- MOSS: A System for Detecting Software Similarity
Moss (for a Measure Of Software Similarity) is an automatic system for determining the similarity of programs. To date, the main application of Moss has been in detecting plagiarism in programming classes. Since its development in 1994, Moss has been very effective in this role. The algorithm behind moss is a significant improvement over other cheating detection algorithms (at least, over those known to us).
- How thousands of ‘overworked, underpaid’ humans train Google’s AI to seem smart | Google | The Guardian
–Funny how many times we “discover” this pattern in new spaces.“At first they told [me]: ‘Don’t worry about time – it’s quality versus quantity,’” she said.
But before long, she was pulled up for taking too much time to complete her tasks. “I was trying to get things right and really understand and learn it, [but] was getting hounded by leaders [asking], ‘Why aren’t you getting this done? You’ve been working on this for an hour.’”
Two months later, Jackson-Artis was called into a meeting with one of her supervisors, questioned about her productivity, and was asked to “just get the numbers done” and not worry about what she’s “putting out there”, she said. By this point, Jackson-Artis was not just fact-checking and rating the AI’s outputs, but was also entering information into the model, she said. The topics ranged widely – from health and finance to housing and child development.
- Standards and Recommendations for the Use of Generative AI in Teaching and Learning at Northeastern
This document is designed to support faculty decision-making about the use of artificial
intelligence in teaching and learning in ways that respect instructor autonomy while
operating within the context of university policies. Any use of AI should be made in
alignment with Northeastern’s Policy on the Use of AI Systems (AI Policy)