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Posted by seancorning on July 5th, 2023
Posted in: Blog
This year the New England Science Bootcamp for Librarians was back in person for the first time since 2019, hosted for three days this June at UMass Amherst. While I was involved in planning last year’s online Boot Camp, I was excited to attend in person for the first time!
The goal of this Boot Camp is to immerse librarians in a selection of scientific topics, led by researchers at the host institution, improving their general knowledge of these topics and enabling to better serve their communities. This year we selected the topic areas of Kinesiology, Food Science and Machine Learning, and capped the week off with a workshop on Grant Writing for Librarians. If you’re interested in the early history of the Boot Camp, UMass Chan’s Sally Gore wrote an article in 2011 about the program.
Recordings of the topical sessions will be available on the Science Bootcamp YouTube channel once they have been processed.
The first sessions of the program were conducted by Professors John Sirard and Amanda Paluch of the Department of Kinesiology. Professor Sirard provided an overview of the discipline, emphasizing how broad kinesiology as the “study of human movement” is as a research field. As you can imagine, there are many approaches to human movement, from a neuroscientific perspective, looking at how the brain controls the body’s movement, to a health and fitness perspective, looking at how different kinds of physical activity can impact health in positive or negative ways. The work Professor Paluch presented focuses on this relationship between physical activity and health, using epidemiological techniques, wearable activity monitors and large meta-analyses to draw stronger conclusions about the benefits of activity than have been possible in the past.
Similar to the previous session, an emphasis here was on how large a discipline Food Science is. In her introduction, Professor Lynne McLandsborough , discussed how Food Science is concerned with “food from the farm to the fork”, including everything from seed supply to processing safety to consumer preferences. Professor Alissa Nolden discussed in her talk the importance of consumer preferences in the success of new, or old, types of food, especially in the context of attempts to shift the food supply in a more sustainable direction. She looks at the characteristics and perceptions of plant based alternative foods, coconut milk yogurt for example, especially compared to their animal-based varieties. At the population level, reducing the consumption of animal based food could have a major impact on environmental impact, and Professor Nolden discussed heavily how understanding the way these alternatives are experienced as food by consumers is critical to designing new foods that people will buy, enjoy and make a part of their diets.
The final topical session was on Machine Learning and AI Tools. This is a topic that has become very prominent in the last year and our speakers did an excellent job of placing the current state. Professor Beverly Woolf of the College of Information and Computer Sciences started with a broad overview of what machine learning is and gave an excellent foundation on its current state and transformational potential. Professor David Jensen talked about his work in two main areas: causal modeling and explainable AI. Causal modeling attempts to use machine learning generated models to give evidence for causal relationships rather than just uncovering correlations. This allows for more useful information to be generated and the possibility of making changes that result in an expected outcome. His work on explainable AI is an approach to the problem that many machine learning algorithms and AI tools are black boxes: even the creators don’t know how the system goes from input to output, even if it works reliably. He is aiming to produce AI systems whose inner workings are more transparent so they can be more useful, predictable and modifiable. This is a gigantic topic and of the three sessions I recommend this the most once the recordings are up.
This year’s Boot Camp was an excellent way to learn about scientific disciplines, both some I wouldn’t have sought out on my own and Machine Learning that is prominent in today’s headlines. Seeing how interdisciplinary and interconnected these fields are brought them into perspective in a way I didn’t expect. But above all it was a delight to get to know so many colleagues, and to meet some faces I’d only seen via Zoom in person for the first time. Looking forward to next year! If you’re interested, keep an eye out later this year regarding announcements for the next New England Science Boot Camp!
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