Artificial intelligence is finding its way into more and more business processes—and with it, increasing demands for transparency, fairness, and security.
Representative and precisely labeled test data is crucial for building trust in AI systems and reducing risks. It enables valid measurement of key performance indicators and reliably reveals distortions or performance gaps.
Errors in AI systems
Fact-based assessments are essential, especially in safety-critical areas such as industrial automation, medicine, and mobility. Errors in AI systems in these areas can have dangerous consequences, as recent examples from medical diagnosis show – especially in stressful situations, human supervision alone is not a sufficient solution. The safe development and testing of state-of-the-art AI is necessary to sufficiently minimize AI risks for such critical applications.
Biases and performance gaps
“AI is not a sure-fire success. Anyone who wants to use it must test its performance in a structured and objective manner. Independent, representative test data is the key to safe and trustworthy AI applications
,“
emphasize Andreas Gruber and Thomas Doms, Managing Directors of TRUSTED AI by TÜV AUSTRIA.
With a high level of expertise in machine learning, data science, software engineering, process management, functional safety and security, early threat detection and defense against AI-supported cyberattacks, bundled audit expertise, certified testing procedures, and precise evaluation models, TÜV AUSTRIA creates the decisive advantage for companies to develop and use artificial intelligence safely and responsibly – transforming technological innovation into sustainable competitive advantages. | trustifai.at
Contact information
TRUSTIFAI – TÜV AUSTRIA & SCCH AI Joint Venture
Andreas Gruber, MSc, MSc
Phone: +43 664 604 54 6592
Email: andreas.gruber@tuvaustria.com
Website: trustifai.at
Check certificate
I am looking for a solution but do not know its title.
