Rosenverse

This video is only accessible to Gold members. Log in or register for a free Gold Trial Account to watch.

Log in Register

Most conference talks are accessible to Gold members, while community videos are generally available to all logged-in members.

Humanizing AI: Filling the Gaps with Multi-faceted Research
Gold
Thursday, March 11, 2021 • Advancing Research 2021

This video is featured in the AI and UX playlist.

Share the love for this talk
Humanizing AI: Filling the Gaps with Multi-faceted Research
Speakers: Joel Branch
Link:

Summary

Artificial intelligence (AI) has graduated from science fiction to commoditized widget form, readily able to snap into many processes of daily life. Hence, enterprises of all maturity levels are increasingly eager to explore AI’s roles in their innovation, or outright survival strategies. Concurrently, ethical and responsible development and execution of AI-based solutions will increasingly become critical for purposes of safety and fairness. Ensuring that AI proliferates along the right path will require the infusion of multi-faceted research activities along the entire AI lifecycle. We will discuss the challenges and opportunities regarding this topic in this presentation.

Key Insights

  • 70% of enterprise AI projects show little to no business impact, and nearly 90% of data science projects fail to reach production.

  • AI bias, particularly intersectional bias in facial recognition, remains a critical unresolved challenge, exemplified by the Gender Shades project.

  • Black-box AI decision-making hinders stakeholder trust and adoption, due to AI’s probabilistic nature and complexity.

  • AI development teams are overly engineer-centric, lacking inclusion of product researchers and ethicists to address societal and user-centered concerns.

  • ML ops, adapted from DevOps, offers governance and accountability frameworks but currently remains engineer-focused.

  • Expanding ML ops to include human-centered researchers can improve AI explainability, trustworthiness, and fairness.

  • Visualization research is essential to analyze and interpret high-dimensional AI data and uncover hidden biases across intersectional subgroups.

  • AI explainability requires moving beyond feature importance towards causal reasoning and natural language explanations accessible to non-technical stakeholders.

  • AI trust is evolving and hinges on AI’s ability to provide convincing, interpretable answers that humans can understand and scrutinize in dialogue form.

  • Humanizing AI is not simply building human-like interfaces but creating governance frameworks that democratize responsible AI development.

Notable Quotes

"AI development is often uninformed and hurried, resulting in deployments that don’t operate well in the real world."

"Humanizing AI means creating governance frameworks that involve a broad array of research competencies for democratizing safe and effective AI."

"Almost 90% of data science projects do not make it into production—they die on the vine."

"Black box decision making is a hallmark problem—information goes in, something comes out, but we have no clue why."

"Bias is fueled by over-engineering without enough participation from non-technical roles that could reduce it."

"The Gender Shades project exposed how facial recognition algorithms had up to a 33% error rate disparity between demographic groups."

"ML ops offers governance, accountability, and a clear stakeholder responsibility framework borrowed from DevOps."

"We want to increase trust and engagement among end users by helping non-technical stakeholders participate in model evaluation."

"Explainability metrics like trustworthiness and understandability are hard, open research problems needing AI-HCI collaboration."

"AI trust will grow when AI can provide back-and-forth justifications like a human would in conversation."

Ask the Rosenbot
Kyle Godbey
Non-linear service design for complex adaptive systems
2025 • Rosenfeld Community
Sam Proulx
Understanding Screen Readers on Mobile: How And Why to Learn from Native Users
2023 • Enterprise UX 2023
Gold
Rachel Posman
A Closer Look at Team Ops and Product Ops (Two Sides of the DesignOps Coin)
2020 • DesignOps Community
Peter Merholz
Design at Scale is People!
2021 • Design at Scale 2021
Gold
Sheri Byrne-Haber
Accessibility at Scale
2021 • Design at Scale 2021
Gold
Laura Gatewood
Beyond Buzzwords: Adding Heart to Effective Slack Communication
2024 • DesignOps Summit 2024
Gold
Wendy Johansson
Design at Scale: Behind the Scenes
2021 • Enterprise Community
Dave Hora
Advice for Establishing Research
2022 • Advancing Research Community
Tim Parmee
Changing Our Design Pressure Points
2023 • DesignOps Summit 2023
Gold
Steve Portigal
Looking Back…to Look Ahead
2024 • Advancing Research 2024
Gold
Sean Baker
Weaving Knowledge Management into the Fabric of Our Design Practice
2025 • DesignOps Summit 2025
Gold
Edward Cupps
The Principal Path: Journeying from Management to Individual Contributor
2021 • Design at Scale 2021
Gold
Katie Hansen
Experimental research: techniques for deep, psychology-driven insights
2025 • Advancing Research 2025
Gold
Joshua Graves
We Need To Talk: Managing Ludicrous Requests at Work (Part 3 of 3)
2025 • Rosenfeld Community
Sarah Barrett
AI in Real Life: Using LLMs to Turbocharge Microsoft Learn
2025 • Rosenfeld Community
Craig Villamor
Resilient Enterprise Design
2017 • Enterprise Experience 2017
Gold

More Videos

Andrew Webster

"Design capability scaling behaves like a social movement with a narrow path to success, requiring both skill-building and environmental adaptation."

Andrew Webster

Scaling Design Capability: How Involved Should You Be?

September 30, 2021

Kristen Honey

"Long COVID will teach us so much about invisible illnesses that are common but overlooked."

Kristen Honey

"Let’s Talk About Data and Crisis”: Public Digital Service Delivery = Open Data + Human Centered Design

November 18, 2021

Tala Tayebi

"I would rather have a product manager do crappy research than have no research at all."

Tala Tayebi Kelly Goto Jared Spool

Voice and influence in an age of noise

March 10, 2026

George Zhang

"Sometimes business and user interests seem opposed, but thoughtful research reveals ways to align them, like early trip cancellations."

George Zhang Molly Stevens

UX Research Excellence Framework

March 11, 2021

Silke Bochat

"Design ops is actually all about fragility. We do stability, security, planning, but can we add more experimentation and comfort with ambiguity?"

Silke Bochat

5 Antifragile Strategies for a DesignOps 2.0

September 23, 2024

Roy Opata Olende

"The value of real exposure holds true in UX, it’s replaceable and helps you understand real user problems."

Roy Opata Olende

How Zapier Uses ‘All Hands Research’ to Increase Exposure to Users

August 6, 2020

"A producer is probably in JIRA day-to-day, running tasks, creating tickets and epics, while a program manager tracks board-level timelines."

Panel Discussion: Communicating the Value of DesignOps

November 7, 2018

Mariesa Lenz

"The queen is not a decision-maker, she’s just there to reproduce."

Mariesa Lenz

What Beekeeping Taught me about Product Teams

October 29, 2025

Rusha Sopariwala

"Sharing unbaked pots and showing vulnerability is central to our process—it helps us collaborate through uncertainty."

Rusha Sopariwala

Remote, Together: Craft and Collaboration Across Disciplines, Borders, Time Zones, and a Design Org of 170+

June 9, 2022