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People + AI Research

3 Google I/O take-aways: Creating responsible generative AI products

by Mahima Pushkarna, Design Lead, People + AI Guidebook and PAIR, and Sally Limb, Senior UX Designer, Responsible AI UX

May 20

A diagram of five principles with a green and black image above each principle. Principle 1: An image of a game console, “Design for user autonomy”. Principle 2: An outline of 2 people, “Align AI with real-world behaviors”. Principle 3: A shield with a check mark, “Treat safety as an evolving endeavor”. Principle 4: Messaging icons, “Adapt AI with user feedback”. Principle 5: A heart shape, “Create helpful AI that enhances work and play”

May 20

People + AI Research @ Google
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People + AI Research

LLM Comparator: A tool for human-driven LLM evaluation

By Minsuk Kahng, Ryan Mullins, Ludovic Peran

May 14

LLM Comparator’s interface features a table on the left displaying input prompts, model outputs, score distributions, and rationales. A column on the right showcases visualizations like score distributions, metrics, clusters, and custom functions. Users can interact with both the table and visualizations to drill down into specific data points and filter results.

May 14

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People + AI Research

Generative AI is reshaping our mental models of how products work. Product teams must adjust.

By Reena Jana, Mahima Pushkarna, and Soojin Jeong

Apr 26

A smiling human form holding a green sphere in one hand stands next to drawer that has been opened from a wall of drawers. The greens sphere indicates a mental model. A burst of light-color and abstract shapes indicate that the sphere has been taken from the drawer. Two other random drawers are partially open, with green spheres peeking out.

Apr 26

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People + AI Research

Interaction Design Policies: Design for the opportunity, not just the task.

By Mahima Pushkarna, design lead of the People + AI Guidebook.

Jan 20

Interaction Design Policies: Design for the opportunity, not just the task.

Jan 20

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People + AI Research

Updating the People + AI Guidebook in the age of generative AI

By Reena Jana and Mahima Pushkarna

Nov 22, 2023

motion graphic: an illustration featuring green and white abstract shapes

Nov 22, 2023

People + AI Research @ Google
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People + AI Research

Generative AI was a helpful tool for an adventurous art exhibition.

By Emily Reif, with Camille Benech and Lucas Dixon (with special thanks to Shahryar Nashat, Sara Sadik, and Rachel Rose)

Oct 5, 2023

Photo of Reverse Rorschach, an art piece by Shahryar Nashat

Oct 5, 2023

People + AI Research @ Google
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People + AI Research

Generative AI: A Golden Opportunity for UX

by Ayça Çakmakli

Aug 9, 2023

Infographic 1 by Ayça Çakmakli

Aug 9, 2023

People + AI Research @ Google
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People + AI Research

The Generation, Evaluation, and Metrics (GEM) Project: Improving dataset transparency with the Data…

By Mahima Pushkarna and Andrew Zalidvar, with Sebastian Gehrmann

Aug 11, 2023

The Generation, Evaluation, and Metrics (GEM) Project: Improving dataset transparency with the Data…

Aug 11, 2023

People + AI Research @ Google

Build generative AI products responsibly with MakerSuite, using the PAIR Guidebook

With all of the excitement around generative AI, we have been working on new tools, like MakerSuite, to let people prototype with large…

Jun 2, 2023

Build generative AI products responsibly with MakerSuite, using the PAIR Guidebook

Jun 2, 2023

People + AI Research @ Google
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People + AI Research

Exploring how AI models can avoid “confident incorrectness”

Much of the conversation around AI models today is healthy skepticism and centers around raising proactive questions about risks and harms…

May 12, 2023

Animated GIF of a an illustration of input to an AI model that shows letters and numbers, beside a visualization of several AI model’s predictions of whether the image is of a letter or a number, along with the averages of the predictions.

May 12, 2023

People + AI Research @ Google

People + AI Research @ Google

People + AI Research (PAIR) is a multidisciplinary team at Google that explores the human side of AI.

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