ΑΙhub.org
 

GRACE Podcast: Dr Harriett Jernigan interviews Dr Nakeema Stefflbauer

by
06 September 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 second episode, Harriett interviews Dr Nakeema Stefflbauer. Listen below:

Dr Nakeema Stefflbauer is a tech product leader, operator, founder and venture partner with a focus on scalable impact tech and AI-driven businesses that solve real environmental, social and governance problems. She holds MA and PhD degrees from Harvard University, a BA from Brown University, and an executive MBA from the disruptive Quantic School of Business and Technology.

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




            AIhub is supported by:


Related posts :



DataLike: Interview with Wuraola Oyewusi

Ndane and Isabella talk to Wuraola Oyewusi about challenging and rewarding aspects of research and how her background in pharmacy has helped her data and AI career

European Union AI Act receives final approval

On 21 May, the Council of the EU formally signed off the artificial intelligence Act.
22 May 2024, by

#ICLR2024 invited talk: Priya Donti on why your work matters for climate more than you think

How is AI research related to climate, and how can the AI community better align their work with climate change-related goals?
21 May 2024, by

Congratulations to the #ICRA2024 best paper winners

The winners and finalists in the different categories have been announced.
20 May 2024, by

Trotting robots offer insights into animal gait transitions

A four-legged robot trained with machine learning has learned to avoid falls by spontaneously switching between walking, trotting, and pronking
17 May 2024, by

Machine learning enhances monitoring of threatened marbled murrelet

CNN analysis of data gathered by acoustic recording devices is a promising new tool for monitoring secretive species.
16 May 2024, by




AIhub is supported by:






©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association