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
Michelle Chin
The DesignOps Starter Kit
2021 • DesignOps Summit 2021
Gold
Mariah Hay
BUILD: Discussion
2018 • Enterprise Experience 2018
Gold
Daniel Korczynski
From generic to contextual research insights with AI | Live Q&A
2026 • Advancing Research 2026
Conference
Aiyana Bodi
Three Key Climate Initiatives and How You Can Help
2024 • Climate UX Interest Group
Mark Boulton
Ops without Designers
2018 • DesignOps Summit 2018
Gold
Jules Monza
Use These Words and Count These Things
2024 • DesignOps Summit 2024
Gold
Sam Proulx
Understanding Screen Readers on Mobile: How And Why to Learn from Native Users
2023 • Advancing Research 2023
Gold
Andrew Custage
The Digital Journey: Research on Consumer Frustration and Loyalty
2023 • Advancing Research 2023
Gold
Marc Majers
Interrupted UX - Add A Dose of Reality To Usability Testing
2022 • Advancing Research 2022
Gold
Joshua Graves
We Need To Talk: Navigating Conversations with Your Boss (Part 1 of 3)
2025 • Rosenfeld Community
Landon Barnes
Are My Research Findings Actually Meaningful?
2022 • Advancing Research 2022
Gold
Jon White
Unsticking Research for Better Information Flow
2026 • Advancing Research 2026
Conference
Sara Asche Anderson
Not Your Ordinary Re-Brand: Design's Path to Driving Customer Obsession at Best Buy
2024 • Enterprise Experience 2020
Gold
Maria Skaaden
Panel Discussion: Methodologies and Work Environments
2018 • DesignOps Summit 2018
Gold
Caroline Vize
The State of UX: Five Lessons from 2021 to Accelerate Digital Experience in 2022
2022 • Advancing Research 2022
Gold
Jacqui Frey
Setting the Table for Dynamic Change
2019 • DesignOps Summit 2019
Gold

More Videos

Phil Hesketh

"We reduced the time to approve consent forms from two weeks to minutes through modular content and legal collaboration."

Phil Hesketh

Designing Accessible Research Workflows

September 29, 2021

Laura Gatewood

"Slack clips can add tone and body language that is too hard to capture in the written word."

Laura Gatewood Laine Prokay

Beyond Buzzwords: Adding Heart to Effective Slack Communication

September 23, 2024

Billy Carlson

"Low fidelity design lets you try things quickly and learn so much before you get too detailed."

Billy Carlson

Principles of Team Wireframing

October 2, 2023

Jodi Forlizzi

"The most successful AI innovations come from moderate AI performance that’s good enough to provide real value."

Jodi Forlizzi

Design and AI innovation

June 5, 2024

Adam Cutler

"A really good designer tells me about the user, the problem, business and tech constraints before jumping to solution."

Adam Cutler Karen Pascoe Ian Swinson Susan Worthman

Discussion

June 8, 2016

Cennydd Bowles

"Design fiction can bring potential futures into the present to stimulate moral imagination and public debate."

Cennydd Bowles

Responsible Design in Reality

June 9, 2021

Louis Rosenfeld

"Books are semantically very rich and thus pull content much more effectively in our vector database than conference talks."

Louis Rosenfeld Peter Van Dijck

GenAI for UXers: A Rosenbot Demo and Discussion

September 11, 2025

Dorelle Rabinowitz

"The key is of course trust, but in my house the magic word is please."

Dorelle Rabinowitz

The Magic Word is Trust

June 15, 2018

Lija Hogan

"Sometimes accommodating 20% of users with special needs improves the experience for the entire 100%."

Lija Hogan

Contexts of Use: A Framework for Connection

December 9, 2021