Technology, Innovation, and Great Power Competition

Course Context

A new approach for teaching policy to increase impact

At the Stanford Gordian Knot Center, we're redefining how policy is taught and applied. Students don’t just study policy—they solve real-world problems at the intersection of technology and global competition. Through engagement with government sponsors, AI-powered policy analysis, and interviews with key stakeholders, they develop actionable solutions that address pressing global challenges. Together, these elements create a powerful framework for addressing real policy challenges.

1. Policy problems directly from government sponsors:

Students engage directly with government sponsors to tackle real-world problems, applying entrepreneurial approaches to problem discovery. This hands-on experience provides deep insights into technology and innovation challenges, with the goal of delivering clear, actionable recommendations.

2. AI-powered synthesis of vast policy content: 

Students use AI tools to analyze vast amounts of policy content— books, articles, and reports — related to their chosen problems. AI tools enable students to integrate insights from the broader policy landscape and the technical details of the problems.

3. Interview-driven problem discovery: 

Students conduct 40 interviews with key stakeholders, validating assumptions and gathering deep insights. AI tools help extract patterns across these interviews, enriching students' understanding and grounding their recommendations. Entrepreneurial methods for problem discovery enable students to test hypotheses and validate assumptions with speed and urgency.

We are combining the power of AI with entrepreneurial problem solving to make real policy impact with speed and urgency. While policy change takes time, our students create urgency and deeper insight for government leaders to make better informed decisions in the global competition for emerging technology, where the stakes have never been higher.

AI and Policy Analysis

Harnessing AI for policy analysis

Purpose and Application

In this course, AI tools are integrated to revolutionize how we approach policy analysis and problem-solving. By leveraging AI, we aim to enhance your ability to navigate vast amounts of data, identify key insights, and generate innovative solutions to complex policy challenges. The use of AI mirrors real-world applications where technology and strategic thinking intersect, providing you with critical skills for the ever-evolving landscape of global power dynamics.

What We Will Be Doing with AI

1. Data Synthesis: AI will be used to process and analyze large volumes of policy content, including academic articles, policy papers, and news reports. This will allow you to quickly distill essential information and focus on the most pertinent details relevant to your policy challenges.
2. Interview Analysis: After conducting interviews with stakeholders and experts, AI tools will assist in synthesizing the data collected. This process will help you identify patterns, themes, and insights that might not be immediately apparent, facilitating a deeper understanding of the issues at hand.
3. Insight Generation: AI will play a pivotal role in helping you validate problem statements and develop hypotheses. By using AI to explore various scenarios and potential outcomes, you will gain a more comprehensive view of possible solutions and their implications.
4. Accelerating Analysis and Decision-Making: This course emphasizes the use of AI tools to accelerate your analysis, enabling you to work with greater speed and urgency. By effectively integrating AI into your research and problem-solving processes, you will be better equipped to tackle complex policy challenges and deliver impactful solutions.

Expectations for AI Use

1. Showcasing AI Integration: Throughout the course, you will be expected to incorporate AI tools into your work strategically. Your assignments and presentations should clearly demonstrate how AI contributed to your analysis, highlighting the unique insights and efficiencies gained through its use. Rather than defending the use of AI, your focus should be on showcasing the value it added to your work and the innovative solutions it helped uncover.
2. Demonstrating Linkages to Facts: While AI can help generate insights, it is essential to ground your conclusions in verifiable facts. You must ensure that the insights derived from AI are supported by empirical data and credible sources. This involves critically evaluating AI-generated outputs and cross-referencing them with other research to validate your findings.
3. Do not feed AI tools confidential information: Do NOT feed any names of interviewees or confidential information into AI tools. It can be assumed that the information will be used in training models. Doing so is a breach of trust with project sponsors and interviewees.

Important Cautions When Using AI

1. Critical Evaluation: While AI is a powerful tool for processing information, it is crucial to apply your own critical thinking and analysis. AI can highlight trends and patterns, but it is your responsibility to interpret these findings within the broader context of your research and policy objectives.
2. Bias Awareness: AI tools are only as unbiased as the data they are trained on. Be aware of potential biases in the data and strive to counteract them by cross-referencing with diverse sources and perspectives.
3. Data Limitations: Remember that AI operates on existing data and algorithms, which may not capture the full complexity of human dynamics and decision-making. Use AI as a supplement to, not a replacement for, qualitative insights gained through personal research and engagement with experts.
4. Confidentiality and Data Privacy: As a reminder, be aware that uploading confidential or proprietary information into AI tools may result in a loss of confidentiality, as many generative AI tools use input data as training data. It is absolutely essential not to upload confidential information into AI tools, as doing so would breach your commitments to sponsors and interviewees. Violations of this policy are clear violations of course policy and will be treated seriously. Always ensure that your use of AI complies with data privacy standards and respect the confidentiality of all involved parties.

By actively and appropriately integrating AI into your policy analysis, you will develop the skills necessary to navigate the intersection of technology and international relations effectively. This course will prepare you to harness the power of AI responsibly, enhancing your ability to make a meaningful impact in the field of global policy.

Expectations for reading and content synthesis

In this course, there are no traditional required textbooks or expectations for reading complete texts beyond Lesson 1 assigned readings. Instead, students are expected to actively engage in synthesizing a wide range of policy content from various sources. Each class session will feature a list of relevant policy texts, and this content should be assessed in its entirety as part of your preparation – but it should not be considered an exhaustive set of content for you to consider. A review of large amounts of text is made possible through the assistance of AI tools. This approach mirrors the real-world demands of policy analysis, where the ability to rapidly gather, process, and apply information is essential to high performance.

Expectations

1. Proactive Research: You are expected to independently seek out and engage with relevant policy content that aligns with your team’s problem statement. Utilize AI tools to streamline your research process, quickly identifying key insights from academic articles, policy papers, government reports, and other credible sources.
2. Synthesis and Application: Your focus should be on synthesizing information across multiple sources to derive actionable insights. This involves going beyond surface-level understanding and delving deeper into texts to grasp the nuances of policy issues. Your ability to connect these insights directly to your problem statements will be critical in your evaluations.
3. Articulation of Insights: In your assignments and presentations, you should clearly articulate how you used the information gathered to inform and address your problem statements. This includes demonstrating a clear linkage between the policy content you reviewed and the solutions or hypotheses you propose, ensuring that your conclusions are grounded in a comprehensive understanding of the material.
4. Evaluation Criteria: Your performance will be assessed based on how effectively you can tie the synthesized policy content to your specific problem statements. This includes showing that your research and analysis are thorough, well-informed, and directly relevant to the challenges you are addressing.

This policy around texts, reading, and content synthesis is designed to prepare you for the complexities of real-world modern day policy work, where independent research, critical analysis, and the ability to apply knowledge to practical problems are essential skills.