Session
Organizer 1: Civil Society, Eastern European Group
Organizer 2: Civil Society, Western European and Others Group (WEOG)
Organizer 3: Civil Society, Eastern European Group
Organizer 2: Civil Society, Western European and Others Group (WEOG)
Organizer 3: Civil Society, Eastern European Group
Speaker 1: Jovan Kurbalija, Civil Society, Western European and Others Group (WEOG)
Speaker 2: Sorina Teleanu, Civil Society, Eastern European Group
Speaker 3: Andrijana Gavrilovic, Civil Society, Eastern European Group
Speaker 2: Sorina Teleanu, Civil Society, Eastern European Group
Speaker 3: Andrijana Gavrilovic, Civil Society, Eastern European Group
Format
Roundtable
Duration (minutes): 60
Format description: Given that the nature of an open-ended conversation relies on maximising the degree of audience engagement, we propose a session format that brings the participants and the moderators on the same level and encourages anyone to speak up. A less squarely structured setup of the room reduces the barriers and formality among participants; a more face-to-face environment is also conducive to multi-directional participation as everyone can be viewed. The length of the session is medium, allowing just enough time for participants to warm up and not too long for the conversation to lose its focus.
Duration (minutes): 60
Format description: Given that the nature of an open-ended conversation relies on maximising the degree of audience engagement, we propose a session format that brings the participants and the moderators on the same level and encourages anyone to speak up. A less squarely structured setup of the room reduces the barriers and formality among participants; a more face-to-face environment is also conducive to multi-directional participation as everyone can be viewed. The length of the session is medium, allowing just enough time for participants to warm up and not too long for the conversation to lose its focus.
Policy Question(s)
What governance models can ensure fair compensation and attribution when AI systems leverage individual and community knowledge?
How to protect community and individual knowledge from exploitation in AI training while fostering local innovation?
What mechanisms can be put in place to empower local communities, SMEs, research institutions in shaping bottom-up AI? How to create enabling environments to support the development of bottom-up AI that leverages localised knowledge, particularly in developing / least developed countries?
How can digital governance frameworks better incorporate the distinction between data, information, and knowledge to ensure that AI development respects and amplifies human and communal insights?
What will participants gain from attending this session? Participants will gain:
Insights into the distinction between data, information, and knowledge, and how this distinction impacts AI development and governance.
Insights into how localised knowledge can be leveraged for sustainable innovation while addressing ethical and governance challenges.
Exposure to diverse perspectives on protecting community knowledge from exploitation, fostering inclusive AI ecosystems, and empowering local actors to drive AI innovation.
Exposure to practical approaches to fostering bottom-up AI development while ensuring knowledge protection and fair attribution.
Exposure to an experimental cognitive proximity approach for institutional AI adoption (developed by the organisation behind this proposal).
Description:
Recent developments in the field of AI are opening the door to a paradigm shift. No longer solely driven by computational scale and processing power, AI’s next frontier lies in leveraging human knowledge: contextual, localised, and domain-specific insights. This session will explore the potential of bottom-up AI, where localised knowledge – cultural insights, industry-specific expertise, and community-driven innovation – becomes the cornerstone of AI development. As the AI landscape shifts from reliance on computational power to the strategic use of human knowledge, this session will examine how communities, SMEs, universities, and other groups can harness their unique knowledge to drive AI innovation while ensuring ethical and sustainable use. Fitting under the theme "Sustainable and Responsible Innovation," the session will look at how bottom-up AI, grounded in community-driven knowledge and expertise, can offer more inclusive, effective, and locally attuned solutions. It will address critical issues surrounding the use and protection of knowledge in AI development. It will also explore the distinction between data, information, and knowledge, reflecting on how digital governance debates have increasingly focused on data and its protection while overlooking the human and communal aspects of knowledge creation. (This shift is visible if we compare the emphasis on knowledge in WSIS outcomes and the emphasis on data in the Global Digital Compact.) By revisiting the concept of knowledge as a dynamic, contextual, and collective resource, the session will address how to protect and leverage it responsibly in AI development. Through an interactive format led by two moderators, the session will foster dialogue on how to empower localised AI initiatives while safeguarding the knowledge that fuels them. By highlighting examples such as European startups leveraging medical data or African fintech firms using regional transaction patterns, the session will showcase the potential of bottom-up AI to drive inclusive and sustainable innovation.
Recent developments in the field of AI are opening the door to a paradigm shift. No longer solely driven by computational scale and processing power, AI’s next frontier lies in leveraging human knowledge: contextual, localised, and domain-specific insights. This session will explore the potential of bottom-up AI, where localised knowledge – cultural insights, industry-specific expertise, and community-driven innovation – becomes the cornerstone of AI development. As the AI landscape shifts from reliance on computational power to the strategic use of human knowledge, this session will examine how communities, SMEs, universities, and other groups can harness their unique knowledge to drive AI innovation while ensuring ethical and sustainable use. Fitting under the theme "Sustainable and Responsible Innovation," the session will look at how bottom-up AI, grounded in community-driven knowledge and expertise, can offer more inclusive, effective, and locally attuned solutions. It will address critical issues surrounding the use and protection of knowledge in AI development. It will also explore the distinction between data, information, and knowledge, reflecting on how digital governance debates have increasingly focused on data and its protection while overlooking the human and communal aspects of knowledge creation. (This shift is visible if we compare the emphasis on knowledge in WSIS outcomes and the emphasis on data in the Global Digital Compact.) By revisiting the concept of knowledge as a dynamic, contextual, and collective resource, the session will address how to protect and leverage it responsibly in AI development. Through an interactive format led by two moderators, the session will foster dialogue on how to empower localised AI initiatives while safeguarding the knowledge that fuels them. By highlighting examples such as European startups leveraging medical data or African fintech firms using regional transaction patterns, the session will showcase the potential of bottom-up AI to drive inclusive and sustainable innovation.
Expected Outcomes
Examples of approaches for safeguarding community knowledge while enabling localised AI innovation.
A set of guiding principles for leveraging and protecting knowledge in bottom-up AI initiatives.
Suggestions for policy actions to foster inclusive, bottom-up AI ecosystems that respect cultural and contextual knowledge.
A knowledge-sharing network among participants to continue discussions beyond the IGF.
Hybrid Format: First and foremost, we invite IGF participants to join us for a somewhat different type of session, which is an open-ended conversation dependent on audience inputs. All participants will have a chance to speak, onsite and online; we will have two speakers/moderators onsite to guide the discussions. There will be no panellists with lecture-like presentations.
The session will rely on experienced moderators who will – throughout the entire session – pay equal attention to onsite and online participants, ensuring that interventions from both audiences are treated equally. Online participants will be constantly encouraged to contribute their views, both by voice and by text chat. An additional experienced online moderator will engage with participants in the chat and ensure that the discussions happening there are integrated into the overall session.
Moreover, we will use live discussion tools (e.g., Slido, Mentimeter, and Pigeonhole) to facilitate real-time exchanges between onsite and online participants.