On AI Governance and Job Displacement: A Comparative Study of AI Policy in Vietnam and The United States

This paper brings together a useful body of Vietnamese AI-policy detail (Resolution 57, the 2025 AI Law and its risk-tiering, the National Digital Transformation agenda) that is hard to find synthesized in English, and it raises a worthwhile under-examined question: why Vietnamese attitudes toward AI remain so positive despite real labor-market exposure. Several steps would substantially raise its analytical contribution.

The most important is method transparency. Beyond reading relevant policy outputs, the paper does not specify an analytical approach. It is not clear whether the qualitative analysis proceeds by document analysis, discourse analysis, or process tracing, and because the sources, though listed, are not cited in-text, it is difficult to connect specific claims to specific evidence. This matters most for the broad discourse-level generalizations about how "Vietnamese society" and "American society" view AI, which are stated without a procedure that would let a reader see how they were reached. Naming the method and adding in-text attribution would make the argument far easier to follow and assess.

Second, the paper sets up its own central thesis but does not test it. It states that Vietnam and the US operate a socialist-oriented market economy and a market-led capitalist one respectively, and that AI policy reflects state-market relations, but it does not then link those political configurations to the specific features of each country's AI policy design. Drawing that connection explicitly, showing how the political setup produces the observed policy posture rather than merely sitting alongside it, is the analytical payoff the framing promises and would transform the paper.

Relatedly, the two cases are presented in parallel but not systematically compared. The four comparative dimensions announced in the methods (formation context, content, practices, outcomes) would be much more powerful executed as a structured side-by-side matrix than as sequential country narratives, and would also help rebalance a comparison that currently weighs heavily toward Vietnam.

Third, the quantitative material is presented but not analyzed. The figures are a welcome inclusion, but indicators such as GDP, inflation, and unemployment are largely displayed rather than connected to the central claim about AI and labor displacement, and the "quantitative methods" described in the design are not employed with enough robustness to generate findings. Tying each data series explicitly to the argument, or trimming those that do not bear on it, would tighten the empirical core considerably.

Finally, the headline observation, that low Vietnamese resentment toward AI may reflect shallow adoption, currently rests mainly on a single industry-sponsored survey (AWS-Strand). Testing it against alternative explanations and grounding it in the rigorous sources already on the reference list, especially the ILO's 2026 Vietnam exposure brief and Brynjolfsson's recent employment-effects work, both cited but not analytically used, would give this promising question a much firmer answer. The raw material for a strong comparative case study is here; the next step is adding a robust analytical method.

This project addresses an important and timely policy issue: how AI adoption may affect labor markets and how different governance models respond to that challenge. The comparison between Vietnam and the United States offers a useful starting point for understanding how national development strategies, institutional structures, and public attitudes shape AI policy priorities. To strengthen the contribution further, the analysis could more clearly connect labor displacement to the hackathon’s AI safety framing, for example by explaining how workforce disruption becomes a governance or societal risk and what concrete policy mechanisms could mitigate it. The methodology would also benefit from making the quantitative component more visible, through clearer indicators, comparative tables, or a more explicit explanation of how the evidence supports the main findings. Overall, this is an informative and relevant comparative policy essay with good potential, especially if future work deepens the evidence base and translates the comparison into more actionable governance recommendations.

The comparison reads clearly and the Vietnam-side is well done: the policy trajectory from Resolution 52-NQ/TW through the 2025 AI Law is a useful, well-sourced synthesis, and "AI policy mirrors each country's development model" is a fair thesis. The gap is between what you set up and what you delivered. You promise a quantitative strand (AI-exposure indices, ILO, OECD, BLS) but the analysis stays descriptive, with none of the tables or comparisons that would back it, and the US half is much thinner than the Vietnam half, which is a problem when the comparison is the whole point. Three things to consider: put at least one real comparative figure on the page from the data you already cite, build the US side out to match Vietnam, and fix the section numbering, since it jumps around. Also say the safety part out loud, which displacement gaps create risks that are not just economic. Solid base, needs its evidence layer.