12:30–2:30 pm
DSI 105 5460 S University
Jeffrey Heer
Jerre D. Noe Endowed Professor of Computer Science & Engineering
University of Washington
Title: Augmenting Data Scientists: The Promise and Peril of AI-Assisted Analysis
Abstract: Data analysis is a rich sensemaking process, with frequent shifts among data representations, tools, and both conceptual & mathematical models. Computational methods can go beyond fitting models and rendering charts to make in-context recommendations and even guide end-to-end analysis workflows. How does the design of such tools affect people’s exploration, modeling, and understanding of data? In this talk, we will consider methods for augmenting data science work by integrating proactive computational support into interactive tools, with the goal of providing algorithmic assistance to augment and enrich, rather than replace, people’s intellectual work. Across tasks such as data transformation, visualization, and statistical modeling, we apply artificial intelligence to bridge gaps between user intent and robust analysis results. At the same time, we need to pay careful attention to ways these methods may exacerbate bias, foster dependence, and pose challenges for the future of data analysis.
Bio: Jeffrey Heer is the Jerre D. Noe Endowed Professor of Computer Science & Engineering at the University of Washington, where he co-directs the Interactive Data Lab and conducts research on data visualization, data science, and human-computer interaction. The visualization tools developed by Jeff and his collaborators – including Vega(-Lite), D3.js, and Mosaic – are used by researchers, companies, and data enthusiasts around the world.
Jeff’s research papers have received awards at the premier venues in Human-Computer Interaction and Visualization (ACM CHI, UIST, CSCW, IUI, IEEE Vis, VAST, EuroVis). Honors include MIT Technology Review’s TR35 (2009), a Sloan Fellowship (2012), the ACM Grace Murray Hopper Award (2016), the IEEE Visualization Technical Achievement Award (2017), and induction into the IEEE Visualization (2019) and ACM CHI (2021) academies.
Jeff holds B.S., M.S., and Ph.D. degrees in Computer Science from UC Berkeley, whom he then “betrayed” to join the Stanford CS faculty (2009–2013). He also co-founded Trifacta, a provider of interactive tools for scalable data transformation acquired by Alteryx in 2022.