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.
I learned more in the training course for 3 days than I did in the last 3 months at my job. The lectures were informative & interesting.
Hanna Sonnig
Setterwalls Advokatbyrå, Sweden
It is always encouraging to see that other TTOs are encountering the same problems that we do!
Aurore De Boom
Université Libré de Bruxelle, Belgium
Three days of learning and networking in Dublin at ASTP annual conference. What a great event!!
Sandra Aresta
CIBIO - Centro de Investigação em Biodiversidade e Recursos Genéticos, Portugal
A lot of fruitful discussions with experienced peers. Very helpful sessions.
Sara Matt-Leubner
University of Innsbruck, Austria
I had a great experience and met high profile professionals.
Antonio Menegatti
Politecnico di Milano, Italy
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