A Systematic approach to assure AI quality and compliance
A Systematic approach to assure AI quality and compliance
Though 80% of executives believe they risk going out of business in 5 years if they don’t scale AI, most of implemented AI projects currently fail to deliver their promised outcomes. To scale AI and utilise its full potential you must manage the associated risks explicitly.
We at TÜV SÜD have shifted our focus early on the quality of AI and have built comprehensive expertise in this field. Hence, we are now help organisations using or developing AI. We teach them how tomanage the risk of technical failures, organizational shortcomings, violation of regulatory or legal requirements, or reputational damage due to unintended ethical biases.
Our AI guided assessment is based on standards, regulations and industry best practices. It enables organisations to implement a systematic AI quality framework.
Our AI quality experts conduct this guided assessment starting with scoping of the actual AI component, solution or system. Like the AI Quality Readiness Analysis, but in significantly more depth, the assessment covers six key quality pillars that are examined:
Using a risk-based approach, we generate a company-specific quality profile thanks to our outstanding quality framework . The profile is then being assessed to provide a clear understanding of the gaps and areas of improvement.
You are now now in the position to implement systematically a quality framework composed of respective standards and best practices meeting company values and regulations.
At TÜV SÜD, we leverage our testing, inspection and certification expertise combined with deep knowledge of Industry 4.0, AI, IoT and Cybersecurity. We set the basis for organisations to systematically plan and implement AI quality, which is essential for AI developers and users to utilise the full potential of this transformative technology.
The whole organisation is involved on the journey to AI Quality:
Let’s use an analogy. You are a car manufacturer, and you are happy with your car specifications and proud of how fast you accelerate from 0 to 100km/h. Does this mean you would produce this car without compelling quality procedures? Do you know how to maintain it? What happens by freezing temperature? Your CTO is leaving, and you are lost? Your insurance is asking you for proof of compliance? You are facing adversarial attacks...
You understand now what this is all about: AI touches your entire organisation, and needs to be addressed as such.
Sure! AI is not only to be managed in your production or data science department, but as well when embedded into IOT devices. You will want to ensure that your customers and final users are dealing with a trustworthy AI, wouldn't you?
This is one of the major reasons to implement AI quality framework, based on standards and regulations: you will tremendously reduce the risk of liabilities, as they just are very unlikely to occur. And shall they nonetheless occur, your compliance to legal requirements and standards will be a really strong umbrella facing liabilities issues.
Readiness Analysis is giving an overview on how mature you are and what are your greatest weakness and risks. It does not go to the bottom of each and single quality criteria. It is a compass to prioritide the next steps.
Guided Assessment is scanning your AI System to the ground, and gives you a clear and detailed picture for each possible quality criteria. The gaps with Standards and regulations are identified in all their aspects.
Establish trust, stay relevant, and utilise the full potential of AI
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A practical guide to gain the required knowledge to master AI quality
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