Research groups are embedding AI into research process and results. Examples include (a) creating new AI models as a research result, using existing or new models and datasets (b) embedding existing AI models or systems into a new result (c) scraping or otherwise obtaining data (licensing, online publication, etc.) for (re) training AI models in research labs (d) creating solutions (platforms, APIs, libraries) that leverage third party AI services such as OpenAI into research results (e) using AI to create code, images, text, data and other results (in part, hopefully, with human supervision afterwards).
In the KT process, this usage can give rise to significant legal issues that need to be understood and managed by the KTO: regulatory compliance (data and AI), ownership and IP protection of results, licensing in conditions, exploitation models.
This masterclass reviews the different scenarios and presents state of the art and best practices in terms of protection and management of results, regulatory compliance and outbound licensing when AI is involved.
The software course has provided invaluable information as our TTO expands to take on software cases.
Tom Withnell
University of Vienna, Austria
ASTP has excellent courses to immerse yourself into the world of tech transfer.
Qing Cai
Vrije Universiteit Brussel, Belgium
Thank you for such enjoyable inspiring event, great choice of the lecturers!!!
Linda Ondrackova
University of Pardubice, Czech Republic
Organisation and speakers were great, so enthusiastic about their work and very good at transferring their knowledge.
Sarka Bartova
Research Centre Rez, Czech Republic
It was great to experience the uncomplicated and fruitful exchange with colleagues from all over Europe, as well as the positive professional spirit of this conference.
Franck Döbrich
Universitat des Saarlandes WuT GmbH, Germany
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