What does it mean for a trained neural network to be Free Software? What needs to be shared to allow users to exercise their freedom to adapt and improve it? Do our current licences fit the task? More and more software-mediated tasks are being accomplished using trained neural networks, in part because the hardware that facilitates deep learning has become so much faster and cheaper. How does the FOSS licensing and development model interact with this trend? Challenges include: + A lack of clarity around the extent and character of IP present in a trained neural network + A reproducibility problem around the generation of a trained neural network from its 'source' data and parameters + Reliance on closed hardware drivers to achieve realistic training rates At a time when our personal freedoms rely more and more on decisions made by such systems, are traditional models of software freedom failing to protect us?

1. Machine Learning:
Challenges for FOSS
Rowan Wilson
Research Support, University of Oxford

2. Background
●
New ingredients
●
New dishes
●
New utensils

3. What’s the problem?
●
A question of where you stand…
●
Instrument of unjust power?
●
Data licensing; data/software boundary
●
Infrastucture availability: driven to the cloud
●
Reproducibility and adadpting open development practices

4. What could we do?
●
Decide it’s not our business?
●
Take control of data back
●
Develop open data improvement community models/projects
●
Support efforts around reproducible and explicable AI
●
...expand the AI Ethics boom to include FOSS considerations?
●
Decide if we believe Free=Able

5. Comments?
rowan.wilson@it.ox.ac.uk