Description:

Please join the Segal Design Institute for a talk given by Erin MacDonald, an Assistant Professor of Mechanical Engineering at Stanford University and the Faculty Director of the MS Design Impact Program

Light refreshments will be served.

Quantified Cognitive Empathy in Sustainable Design
 
Quantified Cognitive Empathy is a combination of behavioral science research and data-driven design, with an emphasis on understanding stakeholder decisions. I will give examples of why this approach is crucial to the success of sustainable products and systems, and how it has been implemented in the Interdisciplinary Research in Sustainable (IRIS) Design Lab at Stanford. We create design methods for quantifying the human- (i.e., customer, user, stakeholder) centered element in design, so that their perspectives can be tested statistically and/or integrated with engineering models.

First, I will discuss a design method we created to identify product features perceived as sustainable by customers (FPSCs) using Machine Learning. The method involves collecting online reviews, manually annotating them using crowd-sourced work, and processing the review fragments with a Natural Language machine learning algorithm. We analyze all three pillars of sustainability for positive and negative perceptions of product features. We show that some crucial sustainability concerns like energy and water consumption did not have a significant impact on customer sentiment, while some superficial material choices surface are crucial, thus demonstrating the anticipated gap in sustainability perceptions and the realities of sustainable design, as noted in previous literature.

Second, I will discuss a series of papers that combined one qualitative (Journey Maps), one quantitative (Agent-Based Modeling), and one hybrid (survey with conjoint questions) design method to investigate the installation process for residential solar panels. We introduce combined (linked) journey maps and use them to understand the perspectives of both the homeowner and the panel installer. Few studies have analyzed the installer, who we found significantly influences the homeowner’s decisions. We demonstrate these linked journey maps as a semi-formal analytical tool to categorize, parameterize, and unite insights affecting both stakeholders. These maps provide insight for subsequent surveys and agent-based model creation. From the maps, we found that post-contract stages were filled with pain points. From the agent-based model, we found that there is incentive for panel manufacturers to improve efficiency, but not reliability. I will conclude with a general discussion of how data-driven design can harness user and stakeholder empathy for design insights.
 
Bio for Erin MacDonald

Erin MacDonald is an Assistant Professor of Mechanical Engineering at Stanford University and the Faculty Director of the MS Design Impact Program. She received an M.S. and Ph.D. in Mechanical Engineering from the University of Michigan; and a B.S. with Honors in Materials Science and Engineering from Brown University. She was a Sloan School of Management Postdoctoral Associate and Mechanical Engineering Instructor at MIT from 2008 to 2009 and an Assistant Professor of Mechanical Engineering at Iowa State University from 2009 to 2014. MacDonald spent several years designing hiking products before returning to graduate school, and holds two patents on consumer product designs. She is the 2012 ASME Design Automation Committee Outstanding Young Investigator, a twice-selected participant in the National Academy of Engineering Frontiers of Engineering program, a Big 12 Faculty Fellow, and a former NSF Graduate Fellow. MacDonald’s research integrates concepts from psychology, economics, and marketing into engineering design methods to better represent the user; an effort she terms "quantified cognitive empathy in design engineering." A main goal of her research is to increase the sustainability of products and technologies by improving the representation of the consumer and other stakeholders in the design process.