Oct 6, 2024 · Trustworthy AI. Our trust in technology relies on understanding how it works. It’s important to understand why AI makes the decisions it does. We’re developing tools to make AI more explainable, fair, robust, private, and transparent.

Aug 14, 2024 · Data is key to technological innovations. We develop theoretical and algorithmic frameworks for generative AI to synthesize realistic, diverse, and targeted data. Our methods facilitate data augmentation for trustworthy machine learning and accelerate novel designs for drug and material discovery, and beyond.

To this end, we offer reformulations of core principles of Trustworthy AI - fairness, accountability, and transparency - that substantively address the deeper issues animating widespread public distrust of AI, including: stewardship and care, openness …

Unlike conventional tutorials that focus on either the positive or the negative impacts made by AI, this tutorial aims to provide a holistic and complementary overview of the trustworthy issues, including security, robustness, privacy, and societal issues of the models so that researchers and developers can have a fresh perspective and some ...

Dr. Varshney is an IBM Fellow based at the Thomas J. Watson Research Center, Yorktown Heights, NY, where he directs Human-Centered Trustworthy AI research. He was a visiting scientist at IBM Research - Africa, Nairobi, Kenya in 2019.

In contrast, the design and sculpting of the data used to develop AI often rely on bespoke manual work, and they critically affect the trustworthiness of the model. This Perspective discusses key considerations for each stage of the data-for-AI pipeline—starting from data design to data sculpting (for example, cleaning, valuation and ...

Apr 10, 2024 · Even advanced AI systems can be vulnerable to adversarial attacks. We’re making tools to protect AI and certify its robustness, including quantifying the vulnerability of neural networks and designing new attacks to make better defenses.

Jun 16, 2023 · The open-source ai-privacy-toolkit is designed to help organizations build more trustworthy AI solutions, with tools that protect privacy and help ensure the compliance of AI models. As AI regulations mature and case-laws around their violations become available, we foresee that many more organizations will implement and embed such tools and ...

Jul 24, 2023 · IBM has long advocated for explainable, trustworthy AI. In 2018, IBM was the first in the industry to launch a free library of bias mitigation algorithms, the AI Fairness 360 (AIF360) toolkit, and incorporate bias mitigation and explainability into its own products.

Jul 25, 2024 · To trust AI systems, explanations can go a long way. We’re creating tools to help debug AI, where systems can explain what they’re doing. This includes training highly optimized, directly interpretable models, as well as explanations of black-box models and visualizations of neural network information flows.