If I’m being honest, my favorite tech invention is more of a breakthrough. In my cognitive science class, we learned about deep reinforcement learning (DRL), an advancement in artificial intelligence (AI). I’m especially intrigued by its application to game theory and decision-making models. I know not everyone is immediately fascinated, so I’d like to invite you to stand shoulder to shoulder with me for a moment and adopt a lens of wonder. Let’s travel back before the era of TikTok to Seoul, South Korea in 2016. A heated match between a machine, DeepMind’s AlphaGo, and the top Go player in the world, Lee Sedol, marked a significant milestone in AI development. AlphaGo’s victory was a turning point in AI-driven decision-making. Unlike traditional AI, which relied on brute-force search and predefined heuristics, AlphaGo employed deep neural networks combined with reinforcement learning to evaluate potential outcomes and develop novel strategies. This approach allowed AI to make decisions in ways that even human experts could not predict, demonstrating the potential of AI in strategic reasoning. Following AlphaGo, advancements like AlphaZero and MuZero refined these techniques further. Beyond board games, machine learning in AI has the potential to optimize real-world decision-making scenarios such as business strategy, cybersecurity, and crisis management without the noise of human emotion that often inhibits effective decision-making in heated moments. This breakthrough piqued my interest because of AI’s ability to model human decision-making. I am currently in a game theory class, where we analyze ‘players’ strategizing in highly competitive ‘games’ or situations—such as how to navigate a nationwide data breach. By combining my foundation in economics with my experience in leadership development, I have chosen to focus on game theory and crisis leadership specifically in the technology and cybersecurity fields. This decision is largely influenced by my father, who filled my childhood with stories of mini-network security crises and how he navigated them as the head on projects. Cyberattacks happen every second of every day (no joke, I’ve seen the logs), and with the rise of AI-driven cyber threats, organizations must stay at the forefront of cybersecurity to protect critical information. AI-driven decision-making models, inspired by milestones like AlphaGo, have the potential to revolutionize how organizations anticipate, prevent, and respond to threats. Applying game-theoretic models powered by neural networks can enhance proactive threat detection, optimize resource allocation, and improve overall security strategies. Beyond cybersecurity, the lessons from AI-driven game theory can also be applied to leadership and crisis management. In high-stakes environments, effective decision-making requires balancing risk, adapting strategies dynamically, and predicting the actions of others. These are core principles of game theory, and AI can serve as a powerful tool in modeling optimal leadership responses in complex scenarios. My long-term goal is to contribute to this field through research and practical applications, integrating AI, game theory, and leadership strategies to improve organizational resilience against crises. Following graduation, I intend to work in business technology and cybersecurity to gain industry experience while refining my knowledge of decision-making models. Ultimately, I plan to return to the University of Michigan to collaborate with my current supervisor on research that explores game theory, positive leadership, and crisis management in cybersecurity. By leveraging AI’s capabilities in modeling strategic interactions, I hope to develop frameworks that enhance decision-making in both security and leadership contexts, ensuring that organizations can navigate challenges with greater intelligence and efficiency. If you've read this far, thank you sincerely for continuing to inspire and show young women like myself that there is an important role for us to play in the STEM and IT fields!