Michael Hind
Distinguished Research Staff Member at IBM Research; co-author of AI Fairness 360, AIX360 and FactSheets
- Distinguished Research Staff Member, IBM Research1
Michael Hind is a Distinguished Research Staff Member in IBM Research's AI department, who has worked on AI governance for much of the past decade and is now also pursuing ideas in generative computing, according to the IBM Research profile. The profile credits Hind and collaborators with transferring FactSheets and AI risk tools into IBM and with launching open-source projects including AI Fairness 360, AI Explainability 360, and AI Risk Atlas Nexus, alongside programming-language projects such as Jikes RVM and WALA. Hind is a co-author of the papers introducing AI Fairness 360, AI Explainability 360, FactSheets, and IBM's Granite Guardian models, and the profile notes the SIGPLAN Software Award in 2012 for work on Jikes RVM.15782
Work
Granite GuardianOpen weights
Listed among the authors of the Granite Guardian technical report (2024), which introduces risk-detection models for LLM prompts and responses released as open source; the repository is under the Apache-2.0 license and the Granite Guardian 3.0 8B model card lists the apache-2.0 license.234
AI Fairness 360 and AI Explainability 360 (external site: github.com)Open-source code
Co-author of the 2018 paper introducing AI Fairness 360, released under the Apache v2.0 license, and of the 2019 paper introducing the open-source AI Explainability 360 toolkit; IBM Research's profile lists both among the open-source projects Hind and collaborators launched.5671
FactSheets and AI Risk Atlas Nexus (external site: github.com)Open-source code
Co-author of the 2018 FactSheets paper on documenting AI services; the IBM Research profile lists AI FactSheets 360 and AI Risk Atlas Nexus among Hind's projects, and the IBM/ai-atlas-nexus repository is under the Apache-2.0 license.819
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