Trustworthy and Dependable AI Applications

Artificial Intelligence (AI) is now ubiquitous in the technology landscape. In some engineering application domains, such as manufacturing, it is very important that AI techniques produce accurate results. Trustworthy and reliable performance means that AI can be used for high-level decision making and in safety-critical scenarios.

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Challenge: Complexity and Uncertainty

  • Ensuring reliability in AI applications is challenging for two main reasons: The complexity of the techniques and the amount of uncertainty they introduce.
  • Artificial Intelligence techniques are complex due to the sophisticated algorithms they implement, the parameters and architectures they use, and the general difficulty in understanding and interpreting the decisions they make.
  • At the same time, these AI techniques rely on different data sets, stochastic search heuristics, and training and operational contexts, all of which introduce multiple sources of uncertainty.

Need: Principles Applicable to AI

  • The key to overcoming these challenges is to identify a set of principles that can be applied to increase the reliability and trustworthiness of AI techniques.
  • These principles should be generalizable enough to be applied to multiple techniques but should also provide concrete validation that the AI meets the desired criteria.
  • If they can strike this balance, they can be applied broadly to increase reliance of AI applications in business.

Solution: Adapted Techniques

A pragmatic approach to ensuring trustworthiness and reliability in AI applications is to identify applicable principles from other domains and adapt them to this context. For example, safety standards can be developed specifically for AI. At the same time, work to improve the interpretability and understandability of AI will allow users to follow the decision-making process behind the techniques, thereby increasing confidence in the results produced.

Our other core competencies

In addition to Trustworthy and Dependable AI Applications, we also focus on the following topics:

Adaptive and Optimized Behavior

Flexible & Reliable Software Service Platform


Automation Systems

In manufacturing, automation is crucial to ensure the quality and efficiency of production processes. Visit Automation Systems to learn more about our focus areas and the various projects Fraunhofer IKS is working on.

Human-Machine Safety Assurance

System Evaluation and Engineering

Blog articles on Trustworthy and Dependable AI Applications

Read more about Trustworthy and Dependable AI Applications on our Safe Intelligence Blog:


Driverless rail vehicles / 10.6.2024

Safe and driverless public transport

In many major cities, the regular operation of self-driving trains is already part of everyday life. But how does autonomous driving in rail transport work?


Railway transportation / 9.11.2022

Thank you for traveling with AI

Using artificial intelligence (AI) in the rail industry could potentially increase both efficiency and quality. At a workshop hosted by Fraunhofer IKS, experts from Deutsche Bahn, Siemens Mobility and the institute itself gathered to discuss the possible uses and challenges associated with AI in rail applications, as well as strategies for ensuring system safety.