Not So Standard Deviations

178 - Hilary is Cranky About Everything

Aug 22, 2023

Hosts discuss concerns about data corruption and bias in machine learning models, regulation of language models and its comparison to cars, racial bias and consequences of facial recognition technology, promoting rules and standards to influence behavior, technology as a weapon and its long-term consequences, safety benefits of self-driving cars for parenting, challenges of parenting and upcoming school year, iterating through multiple steps of analysis and decision-making, and the significance of framed degrees in home offices.

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Quick takeaways

Language models pose significant existential risks that need to be addressed by policymakers and the public.

Regulating language models is a complex challenge due to their intangible nature and requires international collaboration.

Addressing bias in machine learning is important, but it should be balanced with addressing broader threats and potential dangers associated with language models.

Deep dives

Importance of Understanding the Dangers of Advanced Technology

The podcast episode explores the need for a broader awareness of the potential dangers associated with the rapid development of advanced technology, particularly language models (LLMs). The conversation highlights the scale of the threat posed by LLMs in the wrong hands, emphasizing the importance of considering the existential risks rather than focusing solely on issues like bias in data sets. It is suggested that the public and policymakers should have a more informed understanding of the potential harm and work towards strategies to mitigate the risks.