Phil Harvey, an Industrial Metaverse Architect at Microsoft and co-author of "Data: A Guide to Humans," discusses the critical role of empathy in data science. He emphasizes that data empathy is a learnable skill that bridges the gap between technical and non-technical teams. Harvey highlights practical techniques to cultivate empathy, the importance of context in communication, and how storytelling can evoke emotions related to climate issues. He also explores the role of data empathy in developing responsible generative AI technologies, reminding us that data is ultimately about people.
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volunteer_activism ADVICE
Practicing Empathy
Practice cognitive empathy like any other skill, through repeated practice.
Engage with media like art and film, asking how it relates to your data work.
volunteer_activism ADVICE
Dashboard Design with Empathy
When creating data products like dashboards, consider the audience's context, terminology, and way of working.
Simplify complex data into actionable insights to improve user experience and acceptance.
insights INSIGHT
Empathy Beyond Checklists
Checklists can be helpful, but true empathy requires genuine listening and understanding user needs.
Focus on understanding stakeholders' paradigms and systems of thinking to create truly effective data products.
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Data: A Guide to Humans emphasizes the importance of data as humanity's most valuable resource, providing insights into every aspect of life. The book explores how integrating data science with human perspectives can lead to transformative outcomes. It highlights the role of empathy in successful data product development, suggesting that cognitive empathy is a learnable skill crucial for achieving better results in AI projects.
When working with data, it’s easy for us to think about it as a mechanistic process, where data comes in and products come out. But as we’ve explored throughout the show, succeeding in data, whether you’re a data leader looking to build a data culture, a data scientist ascending the ranks, or even a policy maker looking to have an impact with data, the human side is crucial.
At the heart of the “human side” is empathy— whether it’s for your stakeholders if you’re a data scientist developing a dashboard for them, empathy for your workforce if you’re a data or learning leader, or empathy for the planet and your citizens if you’re a policy maker.
So how can we all practice better empathy? Specifically, can we all practice better data empathy? Luckily, empathy is a muscle that can be built. It’s not a “you have it, or you don’t” type of skill. So how can individuals and organizations utilize data empathy to improve how they work with data and the success rate of their projects?
Enter Phil Harvey, an Industrial Metaverse Architect in the Industrial Metaverse Core group at Microsoft. He is an expert in Data & AI Technical and Business Strategy & Philosophy. Harvey is also co-author of the bookData: A Guide to Humans, which explores the concept of Data Empathy, and how it can power better use of data through better communication and understanding of stakeholders in the value chain of data.
DataFramed 