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Another Crazy Day in AI: The Psychology Behind Machine Intelligence

Another Crazy Day in AI: An Almost Daily Newsletter

Hello, AI Enthusiasts.


As the day wraps up, let’s explore the intriguing connections in the realm of AI! 🌙


While we often think about algorithms and data in AI discussions, the influence of psychology is foundational. Delve into how insights from the human mind have guided the development of AI and continue to shape its future. 🧠


Plus, learn why many employees are using AI tools at work without approval, a practice known as "shadow AI." On another note, Meta has launched its Frontier AI Framework to guide risk assessment and model release decisions.


Here's another crazy day in AI:

  • The brain science behind AI

  • Why workers are smuggling AI into their jobs

  • Meta’s open-source approach to AI safety

  • Some AI tools to try out


 

TODAY'S FEATURED ITEM: Before AI, There Was Psychology


Image Credit: Wowza (created with Ideogram)

Image Credit:Wowza (created with Ideogram)


What if understanding the human mind is the key to building smarter machines?


When we think about artificial intelligence, we often focus on algorithms, data, and computing power. But long before AI became what it is today, psychologists were already laying the groundwork by studying how humans learn, adapt, and solve problems. This article by Chris Ludlow and Armita Zarnegar, featured in The Conversation, explores the deep connection between psychology and AI—how insights from the human brain helped shape machine intelligence and continue to influence its development today.



How the human mind shaped machine intelligence:

  • Neural networks began with human learning theories – Donald Hebb’s 1949 model of learning inspired early artificial neural networks.

  • Machines that learn like humans – Frank Rosenblatt’s perceptron, developed in the 1950s, was built on Hebb’s ideas, marking AI’s first steps in pattern recognition.

  • Deep learning’s psychological foundation – David Rumelhart and colleagues advanced neural networks in the 1980s, leading to the deep learning models we use today.

  • The challenge of self-awareness – AI lacks metacognition, or the ability to reflect on its own thinking, a concept psychologist John Flavell explored in human cognition.

  • Problem-solving without prior experience – AI researchers are turning to psychological theories to help machines make decisions in unfamiliar situations.

  • The limits of AI reasoning – Studies by Daniel Kahneman suggest that AI explanations might be just as flawed as human reasoning biases.

  • AI’s impact on human intelligence – Just as taxi drivers’ brains adapt to navigation, AI could be shaping how we process information and solve problems.



Psychology has influenced AI for decades, providing insights into learning, decision-making, and adaptation. But the relationship goes both ways. As AI continues to advance, it’s also challenging our understanding of human intelligence. What does it mean to "think" or "learn" when a machine can process vast amounts of information in ways we can't?


At the same time, AI is changing how we interact with the world. From recommendation systems to automated decision-making, it’s influencing our choices and perceptions, sometimes in ways we don’t fully understand. As this technology continues to evolve, psychology will remain essential—not just for improving AI, but for helping us understand its impact on human behavior and society.





Read the full article here.

 

OTHER INTERESTING AI HIGHLIGHTS:


Why Workers Are Smuggling AI Into Their Jobs

/Sean McManus, Technology Reporter on BBC


Many employees are using AI tools at work without approval, a practice known as "shadow AI." Workers cite reasons like IT restrictions, slow approvals, or a preference for better tools. While AI boosts productivity, it also raises security concerns, as unauthorized AI use could expose sensitive data. Companies are now grappling with whether to ban AI or find ways to safely integrate it into workflows.



Read more here.

 

Meta’s Open-Source Approach to AI Safety

/Meta


Meta has introduced its Frontier AI Framework to guide risk assessment and model release decisions, aligning with global AI safety commitments. The framework focuses on cybersecurity threats and risks related to chemical and biological weapons, balancing innovation with security. By maintaining an open-source approach, Meta aims to encourage collaboration while mitigating catastrophic risks. As AI evolves, Meta plans to refine its strategy to ensure responsible development.



Read more here.

Check the framework here.

Source: Meta
Source: Meta
 

SOME AI TOOLS TO TRY OUT:


  • Tana - An AI-native workspace that turns notes into tasks, webpages, and more.

  • Sonofa - Converts reading materials into podcasts for on-the-go listening.

  • Marketeam - AI-powered assistants for content marketing, SEO, and AEO.

 

That’s a wrap on today’s Almost Daily craziness.


Catch us almost every day—almost! 😉

 

EXCITING NEWS:

The Another Crazy Day in AI newsletter is now on LinkedIn!!!



Wowza, Inc.

Leveraging AI for Enhanced Content: As part of our commitment to exploring new technologies, we used AI to help curate and refine our newsletters. This enriches our content and keeps us at the forefront of digital innovation, ensuring you stay informed with the latest trends and developments.





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