Aartificial intelligence, Database, Design, Finance, IT, Machine learning techniques, Management
Finding a quantitative evaluation metric that can be used to estimate the usefulness of ML model explanations. That wil be the goal of your research in this thesis.
Required interest(s)
What do you get
What you will do
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As machine learning (ML) systems take a more prominent and central role in contributing to life-impacting decisions, ensuring their trustworthiness and accountabilityis of utmostimportance. Explanations sit at the core of these desirable attributes of a ML system. The emerging field is frequently called “Explainable AI (XAI)” or “Explainable ML.” The goal of explainable ML is to intuitively ex-plain the predictions of a ML system, while adhering to the needs to various stakeholders. Many explanation techniques were developed with contributions from both academia and industry. However, there are several existing challenges that have not garnered enough interest and serve as roadblocks to widespread adoption of explainable ML.
It is difficult to determine which eXplainable AI technique (XAI) is most useful in a given scenario. A proper quantitative evaluation metric to determine this does not exist at the moment. As a result, it is unknown whether the explanations created for a certain model are sufficient and usable.
The goal of your research is to find a quantitative evaluation metric that can be used to estimate the usefulness of ML model explanations. This should be a stable metric that could even be utilized in an automated MLOps flow, to give the best possible set of explanations for a given ML model. Your results will assist us in implementing XAI solutions at our clients.
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About Info Support Research Center
We anticipate on upcoming and future challenges and ensures our engineers develop cutting-edge solutions based on the latest scientific insights. Our research community proactively tackles emerging technologies. We do this in cooperation with renowned scientists, making sure that research teams are positioned and embedded throughout our organisation and our community, so that their insights are directly applied to our business. We truly believe in sharing knowledge, so we want to do this without any restrictions.
Read more about Info Support Research here.
What does Info Support offer you during your graduation period?
Of course, we offer you an excellent package of graduation conditions with various options. These include:
During your graduation internship, you will be included in one of our business units and in our Research Center. This will give you a good understanding of the developments within our projects and our research projects.
In addition, Info Support offers you:
About Info Support
Info Support specializes in custom software, data/AI solutions, management, and training and is active in the Finance, Industry, Agriculture, Food & Retail, Mobility & Public, and Healthcare sectors. We provide solid and innovative solutions for complex and critical software issues. Our headquarters are located in Veenendaal (NL) and Mechelen (BE). At present, approximately 500 employees are employed by Info Support.
Info Support staat voor professionele, betrouwbare en vernieuwende softwareoplossingen. Dit doen wij met meer dan 500 medewerkers, werkzaam vanuit vestigingen in Nederland (Veenendaal) en België (Mechelen). Onze dienstverlening omvat softwareontwikkeling, inclusief vernieuwing en onderhoud, business intelligence en integratie oplossingen, beheer & hosting en trainingen. Voor specifieke markten als zorgsector, woningcorporaties en gemeenten bie
Veenendaal, Utrecht, Netherlands
0-2 year
Veenendaal, Utrecht, Netherlands
0-2 year
Veenendaal, Utrecht, Netherlands
0-2 year
Veenendaal, Utrecht, Netherlands
0-2 year
Veenendaal, Utrecht, Netherlands
0-2 year
Veenendaal, Utrecht, Netherlands
0-2 year