Principal Data Scientist, Applied AI @ interos.ai | Perplexity AI Business Fellow | Award-Winning Data and AI Expert @ Correlation One
Did AI tools help our team win a hackathon? Recently I was in Oxford working on a team doing social network analysis of trade data as part of the summer program. The project was a hackathon, so we had two days to do some analysis and find some insights using social network analysis. Our team was a unique mix of experiences: some hadn't worked with trade data before, others were new to social networks, and several of us had little experience doing business presentations. Three observations: 🔬AI Accelerated our Research We were all using AI tools. Each team member gravitated toward different tools depending on their needs and AI fluency. Example: I used Perplexity to create an executive research report about Bulgaria's economy, which we used to gut check our analyses. Rather than spending hours digging through IMF and World Bank reports, I could quickly generate just enough understanding to get us to our time-sensitive deadline. 🧠 Domain Expertise Becomes Even More Critical The most counterintuitive finding: our expertise became more critical as we used AI tools, not less. Critical thinking and research—the bread and butter of people with grad school degrees—served as our most powerful coins of the realm. Even operating outside our subject matter expertise, we were cautious and thoughtful about AI results, keeping our crap detectors on high alert. Sifting through AI results—from poorly written scripts to clear misinterpretations of source documents—was essential to our success. Rather than using AI tooling to override our analytical judgment, we found those skills essential to extracting useful information from the tools we used. 👐Collaboration Feels Different Now While AI tools mattered a bit in cutting down the time it took to get a complete product, I think the larger impact it had was in how we collaborated and focused. What I really found was that the tools helped us to maintain our focus and stay on task in terms of the work we did. And overall, the strategy worked – each of us was able to contribute far more of our unique talent to the team project when we used an AI. 🔑 Takeaway AI tools are largely worthless when people attempt to use them to override domain expertise, strategic analysis, and critical thinking. They add value when they augment team processes that prize critical thinking and domain expertise. The tools don't replace deep knowledge—they enable experts to work in a more focused, efficient, and deliberative way. To me, the future of AI in complex collaborative systems will hinge on how teams can leverage AI tooling to amplify and value of human expertise across traditional boundaries. #AI #collaboration #research #academictwitter #machinelearning #socialnetworkanalysis #oxford #gradschool #teamwork #academia