This session brings together engaged thinkers experienced in the ethics and practices of sharing, copyright, and new technologies. Panelists will discuss AI and its implications for openly-licensed content. Topics to be covered include the use of AI to improve facial recognition software, text and data mining techniques, and the expectations held by some CC licensors about how their openly-licensed works ought not be used without their permission even when the licenses otherwise allow. For example, the use of CC-licensed works by companies seeking to improve machine learning implicates ethics, algorithmic transparency and bias and how to ensure that learning happens using an open and inclusive dataset. But not all licensors want their shared works to be used in such settings.
What solutions might the open community pursue outside of CC licenses that align creator expectations with those who are reusing their works? What tools might open platforms deploy to do the same, such as through establishing principles, best practices, or additional terms? This session is will explore analogous systems where change can be made and more.
Session notes:https://docs.google.com/document/d/1Gbfr79WHnUgDJb-aedHxqSbf8c-ERczV4Gom-ghkHKk/edit
