ΑΙhub.org
 

Radical AI podcast: featuring Jaime Snyder


by
01 June 2022



share this:
jaime snyder

Hosted by Dylan Doyle-Burke and Jessie J Smith, Radical AI is a podcast featuring the voices of the future in the field of artificial intelligence ethics. In this episode Jess and Dylan chat to Jaime Snyder about visualizing our lives through data.

Visualizing our lives through data

How do we see ourselves in data? What is self-tracking and how can we design for visualizing the data of our bodies and mental health? How do we make visualized data more accessible?

In this episode, we interview Jaime Snyder about the data visualization of COVID, mental health, and more. Jaime Snyder is an Associate Professor in the Information School at the University of Washington in Seattle.

She leads the Visualization Studies Research Studio and is also an Adjunct Associate Professor in the UW Department of Human-Centered Design and Engineering. Snyder’s research draws on her background as an artist and information science scholar to explore the creation and use of visual representations of information, data, and knowledge in collaborative and coordinated contexts.

Follow Jaime on Twitter @jay_ess.

Full show notes for this episode can be found at Radical AI.

Listen to the episode below:

About Radical AI:

Hosted by Dylan Doyle-Burke, a PhD student at the University of Denver, and Jessie J Smith, a PhD student at the University of Colorado Boulder, Radical AI is a podcast featuring the voices of the future in the field of Artificial Intelligence Ethics.

Radical AI lifts up people, ideas, and stories that represent the cutting edge in AI, philosophy, and machine learning. In a world where platforms far too often feature the status quo and the usual suspects, Radical AI is a breath of fresh air whose mission is “To create an engaging, professional, educational and accessible platform centering marginalized or otherwise radical voices in industry and the academy for dialogue, collaboration, and debate to co-create the field of Artificial Intelligence Ethics.”

Through interviews with rising stars and experts in the field we boldly engage with the topics that are transforming our world like bias, discrimination, identity, accessibility, privacy, and issues of morality.

To find more information regarding the project, including podcast episode transcripts and show notes, please visit Radical AI.




The Radical AI Podcast




            AIhub is supported by:


Related posts :



Stuart J. Russell wins 2025 AAAI Award for Artificial Intelligence for the Benefit of Humanity

  04 Feb 2025
Stuart will give an invited talk about his work at AAAI 2025.

Forthcoming machine learning and AI seminars: February 2025 edition

  03 Feb 2025
A list of free-to-attend AI-related seminars that are scheduled to take place between 3 February and 31 March 2025.

Hanna Barakat’s image collection & the paradoxes of depicting diversity in AI history

  31 Jan 2025
Read about Hanna's artistic process and reflections upon creating new images about AI

A deep learning pipeline for controlling protein interactions

  30 Jan 2025
Scientists have used deep learning to design new proteins that bind to complexes involving other small molecules like hormones or drugs.
monthly digest

AIhub monthly digest: January 2025 – artists’ perspectives on GenAI, biomedical knowledge graphs, and ML for studying greenhouse gas emissions

  29 Jan 2025
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

Public competition for better images of AI – winners announced!

  28 Jan 2025
See the winning images from the Better Images of AI and Cambridge Diversity Fund competition.

Translating fiction: how AI could assist humans in expanding access to global literature and culture

  27 Jan 2025
Dutch publishing house Veen Bosch & Keuning (VBK) has confirmed plans to experiment using AI to translate fiction.

Interview with Yuki Mitsufuji: Improving AI image generation

  23 Jan 2025
Find out about two pieces of research tackling different aspects of image generation.




AIhub is supported by:






©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association