Research – Data & AI
Toward Interpretable Machine Learning
Many of today’s decision-making processes are increasingly being made by computer-based systems: from whether a company receives a loan, to whether an individual’s parole is granted. However, modern machine learning techniques, including deep learning, focus solely on predictive accuracy and completely disregard the topic of interpretability. This shortcoming has significantly curtailed the adoption of state-of-art machine learning techniques in many industries, including healthcare, finance, insurance and law, in which regulations and business practice require transparent, trustful and auditable decision support systems.
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