The AI Report Live with Liam Lawson The AI Behind Fortune 500 Risk: Anton Dam, AuditBoard
Dec 11, 2025
Join Anton Dam, a seasoned machine learning and AI engineer now at AuditBoard, as he explores the evolution of AI technology. He shares insights from his time at Bright.com, highlights the importance of big data and embarrassingly parallel computing for building scalable systems, and discusses the shift towards human-centered design. Anton emphasizes how Fortune 500 companies are now embracing AI, transforming audit processes from reactive to proactive, and underscores the need for trust and accountability in AI governance.
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Bright.com's Transparent Match Score
- Anton Dam describes Bright.com as a two-sided recruitment platform that exposed transparent match scores to guide candidates and employers.
- The score helped candidates gauge fit and helped employers prioritize applicant review time.
Embarrassingly Parallel Powered Early Recommendations
- The early big-data era relied on embarrassingly parallel processing like Hadoop and Spark to handle massive web-scale counts and joins.
- That architecture enabled large-scale recommendations long before today's deep learning advances.
From Low-Level Data To Model Foundations
- Anton recalls that data scientists then had to manage low-level infrastructure, curate datasets, and fix constant data-cleaning failures.
- He contrasts that toil with today's higher-level model foundations and community model sharing (e.g., Hugging Face).