Artificial intelligence (AI) transformed podcast with Ed Fowler

Dive into the future with 🤖 Artificial intelligence (AI) transformed podcast 🎙

Where we unravel the mysteries of Artificial Intelligence

Join us as we explore 🔪 cutting-edge technologies, decode 📔 the ethics of AI, and meet the brilliant minds shaping our world 🌍

From self-driving cars 🏎 to AI in healthcare 👩‍⚕️ , we demystify the tech that’s changing everything

Get ready to feed your curiosity and stay ahead in the hashtag#AI revolution

Tune in now and let’s talk AI!

hashtag#linkedinlive hashtag#podcast hashtag#socialselling hashtag#artificialintelligence hashtag#machinelearning

Key articles:

https://www.csoonline.com/article/1071129/generative-ai-could-erode-customer-trust-half-of-business-leaders-say.html
illustrating the issues around AI and customer trust

https://www.thebanker.com/Capital-markets-face-regulatory-scrutiny-over-AI-use-1701764934
AI, regulation and market manipulation fears

https://www.nature.com/articles/d41586-023-03817-6
AI and fundamentals around reproducibility and trust in science

https://www.science.org/content/article/materials-predicting-ai-deepmind-could-revolutionize-electronics-batteries-and-solar
AI and further exploration around reproducibility, this time in the deep science of materials

Finally

Generative AI puts trust in the news media to the test

AI and media trust, the underpinnings of AI generated misinformation and AI powered echo chambers

An apt quote:

“Finding the occasional straw of truth awash in a great ocean of confusion and bamboozle requires vigilance, dedication, and courage. But if we don’t practice these tough habits of thought, we cannot hope to solve the truly serious problems that face us—and we risk becoming a nation of suckers, a world of suckers, up for grabs by the next charlatan who saunters along”. Carl Sagan “The demon haunted world: Science as a candle in the dark” 1996

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And here is the outline:

Introduction
Present the thesis inspired by Carl Sagan: the importance of deep understanding, rationality, and the ability to reproduce knowledge from first principles in the context of AI.
Briefly explain how this thesis will be examined through the lens of AI in different sectors, highlighting the need for responsible AI development that aligns with these principles.
Segment 1: Scientific Research – Rationality and Replicability
Discuss the role of AI in scientific research, emphasizing the importance of rationality and the ability to replicate findings.
Explore how AI can both aid and complicate the pursuit of replicable science, touching upon Sagan’s emphasis on scepticism and empirical validation.
Segment 2: Materials Science – Understanding from First Principles
Highlight the AI-driven discoveries in materials science, particularly focusing on the need for understanding these discoveries from fundamental principles.
Discuss how this approach aligns with Sagan’s thesis, ensuring that AI’s contributions to materials science are both innovative and grounded in rational, foundational knowledge.
Segment 3: Capital Markets – Rational Decision Making with AI
Address the integration of AI in capital markets, focusing on how it can aid or hinder rational decision-making.
Explore the importance of ensuring that AI systems in financial sectors are developed and used based on rational principles and transparent methodologies, reflecting Sagan’s ideals.
Segment 4: Media and Information – Fostering a Rational Public Discourse
Delve into the role of AI in media, particularly its impact on public discourse and the spread of information.
Discuss the need for media to use AI in ways that promote rationality and critical thinking among the public, resonating with Sagan’s advocacy for scepticism and understanding.
Segment 5: Business and Trust – Compliance with Rational Standards
Incorporate the concerns around generative AI in business, emphasizing the need for security and compliance measures that align with rational, principled approaches.
Discuss how businesses can use AI to not only enhance operations but also maintain trust and adhere to rational, ethical standards.
Conclusion
Summarize how each sector’s use of AI intersects with the themes of understanding, rationality, and the ability to reproduce knowledge from first principles.
Conclude with reflections on the necessity of aligning AI development with these Sagan-inspired principles to foster a more informed, rational, and trustworthy future.

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