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תוכן מסופק על ידי Debra J. Farber (Shifting Privacy Left). כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Debra J. Farber (Shifting Privacy Left) או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.
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S2E39: 'Contextual Responsive Intelligence & Data Minimization for AI Training & Testing' with Kevin Killens (AHvos)

43:20
 
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Manage episode 391727563 series 3407760
תוכן מסופק על ידי Debra J. Farber (Shifting Privacy Left). כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Debra J. Farber (Shifting Privacy Left) או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

My guest this week is Kevin Killens, CEO of AHvos, a technology service that provides AI solutions for data-heavy businesses using a proprietary technology called Contextually Responsive Intelligence (CRI), which can act upon a business's private data and produce results without storing that data.
In this episode, we delve into this technology and learn more from Kevin about: his transition from serving in the Navy to founding an AI-focused company; AHvos’ architectural approach in support of data minimization and reduced attack surface; AHvos' CRI technology and its ability to provide accurate answers based on private data sets; and how AHvos’ Data Crucible product helps AI teams to identify and correct inaccurate dataset labels.
Topics Covered:

  • Kevin’s origin story, from serving in the Navy to founding AHvos
  • How Kevin thinks about privacy and the architectural approach he took when building AHvos
  • The challenges of processing personal data, 'security for privacy,' and the applicability of the GDPR when using AHvos
  • Kevin explains the benefits of Contextually Responsive Intelligence (CRI): which abstracts out raw data to protect privacy; finds & creates relevant data in response to a query; and identifies & corrects inaccurate dataset labels
  • How human-created algorithms and oversight influence AI parameters and model bias; and, why transparency is so important
  • How customer data is ingested into models via AHvos
  • Why it is important to remove bias from Testing Data, not only Training Data; and, how AHvos ensures accuracy
  • How AHvos' Data Crucible identifies & corrects inaccurate data set labels
  • Kevin's advice for privacy engineers as they tackle AI challenges in their own organizations
  • The impact of technical debt on companies and the importance of building slowly & correctly rather than racing to market with insecure and biased AI models
  • The importance of baking security and privacy into your minimum viable product (MVP), even for products that are still in 'beta'

Guest Info:

Send us a Text Message.

Privado.ai
Privacy assurance at the speed of product development. Get instant visibility w/ privacy code scans.
Shifting Privacy Left Media
Where privacy engineers gather, share, & learn
Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.
Copyright © 2022 - 2024 Principled LLC. All rights reserved.

  continue reading

פרקים

1. S2E39: 'Contextual Responsive Intelligence & Data Minimization for AI Training & Testing' with Kevin Killens (AHvos) (00:00:00)

2. Introducing Kevin Killens, Founder & CEO at AHvos (00:01:49)

3. Kevin tells us his origin story and how that led him to found AHvos (00:03:19)

4. How Kevin thinks about privacy and the architectural approach he took when building AHvos (00:06:49)

5. Debra & Kevin discuss processing personal data, "Security for Privacy," and the applicability of the GDPR when using AHvos; Kevin tells us about AHvos Contextually Responsive Intelligence (CRI). (00:10:42)

6. Kevin describes several use cases for CRI, including the ability to identify and correct inaccurate dataset labels (00:15:42)

7. Kevin tells us about the leading cause of AI model bias; and why transparency is so important (00:18:35)

8. Kevin delves deeper into how customer data is ingested into models via AHvos and leveraging Trinsic as a backend (00:22:32)

9. Why it is important to remove bias from Testing Data, not only Training Data (00:24:53)

10. Kevin tells us about Data Crucible, AHvos' solution for identifying and correcting inaccurate data set labels (00:29:34)

11. Kevin's advice for privacy engineers as they tackle AI challenges in their own organizations (00:32:33)

12. Debra & Kevin discuss the impact of technical debt and the importance of building slowly and correctly rather than race to market with insecure and biased AI (00:35:29)

13. How to reach out to Kevin and learn more about AHvos (00:41:40)

63 פרקים

Artwork
iconשתפו
 
Manage episode 391727563 series 3407760
תוכן מסופק על ידי Debra J. Farber (Shifting Privacy Left). כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Debra J. Farber (Shifting Privacy Left) או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

My guest this week is Kevin Killens, CEO of AHvos, a technology service that provides AI solutions for data-heavy businesses using a proprietary technology called Contextually Responsive Intelligence (CRI), which can act upon a business's private data and produce results without storing that data.
In this episode, we delve into this technology and learn more from Kevin about: his transition from serving in the Navy to founding an AI-focused company; AHvos’ architectural approach in support of data minimization and reduced attack surface; AHvos' CRI technology and its ability to provide accurate answers based on private data sets; and how AHvos’ Data Crucible product helps AI teams to identify and correct inaccurate dataset labels.
Topics Covered:

  • Kevin’s origin story, from serving in the Navy to founding AHvos
  • How Kevin thinks about privacy and the architectural approach he took when building AHvos
  • The challenges of processing personal data, 'security for privacy,' and the applicability of the GDPR when using AHvos
  • Kevin explains the benefits of Contextually Responsive Intelligence (CRI): which abstracts out raw data to protect privacy; finds & creates relevant data in response to a query; and identifies & corrects inaccurate dataset labels
  • How human-created algorithms and oversight influence AI parameters and model bias; and, why transparency is so important
  • How customer data is ingested into models via AHvos
  • Why it is important to remove bias from Testing Data, not only Training Data; and, how AHvos ensures accuracy
  • How AHvos' Data Crucible identifies & corrects inaccurate data set labels
  • Kevin's advice for privacy engineers as they tackle AI challenges in their own organizations
  • The impact of technical debt on companies and the importance of building slowly & correctly rather than racing to market with insecure and biased AI models
  • The importance of baking security and privacy into your minimum viable product (MVP), even for products that are still in 'beta'

Guest Info:

Send us a Text Message.

Privado.ai
Privacy assurance at the speed of product development. Get instant visibility w/ privacy code scans.
Shifting Privacy Left Media
Where privacy engineers gather, share, & learn
Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.
Copyright © 2022 - 2024 Principled LLC. All rights reserved.

  continue reading

פרקים

1. S2E39: 'Contextual Responsive Intelligence & Data Minimization for AI Training & Testing' with Kevin Killens (AHvos) (00:00:00)

2. Introducing Kevin Killens, Founder & CEO at AHvos (00:01:49)

3. Kevin tells us his origin story and how that led him to found AHvos (00:03:19)

4. How Kevin thinks about privacy and the architectural approach he took when building AHvos (00:06:49)

5. Debra & Kevin discuss processing personal data, "Security for Privacy," and the applicability of the GDPR when using AHvos; Kevin tells us about AHvos Contextually Responsive Intelligence (CRI). (00:10:42)

6. Kevin describes several use cases for CRI, including the ability to identify and correct inaccurate dataset labels (00:15:42)

7. Kevin tells us about the leading cause of AI model bias; and why transparency is so important (00:18:35)

8. Kevin delves deeper into how customer data is ingested into models via AHvos and leveraging Trinsic as a backend (00:22:32)

9. Why it is important to remove bias from Testing Data, not only Training Data (00:24:53)

10. Kevin tells us about Data Crucible, AHvos' solution for identifying and correcting inaccurate data set labels (00:29:34)

11. Kevin's advice for privacy engineers as they tackle AI challenges in their own organizations (00:32:33)

12. Debra & Kevin discuss the impact of technical debt and the importance of building slowly and correctly rather than race to market with insecure and biased AI (00:35:29)

13. How to reach out to Kevin and learn more about AHvos (00:41:40)

63 פרקים

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