AI Quality webinar

Understand Your Role & Responsibilities in Managing AI Quality

On-demand Webinar

On-demand Webinar

INTRODUCTION TO IMPORTANCE OF AI QUALITY & WAYS TO SUCCESSFULLY MANAGE AND SCALE AI

Artificial Intelligence (AI) is one of the most influential technologies that will disrupt organisations and redefine competition. While significant breakthroughs are making headlines, some organisations struggle to realise the potential of AI and scale AI projects successfully. Organisations are challenged by legal and technological uncertainties and a general lack of trust in AI. 

AI governance is currently the most effective mitigation to manage AI risks. Organisations must augment their processes to measure, assess and reliably quantify quality metrics, such as robustness, accuracy, and predictability for AI.

Whether you are a provider or user of AI, you are responsible for meeting AI’s complex quality requirements. Our webinar will introduce you to key concepts of AI quality and framework that will guide you on your path to successful adoption and scaling of AI.

To view the webinar and the list of questions & answers, fill up the form now.


Our webinar will tackle these points, focusing on:

  • Importance of AI and risk of business disruption due to regulations
  • Sources of AI risks and challenges for quality assurance
  • Roles and responsibilities for providers and users of AI technology and data
  • Overview of AI regulation and standardisation landscape
  • Overview of an AI Quality framework to manage AI quality
  • Q & A session 

About the speaker

Martin Saerbeck

 

Dr. Martin Saerbeck

CTO, Digital Service, TÜV SÜD 

In his role as CTO of Digital Service at TÜV SÜD, Martin leads strategic research and development initiatives of novel digital testing solutions in the domains of AI, Robotics, and IoT technology.

 

 

 

 


TÜV SÜD provides trainings on the topic of AI Quality. Attendees will understand the six major quality pillars of AI (Safety, Security, Ethics, Legal, Performance, Sustainability), their characteristics, dedicated risks assessments and strategies to address them throughout the AI system’s life cycle. The goal is to provide actionable insights that are tailored to an organisations’ specific context.

Learn more about our AI Quality training course here.

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