In this talk (slides here) by data scientist Suneeta Mall at Kubeflow Con, she talks about why reproducbility needs to gets much stronger in the coming years of AI development. Without understanding, auditing and reproducibility, we got zero chance of fixing the wild proliferation of edge cases that pop up like a bad game of Whack-A-Mole as AI rolls out into the chaos of the real world.
- Using NLP to Bring the 7000 Languages of the World to Light
- Why Explainability is No Panacea
- If You Don’t Have Reproducibility You Don’t Have Anything
- Move Fast and Break Things? The AI Governance Dilemma
- MIT and IBM’s ObjectNet Shows Why Your Image Classifier AI Struggles at Seeing Things in the Real World