Internal seminar on the Interplay of human and machine learning in scientific discovery games. Presenters: Anna Jia Gander and Marisa Ponti. March 24, 2020, 13:00-15:00, Room: TBA
A short work-in-progress report will be circulated a few days before the seminar.
We investigate how citizen scientists interact and collaborate with algorithms in citizen science applications. It is not uncommon that members of the general public collaborate, directly or indirectly, not only with professional scientists but also with machines. iNaturalist and Wildlife Spotter, to name just two applications in environmental sciences, rely on a complex interplay of human input and machine learning (ML) to reach their goals. This cooperation implies both human learning and machine learning.
As part of our OptimHum project, we started to address the relationship between humans and machines by examining the learning models that machine learning-based applications are brought to bear in citizen science. We are describing a small sample of citizen science applications, to find out the machine learning paradigm, the sequential order of human-machine interaction, the main human cognitive activity and the main machine learning activity involved.
Seminar with Janet Rafner, Center for Hybrid Intelligence, Aarhus University, DK
Janet will talk about the work we are currently doing together in “Hybrid Intelligence in citizen science: developing a model to understand optimal human and algorithmic interactions in citizen science games.” Where: Department of Applied IT, Room Thanos, January 31, 2020, from 10 to 11.
OptimHum Kickoff, October 9th, 2019
Department of Physics and Astronomy
Ny Munkegade 120
DK-8000 Aarhus C