ΑΙhub.org
 

GRACE Podcast: Dr Harriett Jernigan interviews Dr Brandeis Marshall


by
04 July 2022



share this:
grace podcast

GRACE: Global Review of AI Community Ethics is a new student-run, peer-reviewed, open-access, international journal. To accompany the journal, there is a podcast hosted by Dr Harriett Jernigan.

In this first episode, Harriett interviews Dr Brandeis Marshall about her research, ranking algorithms, misinformation, combining the analytical and the creative, the lack of Black women in leadership roles in the data industry, the disproportional effect of data on Black women, tech solutionism, her forthcoming book, and more.

Listen to the audio version below:

You can watch the video version here.

Dr Brandeis Marshall is founder and CEO of DataedX Group, a social impact business that provides learning and development activities on recognizing algorithmic harms and humanizing data practices for data educators, scholars and practitioners. She is also Full Professor of Computer Science at Spelman College. She holds a Ph.D. and Master of Science in Computer Science from Rensselaer Polytechnic Institute and a Bachelor of Science in Computer Science from the University of Rochester. Find out more about her forthcoming book here.

Dr Harriett Jernigan is a lecturer at Stanford University. She earned her BA in German and Creative Writing at the University of Alabama and her PhD in German Studies at Stanford University. She specializes in writing across the disciplines; second-language acquisition; project-based instruction; social geography; and German languages, literatures and cultures.




GRACE

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

Reflections from #AIES2025

and   14 May 2026
We reflect on AIES 2025, outlining a discussion session on LLMs for clinical usage and human rights.

Deep learning-powered biochip to detect genetic markers

System can detect extremely small amounts of microRNAs, genetic markers linked to diseases such as heart disease.

Half of AI health answers are wrong even though they sound convincing – new study

  12 May 2026
Imagine you have just been diagnosed with early-stage cancer and, before your next appointment, you type a question into an AI chatbot.

Gradient-based planning for world models at longer horizons

  11 May 2026
What were the problems that motivated this project and what was the approach to address them?

It’s tempting to offload your thinking to AI. Cognitive science shows why that’s a bad idea

  08 May 2026
Increased offloading to new tools has raised the fear that people will become overly reliant on AI.

Making AI systems more transparent and trustworthy: an interview with Ximing Wen

  07 May 2026
Find out more about Ximing's work, experience as a research intern, and what inspired her to study AI.

Report on foundation model impacts released

  06 May 2026
Partnership on AI publish a progress report on post-deployment governance practices.

Forthcoming machine learning and AI seminars: May 2026 edition

  05 May 2026
A list of free-to-attend AI-related seminars that are scheduled to take place between 5 May and 30 June 2026.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence