Microsoft Announces New Tools for Responsible AI

Microsoft | March 01, 2021

Microsoft Corporation has announced new capabilities in its responsible AI (RAI) toolkits to help data scientists reduce bias within their ML models. Last May at Microsoft Build, it launched 3 tools for the toolkit: InterpretML, Fairlearn, and SmartNoise.

SmartNoise is a collaborative effort by Microsoft and Harvard and is used to prevent personal data while allowing researchers to collect insights from that data using differential privacy. It now offers the ability to use synthetic data, which is a sample that is derived from the original dataset.

By combining the synthetic dataset with the original dataset, researchers can continue to analyse the same dataset without increasing privacy risk. The synthetic data capability will increase collaboration between research parties, democratized knowledge, and open dataset initiatives, the company explained.

Microsoft has also launched a new tool called Error Analysis. This tool enables data scientists to recognize the patterns in their errors, identify subgroups with higher inaccuracy, and visually analyse root causes of the errors.

According to Microsoft, Error Analysis can be used to dive deeper into questions such as:

Does the loan approval model perform similarly for population cohorts across ethnicity, gender, age, education? and

Will the self-driving car recognition model still perform well even when it is dark and snowing outside?

Error Analysis had already been in use within Microsoft. It started as a research project in 2018 as part of an alliance between the AI, Ethics, and Effects in Engineering and Research (AETHER) Committee and Microsoft Research.

Going forward, Microsoft plans to add Error Analysis and other RAI tools to a larger model assessment dashboard that is expected to be available in mid-2021 in OSS and Azure Machine Learning.

Sarah Bird, principal program manager at Microsoft; Mehrnoosh Sameki, senior program manager, at Microsoft and Besmira Nushi, principal researcher at Microsoft; wrote in a post, “The work doesn’t stop here. We continue to expand the capabilities in FairLearn, InterpretML, Error Analysis, and SmartNoise. We hope you’ll join us on GitHub and contribute directly to helping everyone build AI responsibly,”


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