Worker-Owned Cooperative Models for Training Artificial Intelligence

Anand Sriraman, Jonathan Bragg, Anand Kulkarni
2017 Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW '17 Companion  
Artificial intelligence (AI) is widely expected to reduce the need for human labor in a variety of sectors. Workers on virtual labor marketplaces accelerate this process by generating training data for AI systems. We propose a new model where workers earn ownership of trained AI systems, allowing them to draw a long-term royalty from a tool that replaces their labor. This concept offers benefits for workers and requesters alike, reducing the upfront costs of model training while increasing
more » ... r-term rewards to workers. We identify design and technical problems associated with this new concept, including finding market opportunities for trained models, financing model training, and compensating workers fairly for training contributions. A survey of workers on Amazon Mechanical Turk about this idea finds that workers are willing to give up 25% of their earnings in exchange for an investment in the future performance of a machine learning system.
doi:10.1145/3022198.3026356 fatcat:46axt7px5vbq7p5yrle2v63sfi