This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and beyond.

Aligning AI With Shared Human Values (ICLR 2021)

LangFair is a Python library for conducting use-case level LLM bias and fairness assessments

📚 A curated list of papers & technical articles on AI Quality & Safety

A curated list of awesome academic research, books, code of ethics, data sets, institutes, maturity models, newsletters, principles, podcasts, reports, tools, regulations and standards related to Responsible, Trustworthy, and Human-Centered AI.

Documentation for dynamic machine learning systems.

Master thesis: Exploring bias in German NLG (GPT-3 & GerPT-2). Applies regard classification and bias mitigation triggers.

Visually compare fill-in-the-blank LLM prompts to uncover learned biases and associations!

Experimental interface environment for open source LLM, designed to democratize the use of AI. Powered by llama-cpp, llama-cpp-python and Gradio.

A python implementation of Dave Shap's ACE Model

NudeDetect is a Python-based tool for detecting nudity and adult content in images. This project combines the capabilities of the NudeNet library, EasyOCR for text detection, and the Better Profanity library for identifying offensive language in text.

Trustworthy AI: From Theory to Practice book. Explore the intersection of ethics and technology with 'Trustworthy AI: From Theory to Practice.' This comprehensive guide delves into creating AI models that prioritize privacy, security, and robustness. Featuring practical examples in Python, it covers uncertainty quantification, adversarial ML

Intercept AI - Empowering safe and secure online experiences through cutting-edge content filtering technology.

Personal Data Science Projects

Capture fundamentals around ethics of AI, responsible AI from principle, process, standards, guidelines, ecosystem, regulation/risk standpoint.

Automate LLM ethical self-assessments

Ami is friend in French. She could be everyone's friend, and is extremely helpful

Hackathon winner at AI Engineer World Fair Hackathon: Transforming code, one function at a time, to reduce digital carbon footprints and create a more sustainable digital world.

Upload, score, and visually compare multiple LLM-graded summaries simultaneously!

KLEP (Key-Lock-Executable-Process) is a groundbreaking AI framework that utilizes symbolic AI for dynamic decision-making. It integrates keys, locks, executables, and processes to foster ethical, modular, and transparent AI applications, offering a novel approach for developers and researchers in AI and cognitive science.