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.
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 experts, the specific content and the informal setting will improve you as a professional.
Brechtje Vreenegoor
Radboud Universteit, Netherlands
Excellent professional gathering, perfect collection of topics and very up-to-date insight.
Ludovic Urgeghe
University of Mons, Belgium
Excellent organisation, multifarious activities, great atmosphere… I can't say enough about how well it is tailored to the needs of technology transfer professions.
Tamara Čolić Milosavljević
Centre of Technology Transfer - University of Belgrade, Serbia
ASTP corroborates the strong need for profound insights and exchanges on practices, instruments and competencies that cut across functional, organisational, institutional, sectorial and geographic boundaries.
Koenraad Debackere
KU Leuven, Belgium
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