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.
Starting or changing any procedure at a TTO/Institution is challenging and I could not think of anything better than learning with the best.
Ricardo Castro
Centre for research in agricultural Genomics, Spain
ASTP has attained a unique position that has turned it into a highly valued player on the global technology transfer scene.
Koenraad Debackere
KU Leuven, Belgium
The course Software Specific Challenges is a must for every TTO/KTO professional, especially for those working with Social Sciences and Humanities!
Brechtje Vreenegoor
Radboud University, Netherlands
Just perfect 3 days full of information and perfect communication.
Petr Kubečka
Palacký University Olomouc, Czech Republic
This was the right decision giving me the broadest overview, confidence, tools, network and support that is fundamental to feel right in my daily decision process and to keep on learning.
Ricardo Castro
Centre for research in agricultural Genomics, Spain
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