This weekend, Vivian Rebrin was able to attend the second annual Women in Data Science Conference in St. Louis. The event took place in Washington University’s Emerson Auditorium. My colleague David Freni and I met some data scientists who work with our client Bayer Crop Science. We were able to listen to several women working in the industry, as well as Washington University’s Professor Liberty, describe the dangers of manipulating data for self-interest and the importance of asking the right questions. The main subject that stuck out to me was the manipulation of data. The two main brands that were affected by this in her examples were Starbucks and Uber. Each of these had their data distorted to sabotage their reputations. Her conclusion for the women in data science and entering it was to always ask these four questions when looking for results. Who was asked? What was asked? How was it interpreted? Why do we care? In the world of science, it is important to maintain humanism.
Next, we had an employee from Microsoft, who used to work at Bayer Crop Science, speak about the research she had been conducting to provide factory workers more safety through AI sound. Lastly, we heard from Bayer Crop Science on some new projects that they are working on to develop sustainable farming in an ever-growing population and what the future of AI holds for them. Bayer’s Bing Liu and Qinglin Duan discussed how one of the biggest challenges for farmers is how quickly the population is growing, and that by early 2050, the population will have reached 10 million. This poses a threat to farmers in terms of limited farmland, having to produce enough food with fewer resources to support our world population. Bayer Crop Science is working on solutions through plant breeding, crop protection, plant biotechnology, and digital advisors.
Two projects that they are currently working on are called the Trait Introgression Project where they are introducing Biotech traits to conventional breeding germplasm. Through repeat crossing to the conventional breed line, materials from the donor line (the line that brings in the biotech trait) will reduce to a negligible amount but only the traits of interest. The process is highly efficient at Bayer Crop through marketer technology, chipping predictions, multi-generation greenhouses, etc. The Women in Data Science Conference was an incredibly empowering event and showed me how far we’ve come in gender equality in the workforce. Big thank you to all of the incredible women who made this event happen and the attendees.