Webinar

Lab Talk - AI, machine learning and automation in research

What you'll learn

  • Realistic AI/ML use cases
  • Data analysis and pattern finding
  • Automation and monitoring
  • Risk/benefit assessment methods
  • Data quality and bias mitigation
  • Change management for teams
  • How to pilot and evaluate AI tools

An accessible overview of how AI and ML are used in research, the upside for discovery, and the trade-offs and risks to consider.

  • Where AI is already useful
  • Barriers to full adoption
  • Ethical and practical considerations

You’ll get a balanced view to inform sensible AI adoption in your lab.

Speakers

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