During the last few years, the RB and LPX Foundation has offered challenges to produce novel ML applications. Our motivation was to encourage the public to engage in ML as a scientific adventure in the spirit of a makerspace. There was interest in the public and what seemed a generally positive sentiment towards data science and machine learning.
The tone changed a bit with the availability of LLMs and generative AI. Many now express distrust of AI and ML because of ethical concerns about how large companies harvested data without concern for the rights of small artists or privacy.
This year, please let us discuss this matter. As a challenge, we would like to request proposals for ethical and practical AI. How can ML training be done in a way respectful to public interest, and how can ML practitioners provide assurance to the public that training was done in that respectful manner? What promises should ethical practitioners make to the public, and what can ordinary members of the public do to hold practitioners accountable?