Singapore vs. USA Education Systems, WEIRD AI Teddy Bears & US Senate $32B AI Investment Bill with Shiyan Koh - E428

Shiyan Koh, Managing Partner of  Hustle Fund, and ​​Jeremy Au talked about three main themes:

1. Singapore vs. USA Education Systems: Jeremy and Shiyan discussed differences in structure, funding, and outcomes. In Singapore, the education system is centralized with high academic rigor, while in the USA, quality varies significantly due to local property tax funding, leading to disparities between affluent and less affluent areas. They highlighted how the Singapore system is envied by global peers for its academic outcomes but faces internal criticism for being a "pressure cooker.” Shiyan also emphasized the personal nature of educational choices and the high costs associated with private international schools, which can be prohibitive for startup founders.

2. WEIRD AI Teddy Bears: Jeremy and Shiyan debated AI integration into children's toys and education. Jeremy expressed concerns about AI potentially replacing difficult human conversations with always-pleasant AI interactions. They discussed the inherent biases in LLM models, which are trained on data from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies. Embedding AI into education thus further propagates this worldview to the next generation, which may not reflect current, local or parental cultural values or norms.

3. US Senate $32B AI Investment Bill: Jeremy and Shiyan discussed the proposed legislation advocating for a $32 billion annual investment in AI. Jeremy added that the US is already a leader in AI investment, with private investments expected to reach $82 billion next year, more than double that of China. She questioned the need for further government investment in an area already heavily funded by the private sector and argued that government funds might be better spent on education, which offers broader societal benefits.

Jeremy and Shiyan also talked about parental competition for "good jobs”, the challenges in balancing academic rigor and student well-being, and the future implications of AI in the workforce.

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