Mahima Pushkarna
I am a UX Designer at Google AI, where I design novel tools and frameworks for understanding machine learning models and interpreting decisions made by algorithms.
I tend to wear many hats – UI/UX, visual design, strategy and design research - to create better human-ai partnerships, such as helping doctors diagnose cancer using AI. The products and processes that I have designed, such as the What-If Tool and Facets, have been widely used to advance better practices in machine learning in industry and academia. As a part of Google's People + AI Research Initiative, I study the impact of design on AI, and vice-versa.
I hold an MFA in Information Design & Data Visualization from Northeastern University, (Boston, MA) and previously studied design at Srishti School of Art, Design & Technology (Bangalore, India) and the University of Michigan, Ann Arbor.
I tend to wear many hats – UI/UX, visual design, strategy and design research - to create better human-ai partnerships, such as helping doctors diagnose cancer using AI. The products and processes that I have designed, such as the What-If Tool and Facets, have been widely used to advance better practices in machine learning in industry and academia. As a part of Google's People + AI Research Initiative, I study the impact of design on AI, and vice-versa.
I hold an MFA in Information Design & Data Visualization from Northeastern University, (Boston, MA) and previously studied design at Srishti School of Art, Design & Technology (Bangalore, India) and the University of Michigan, Ann Arbor.
Authored Publications
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Google
Believing Anthropomorphism: Examining the Role of Anthropomorphic Cues on User Trust in Large Language Models
Michelle Cohn
Femi Olanubi
Zion Mengesha
Daniel Padgett
CM (Association of Computing Machinery) CHI conference on Human Factors in Computing Systems 2024 (2024)
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
Minsuk Kahng
Michael Xieyang Liu
Krystal Kallarackal
Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA '24), ACM (2024)
LaMPost: Evaluation of an AI-assisted Writing Email Editor Prototype for Adults with Dyslexia
Steven Goodman
Erin Buehler
Patrick Clary
Andy Coenen
Aaron Michael Donsbach
Tiffanie Horne
Bob MacDonald
Rain Breaw Michaels
Ajit Narayanan
Joel Christopher Riley
Alex Santana
Rachel Sweeney
Phil Weaver
Ann Yuan
Proceedings of ASSETS 2022, ACM (2022) (to appear)
Healthsheet: development of a transparency artifact for health datasets
Diana Mincu
Lauren Wilcox
Jessica Schrouff
Razvan Adrian Amironesei
Nyalleng Moorosi
ACM FAccT Conference 2022, ACM (2022)
Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI
Association for Computing MachineryNew YorkNYUnited States (2022)
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models
Andy Coenen
Sebastian Gehrmann
Ellen Jiang
Carey Radebaugh
Ann Yuan
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, Association for Computational Linguistics (to appear)
