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

The Shifting Privacy Left Podcast

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:

• Connect with Kevin on LinkedIn
• Check out AHvos
• Check out Trinsic Technologies

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Chapters

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)