Trusting machines with robust, unbiased and reproducible AI
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Algorithms • November 2020
Trusting machines with robust, unbiased and reproducible AI
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Language
English
Level
Non technical / For everyone
Length
30 minutes
Type
online conference
About
Trusting machines with robust, unbiased and reproducible AI
About
We see more and more stories in the news about machine learning algorithms causing real-world harm. People's lives are affected by the decisions made by machines. Human trust in technology is based on our understanding of how it works and our assessment of its safety and reliability. To trust a decision made by a machine, we need to know that it is reliable and fair, that it can be accounted for, and that it will cause no harm. We need assurance that it cannot be tampered with and that the system is secure. Learn how to achieve AI fairness, robustness, explainability and accountability.
About speaker
About speaker
Margriet Groenendijk
Developer AdvocateIBM
Margriet is a Data & AI Developer Advocate for IBM. She develops and presents talks and workshops about data science and AI. She is active in the local developer communities through attending, presenting and organising meetups. She has a background in climate science where she explored large observational datasets of carbon uptake by forests during her PhD, and global scale weather and climate models as a postdoctoral fellow. 
Details
Language
English
Level
Non technical / For everyone
Length
30 minutes
Type
online conference