toolings
BIAS ETHICS & TRUST FAIRNESS

AI Fairness 360

Linux Foundation

TOOLKIT

AI Fairness 360, an LF AI incubation project, is an extensible open source toolkit that can help users examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle. It is designed to translate algorithmic research from the lab into the actual practice of domains as wide-ranging as finance, human capital management, healthcare, and education. The toolkit is available in both Python and R.

toolings
ETHICS & TRUST Uncategorised

Datasheets for Datasets

Microsoft

DATASET

The machine learning community has no standardized way to document how and why a dataset was created, what information it contains, what tasks it should and should not be used for, and whether it might raise any ethical or legal concerns. To address this gap, we propose the concept of datasheets for datasets...

toolings
ETHICS & TRUST EXPLAINABILITY

AI Explainability 360

Linux Foundation

TOOLKIT

The AI Explainability 360 toolkit, an LF AI Foundation incubation project, is an open-source library that supports interpretability and explainability of datasets and machine learning models. The AI Explainability 360 Python package includes a comprehensive set of algorithms that cover different dimensions of explanations along with proxy explainability metrics.There is no single approach to explainability that works best. The toolkit is designed to translate algorithmic research from the lab into the actual practice of domains as wide-ranging as finance, human capital management, healthcare, and education...

toolings
ETHICS & TRUST FAIRNESS

Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning

RESEARCH

In this work, we leverage the rich literature on organizational justice and focus on another dimension of fair decision making: procedural fairness, i.e., the fairness of the decision making process. We propose measures for procedural fairness that consider the input features used in the decision process, and evaluate the moral judgments of humans regarding the use of these features. We operationalize these measures on two real world datasets using human surveys on the Amazon Mechanical Turk (AMT) platform, demonstrating that our measures capture important properties of procedurally fair decision making...

projects
ETHICS & TRUST POLICY & REGULATION

AI Policy Forum

FORUM

The AI Policy Forum will be a yearlong process that brings together scientists, technologists, policymakers and business leaders, culminating in an event gathering high-level decision makers to provide a focal point for work to move from AI principles to AI practice, and to serve as a springboard to global efforts to design the future of AI.

projects
ETHICS & TRUST HUMAN RIGHTS WORK & ECONOMIC GROWTH

GPAI

POLICY

The Global Partnership on AI (GPAI) is an international initiative created by France and Canada along with Australia, the European Union, Germany, India, Italy, Japan, Mexico, New Zealand, the Republic of Korea, Singapore, Slovenia, the United Kingdom and the United States of America. It is also multiparty and seeks to guide responsible development and use of AI in a spirit of respect for human rights, inclusion, diversity, innovation and economic growth.

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