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How to Fail Interpretability Research
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- 1 Intro
- 2 Premeditation of evils
- 3 Interpretability hype.
- 4 well... we've been here before...
- 5 What this talk is about
- 6 What this talk is NOT about
- 7 We need interpretability to increase user trust.
- 8 We need to understand every single bit of the model.
- 9 Agenda Many opportunities to fail.
- 10 We first must define a universal mathematical definition of interpretability
- 11 The performance and interpretability trade-off is inevitable.
- 12 How I present the explanations doesn't
- 13 Since there is no good way to evaluate interpretability methods, I can only show you qualitative results
- 14 I am a computer scientist! Running human
- 15 The explanation is always true; It is what the model thinks.
- 16 I'm just a researcher who provide technical tools. The real world usage is something I cannot control.