May 15, 2018
At the Food Safety Summit in Rosemont, IL, on May 9th, 2018, we had the opportunity to present on topics that sit at the core of our work at Iwaspoisoned.com: machine learning, AI, and confirmation bias in crowdsourced foodborne illness reporting. Our discussions explored the utilization of crowdsourced data in probing foodborne illness outbreaks, discussing its benefits and challenges. Our focus was on how machine learning and AI can enhance the accuracy and efficiency of identifying potential foodborne illness outbreaks from the vast amounts of data generated by crowdsourcing. We also addressed the critical issue of confirmation bias in this context, highlighting the need for algorithms that can discern valid reports from noise.
The presentation sparked engaging discussions on the potential and limitations of technology in food safety surveillance. We delved into how these advanced tools can transform the way we track and respond to food safety incidents, making the process faster and more reliable. This topic, reflecting the intersection of technology and public health, underscored the importance of innovation in our ongoing battle against foodborne illnesses. Presenting at the summit not only allowed us to share our insights but also to learn from other experts in the field, further enhancing our approach to leveraging technology for public health.
Click
here if you want to learn more about past or future speaking engagments we have attended and will attend.
