Ethical ML: Who's Afraid of the Black Box Models? • Prayson Daniel • GOTO 2021

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This presentation was recorded at GOTO Copenhagen 2021. #GOTOcon #GOTOcph

Prayson Daniel - Principal Data Scientist at NTT DATA

Take a dive into the deep depths and pitfalls of explainable machine learning, going beyond the illusions of interpretability and explainability.
Draw from Prayson's experience and explore how ethical data handling and counter-factual fairness model testing help in keeping black-box models and yet satisfy GDPR and ALTAI (Guidelines for Trustworthy AI) [...]

00:00 Intro
01:26 Dragons & unicorns
03:42 Beyond model transparency & explainability
04:30 Why should you care?
07:16 We (data scientists) have messed things up
14:48 We (data scientists) are fixing it
21:25 Demo
33:55 Conclusions
38:34 Outro

Read the full abstract here:

Phil Winder • Reinforcement Learning •
Kelleher & Tierney • Data Science (The MIT Press Essential Knowledge series) •
Lakshmanan, Robinson & Munn • Machine Learning Design Patterns •
Lakshmanan, Görner & Gillard • Practical Machine Learning for Computer Vision •
Aurélien Géron • Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow •
#DataScience #ML #AI #MachineLearning #ArtificialIntelligence #Programming #BlackBox #BlackBoxModels #EthicalML #EthicalAI #Ethics #MachineEthics

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