Ethical ML: Who's Afraid of the Black Box Models? • Prayson Daniel • GOTO 202138:49 358 views 100% Published 3 months ago
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) [...]
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
Read the full abstract here:
Phil Winder • Reinforcement Learning • https://amzn.to/3t1S1VZ
Kelleher & Tierney • Data Science (The MIT Press Essential Knowledge series) • https://amzn.to/3AQmIRg
Lakshmanan, Robinson & Munn • Machine Learning Design Patterns • https://amzn.to/2ZD7t0x
Lakshmanan, Görner & Gillard • Practical Machine Learning for Computer Vision • https://amzn.to/3m9HNjP
Aurélien Géron • Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow • https://amzn.to/2XZaQy8
#DataScience #ML #AI #MachineLearning #ArtificialIntelligence #Programming #BlackBox #BlackBoxModels #EthicalML #EthicalAI #Ethics #MachineEthics
Looking for a unique learning experience?
Attend the next GOTO conference near you! Get your ticket at https://gotopia.tech
Sign up for updates and specials at https://gotopia.tech/newsletter
SUBSCRIBE TO OUR CHANNEL - new videos posted almost daily.