US and China Vie for AI Leadership in K-12 Education
Two new national plans promise to overhaul classrooms with AI. Here’s how the US and China differ – and overlap
Hot on the heels of China's plans to embed AI in all levels of teaching and education, the US has launched a wide-ranging executive order on Advancing Artificial Intelligence Education for American Youth. Both recognize that early investment in AI and education is critical to future economic leadership and success. Yet despite some broad areas of alignment, the two strategies diverge on aims, ambitions, and approaches.
In the US, the just-released Executive Order on Advancing Artificial Intelligence Education for American Youth lays out plans to deeply embed AI learning, education, and use, within the K-12 system. In part it starts to rebuild from a systematic dismantling of AI-focused initiatives from the previous administration — including the 2023 Executive Order on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence which was rescinded by the Trump Administration in January. But it also responds to a growing awareness that the US cannot afford not to invest in the skills, understanding and innovation that will underpin global relevance and influence in an AI-driven future.
And much of this awareness stems from the breakneck speed at which China is preparing for this selfsame future.
Just last week it was reported that China is setting out to integrate artificial intelligence applications into teaching, textbooks, and the (largely centralized) school curriculum, as it moves to overhaul education in an age of AI. As with the US, there’s a clear focus on long term global economic influence and impact. But China’s approach also differs from that being taken by the US in ways that reflect different social and cultural perspectives and goals.
I’ve attached a detailed comparison of the two approaches being taken to AI in education at the bottom of this article.1 It’s too long to include directly, but is well worth reading if you are interested in an in-depth analysis of how policy approaches align and converge around AI in K-12 education in particular, and what this might mean for the future.
However I did want to reflect on some of more salient points in comparing emerging strategies and policies on AI in K-12 education the US and China:
Transformation and disruption are coming: Both countries recognize the transformative nature of AI (even if it doesn’t reach the hyperbolic heights of artificial general intelligence any time soon), and the need to invest early and fast in equipping future generations to thrive in an AI future.
The stakes are high: Both countries realize that the geopolitical stakes are high, and not to invest in AI in K-12 education could mean global irrelevance in the future.
Integration: Both countries understand that smart integration of AI in education will most likely transform learning in positive ways.
Divergent approaches: The US approach to AI in education focuses on economic growth, geopolitical power and influence, and personal empowerment. In contrast, while China is also looking at long term strategies to ensure the same, it is also aligning policies with securing technological independence, together with collective advancement and societal flourishing — albeit within the context of the country’s underlying cultural philosophies. China also emphasizes the importance of maintaining and extending “soft power” through the integration of AI through society (including the skills and abilities of upcoming generations), and cultivating what are referred to as “A-HERO” qualities (AI literacy, High-order thinking, Ethical thinking, Resilience, Openness).
Responsible and ethical AI: Emerging from this, there is a more overt emphasis on AI ethics, responsible use, and public value growth beyond economic growth in China. Un the US, it is implied that these will be a natural outgrowth of economic growth and geopolitical strength, although this is not explicitly indicated in the executive order.
Centralized versus distributed approaches: China has a centralized approach to education policy implementation that means it is fast, agile, and can facilitate rapid and lasting impacts. At the same time, the country has built-in rigidity that may make it fragile in a rapidly changing world. In contrast, the US approach is distributed and more reliant on partnerships — with a far greater degree of autonomy at the state and regional level — with the government providing incentives for innovation and entrepreneurial experimentation rather than dictating how AI is integrated into education. The risks to the US are slower and more patchy adoption, potentially leading to students in some areas being left behind. The benefits are far greater resilience under uncertainty as AI develops.
Collaborative opportunities: While the two approaches to AI integration into K-12 education and the long term political goals associated with this differ, there are win-win opportunities for collaboration between China and the US on AI in education as AI becomes a global challenge/opportunity that transcends national politics.
These are just my first-cut top-level reflections though — remembering that the White House Executive Order is only a day old. For a much deeper analysis, check out the report below:
This is part of our exploration of leveraging AI tools like OpenAI’s Deep Research in the work we do in ASU’s Future of Being Human initiative — usual cautions apply for AI-generated analysis, although we are developing a “developed by AI, checked by humans” workflow.