical and Data Challenges: AI systems must navigate ethical considerations and data privacy concerns, ensuring transparency and accountability.

  • Innovation and Impact: AI has the potential to revolutionize industries, from healthcare to finance, by driving advancements and creating new opportunities.

  • Regulatory and Legacy Issues: Balancing innovation with necessary regulations and overcoming legacy systems are key challenges for AI adoption.

  • Bias and Misinformation: Addressing bias in AI models and combating misinformation are critical for ensuring AI's positive impact on society.

  • Job Market Evolution: While AI may automate some jobs, it also creates new opportunities, emphasizing the need for adaptability and skill diversification.

  • Human Responsibility: The importance of human oversight in AI systems is crucial, as technology should serve humanity's best interests.


Connect with Marijn Markus

Connect with Thomas Bustos & Let's Talk AI


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Description

AI is evolving fast, but are our systems, ethics, and infrastructure keeping up?


In this episode, Thomas Bustos and Marijn Markus break down the complex interplay between innovation and responsibility in artificial intelligence and machine learning. They examine current limitations in explainability and bias, and unpack what it will take to build scalable, transparent, and human-centric systems.


With examples from healthcare and finance, and a strong focus on aligning AI with social good, this episode offers both technical depth and strategic perspective. Whether you’re designing ML pipelines or debating LLM regulation, this conversation delivers insight you won’t want to miss.


Top Insights:

  • Ethical and Data Challenges: AI systems must navigate ethical considerations and data privacy concerns, ensuring transparency and accountability.

  • Innovation and Impact: AI has the potential to revolutionize industries, from healthcare to finance, by driving advancements and creating new opportunities.

  • Regulatory and Legacy Issues: Balancing innovation with necessary regulations and overcoming legacy systems are key challenges for AI adoption.

  • Bias and Misinformation: Addressing bias in AI models and combating misinformation are critical for ensuring AI's positive impact on society.

  • Job Market Evolution: While AI may automate some jobs, it also creates new opportunities, emphasizing the need for adaptability and skill diversification.

  • Human Responsibility: The importance of human oversight in AI systems is crucial, as technology should serve humanity's best interests.


Connect with Marijn Markus

Connect with Thomas Bustos & Let's Talk AI


Hosted by Ausha. See ausha.co/privacy-policy for more information.

Share

Embed

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