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Using AI to Impact Performance Feedback Equity with Tacita Morway

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Manage episode 443179555 series 3604986
Inhalt bereitgestellt von DataStax and Charna Parkey. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von DataStax and Charna Parkey oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Dive into the world of purposeful AI with Tacita Morway, CTO of Textio. Learn how Textio ensures their AI is built responsibly and ethically to transform the way teams communicate, hire, and measure their health. Discover their rigorous testing processes and the importance of having a diverse team to catch potential risks and how that helps the company develop strategies for avoiding bias and maintaining data privacy.

Episode timestamps

(02:15): Tacita's unconventional career path to becoming a CTO

(07:00): Textio's practices for building AI responsibly and ethically

(14:00) The impact of Textio's AI on performance feedback

(17:00) The importance of purpose-built vs generic AI models

(28:00) Balancing open source and proprietary data/models

(42:00) Advice for the AI industry moving forward

Quotes

Tacita Morway

“When you've got a team with different backgrounds, educational, lived experiences, identity, careers, all of those things, we have those different perspectives in the room. And we're all working off of the same expectations. We can catch each other's gaps.”

Charna Parkey

“There's an interesting conversation happening, I think, in the community right now about these purpose-built LLMs. Are they as good as generic LLMs? Sure, certainly if you're not going to apply something purpose-built to something generic or outside of its domain, it is not as good. But I think some of this shows us that unless you have something purpose-built and unless you're leveraging the data in the right way, you may just be feeding noise back into the system.”

Links

Connect with Tacita
Connect with Charna

  continue reading

103 Episoden

Artwork
iconTeilen
 
Manage episode 443179555 series 3604986
Inhalt bereitgestellt von DataStax and Charna Parkey. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von DataStax and Charna Parkey oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Dive into the world of purposeful AI with Tacita Morway, CTO of Textio. Learn how Textio ensures their AI is built responsibly and ethically to transform the way teams communicate, hire, and measure their health. Discover their rigorous testing processes and the importance of having a diverse team to catch potential risks and how that helps the company develop strategies for avoiding bias and maintaining data privacy.

Episode timestamps

(02:15): Tacita's unconventional career path to becoming a CTO

(07:00): Textio's practices for building AI responsibly and ethically

(14:00) The impact of Textio's AI on performance feedback

(17:00) The importance of purpose-built vs generic AI models

(28:00) Balancing open source and proprietary data/models

(42:00) Advice for the AI industry moving forward

Quotes

Tacita Morway

“When you've got a team with different backgrounds, educational, lived experiences, identity, careers, all of those things, we have those different perspectives in the room. And we're all working off of the same expectations. We can catch each other's gaps.”

Charna Parkey

“There's an interesting conversation happening, I think, in the community right now about these purpose-built LLMs. Are they as good as generic LLMs? Sure, certainly if you're not going to apply something purpose-built to something generic or outside of its domain, it is not as good. But I think some of this shows us that unless you have something purpose-built and unless you're leveraging the data in the right way, you may just be feeding noise back into the system.”

Links

Connect with Tacita
Connect with Charna

  continue reading

103 Episoden

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