Entering the primary labour market represents a major challenge for many people with special needs. (Company) communication can be one of the challenges. The Westfalen-Lippe regional branch of the German Red Cross e.V. and the company SUTSCHE GbR therefore intend to develop an AI solution that will translate company instructions and suchlike into easily understood language. The aim is for this group of otherwise frequently disadvantaged people to be able to gain a foothold in the labour market.
AI to integrate people with special needs into the primary labour market
Why are you a strong team?
Our team combines project management skills with expertise in social work and experience in implementing translation algorithms using artificial intelligence. Consequently, we already have a diversified network and can use our experience gained from an inclusive workplace to speak to the target audience directly while accessing a server for training AI.
Explain your idea in three sentences.
We are seeking to use AI to translate communication in a company context into plain language so that workers who have reading difficulties, speak little German or are intellectually disabled can integrate better and more easily. For people who need support when reading, it is intended to open a door to take on a wider range of tasks. Secondly, it will make it easier for them to be included in the primary labour market.
What makes your idea special?
Based on our experience at our own inclusive workplace, the largest challenge in including employees with disabilities and impairments is communication. This is why we want to help translate everyday language in company communication into plain language. After a pilot stage, the tool developed can also be scaled up for other fields and let the target audience enjoy a new-found independence from the services that are already provided in plain language today.
What are the next steps?
We are now starting on a rule-based prototype which is intended to translate the first few texts from everyday language to plain language. To this end, we have analysed existing rule books and gathered text from company contexts that can serve as the initial input for the database. We are also starting to collect data extensively so that we then have enough material to train the algorithm to translate.
Contact the project team
- Contact person: Dr. Beate Rottkemper
- E-mail: beate.rottkemper[at]drk-westfalen.de
The Policy Lab of the Federal Ministry of Labour and Social Affairs