Man-machine Dialogues Grounded in Public-sector Meeting Transcripts

Civic Technology Community Group,

Hello. I'd like to share a hyperlink to some exciting AI R&D:

https://research.google/blog/efficient-data-generation-for-source-grounded-information-seeking-dialogs-a-use-case-for-meeting-transcripts/

"Meeting recordings have helped people worldwide catch missed meetings, focus instead of taking notes during calls, and review information. But recordings can also take a lot of time to review. One solution to enable efficient navigation of recordings would be an agent that supports natural language conversations with meeting recordings, so that users can catch up on meetings they have missed. This could manifest as a source-grounded information-seeking dialog task where the agent would allow users to efficiently navigate the given knowledge source and extract information of interest. In this conversational setting, a user would interact with an agent over multiple rounds of queries and responses regarding a source text. The input to the agent model would include the source text, dialog history, and the current user query, and its output should be a response to the query and a set of attributions (text spans from the source document that support the response)."

These technologies will benefit society across sectors – meetings are ubiquitous – and will have civic-technology applications.

In the not-too-distant future, citizens and journalists will be able to ask questions and to engage in dialogues about public-sector meetings, both individual meetings and collections of such meetings.


Best regards,
Adam Sobieski