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Data Protection in AI Adoption with Bob McCowan

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Manage episode 398877178 series 3537590
Content provided by Steve Swan. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Steve Swan or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

A revolution in biotechnology is underway, with artificial intelligence at its core, but the fervor over AI adoption brings with it pressing concerns about data protection that cannot be overlooked.
In this episode, I'm joined by Bob McCowan, Chief Information Officer at Regeneron, to navigate the crossroads of AI development and data security. We dissect the lifeblood of AI efficacy - the quality of input data - and explore how organizations can create a sanctuary for innovation while preventing data breaches.

Bob brings a wealth of experience to the table, revealing how AI serves as a copilot for human ingenuity. We also delve into fostering a culture that accepts failure as a part of innovation and the need for strategic training within enterprises.
This conversation brings to light pivotal strategies for integrating AI securely and effectively. Join us to uncover practical insights and prepare your organization for the future of biotech.
Specifically, this episode highlights the following themes:

  • The critical role of data quality and leadership in AI implementation
  • Building the right environment for AI adoption and the importance of learning from failure
  • Data protection and intellectual property safeguarding in the age of advanced analytics

Links from this episode:

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Chapters

1. Introduction (00:00:00)

2. Leverage AI for productivity gains across organization (00:05:29)

3. Apply AI/ML for imaging analysis (00:09:41)

4. Exploring deep analytics for scientific and business applications (00:10:36)

5. Quantum computing is a potential game-changer (00:16:05)

6. Architected with guardrails, monitoring, prioritize risk prevention (00:18:40)

7. Scientists propose theoretical research, AI is tool (00:20:49)

8. Research and utilize data effectively for progress (00:25:17)

9. Internet content requires healthy skepticism and verification (00:26:59)

10. Embrace failures, create your own learning journey (00:32:26)

21 episodes

Artwork
iconShare
 
Manage episode 398877178 series 3537590
Content provided by Steve Swan. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Steve Swan or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

A revolution in biotechnology is underway, with artificial intelligence at its core, but the fervor over AI adoption brings with it pressing concerns about data protection that cannot be overlooked.
In this episode, I'm joined by Bob McCowan, Chief Information Officer at Regeneron, to navigate the crossroads of AI development and data security. We dissect the lifeblood of AI efficacy - the quality of input data - and explore how organizations can create a sanctuary for innovation while preventing data breaches.

Bob brings a wealth of experience to the table, revealing how AI serves as a copilot for human ingenuity. We also delve into fostering a culture that accepts failure as a part of innovation and the need for strategic training within enterprises.
This conversation brings to light pivotal strategies for integrating AI securely and effectively. Join us to uncover practical insights and prepare your organization for the future of biotech.
Specifically, this episode highlights the following themes:

  • The critical role of data quality and leadership in AI implementation
  • Building the right environment for AI adoption and the importance of learning from failure
  • Data protection and intellectual property safeguarding in the age of advanced analytics

Links from this episode:

  continue reading

Chapters

1. Introduction (00:00:00)

2. Leverage AI for productivity gains across organization (00:05:29)

3. Apply AI/ML for imaging analysis (00:09:41)

4. Exploring deep analytics for scientific and business applications (00:10:36)

5. Quantum computing is a potential game-changer (00:16:05)

6. Architected with guardrails, monitoring, prioritize risk prevention (00:18:40)

7. Scientists propose theoretical research, AI is tool (00:20:49)

8. Research and utilize data effectively for progress (00:25:17)

9. Internet content requires healthy skepticism and verification (00:26:59)

10. Embrace failures, create your own learning journey (00:32:26)

21 episodes

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