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Can AI and Automation Reinvent Testing?

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Manage episode 498385922 series 2818468
Content provided by AASHTO resource. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by AASHTO resource 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://podcastplayer.com/legal.

The digital revolution has reached the world of construction materials testing, and it's happening faster than many of us realize. In this eye-opening conversation with Mike Copeland, Quality Program Manager at the Idaho Department of Transportation, we explore the remarkable ways artificial intelligence is transforming how state DOTs handle testing data, quality assurance, and technical decision-making.
Mike shares his journey from struggling with data trapped in PDFs to developing sophisticated AI tools that now save his agency countless hours of manual work. We witness firsthand demonstrations of AI applications that extract testing data in seconds instead of hours, plot complex gyratory compactor data with simple drag-and-drop functionality, and even predict material properties with surprising accuracy. But this isn't just about efficiency—it's about reimagining what's possible.
Perhaps most valuable is our frank discussion about the double-edged nature of these powerful technologies. While AI offers unprecedented capabilities to streamline workflows and enhance decision-making, it also creates new vulnerabilities in our quality assurance systems. Mike explains how traditional approaches to sample custody and verification testing may need fundamental reconsideration as we enter an era where data itself requires security and verification.
Throughout our conversation, practical examples bring these concepts to life: an AI chatbot that instantly answers technical questions about specifications while identifying conflicts between manuals; tools that transform handwritten test sheets into structured data without error-prone manual entry; and exploratory models that challenge our assumptions about which physical tests are truly necessary.
Whether you're already experimenting with AI or just beginning to consider its implications for materials testing, this episode provides both inspiration and caution from someone at the leading edge of this technological transformation. Join us to discover how these tools might reshape your own testing program while maintaining the integrity that ensures public safety in our infrastructure.

Send us a text

Have questions, comments, or want to be a guest on an upcoming episode? Email [email protected].
Related information on this and other episodes can be found at aashtoresource.org.

  continue reading

Chapters

1. Introduction to Mike Copeland (00:00:00)

2. Extracting Data from PDFs Using AI (00:02:12)

3. AI Applications in Quality Assurance (00:06:17)

4. AI Risks and Data Security Concerns (00:10:15)

5. Time-Saving AI Tools for Testing (00:16:15)

6. Chatbots and Document Conflict Detection (00:21:40)

7. AI Demonstration and Future Applications (00:28:07)

8. The Path Forward with AI Technology (00:34:05)

184 episodes

Artwork
iconShare
 
Manage episode 498385922 series 2818468
Content provided by AASHTO resource. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by AASHTO resource 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://podcastplayer.com/legal.

The digital revolution has reached the world of construction materials testing, and it's happening faster than many of us realize. In this eye-opening conversation with Mike Copeland, Quality Program Manager at the Idaho Department of Transportation, we explore the remarkable ways artificial intelligence is transforming how state DOTs handle testing data, quality assurance, and technical decision-making.
Mike shares his journey from struggling with data trapped in PDFs to developing sophisticated AI tools that now save his agency countless hours of manual work. We witness firsthand demonstrations of AI applications that extract testing data in seconds instead of hours, plot complex gyratory compactor data with simple drag-and-drop functionality, and even predict material properties with surprising accuracy. But this isn't just about efficiency—it's about reimagining what's possible.
Perhaps most valuable is our frank discussion about the double-edged nature of these powerful technologies. While AI offers unprecedented capabilities to streamline workflows and enhance decision-making, it also creates new vulnerabilities in our quality assurance systems. Mike explains how traditional approaches to sample custody and verification testing may need fundamental reconsideration as we enter an era where data itself requires security and verification.
Throughout our conversation, practical examples bring these concepts to life: an AI chatbot that instantly answers technical questions about specifications while identifying conflicts between manuals; tools that transform handwritten test sheets into structured data without error-prone manual entry; and exploratory models that challenge our assumptions about which physical tests are truly necessary.
Whether you're already experimenting with AI or just beginning to consider its implications for materials testing, this episode provides both inspiration and caution from someone at the leading edge of this technological transformation. Join us to discover how these tools might reshape your own testing program while maintaining the integrity that ensures public safety in our infrastructure.

Send us a text

Have questions, comments, or want to be a guest on an upcoming episode? Email [email protected].
Related information on this and other episodes can be found at aashtoresource.org.

  continue reading

Chapters

1. Introduction to Mike Copeland (00:00:00)

2. Extracting Data from PDFs Using AI (00:02:12)

3. AI Applications in Quality Assurance (00:06:17)

4. AI Risks and Data Security Concerns (00:10:15)

5. Time-Saving AI Tools for Testing (00:16:15)

6. Chatbots and Document Conflict Detection (00:21:40)

7. AI Demonstration and Future Applications (00:28:07)

8. The Path Forward with AI Technology (00:34:05)

184 episodes

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