clinicalml/onboarding_human_ai
Onboarding Humans to work with AI: Algorithms to find regions and describe them in natural language that show how humans should collaborate with AI (NeurIPS23)
This project helps teams understand how humans and AI systems can collaborate more effectively. It takes in data where humans and AI have made decisions and outputs natural language descriptions of specific data subsets where the AI either performs better or worse than human expectations. This is for AI project managers, ethicists, and team leads who need to align human expertise with AI capabilities.
No commits in the last 6 months.
Use this if you need to onboard humans to work with AI, identifying specific scenarios where the AI is highly reliable, or where human intervention is crucial.
Not ideal if you are looking for a tool that retrains or improves the AI model itself, as this focuses on understanding and describing existing AI behavior for human collaboration.
Stars
12
Forks
2
Language
Jupyter Notebook
License
—
Category
Last pushed
Mar 15, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/clinicalml/onboarding_human_ai"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
qxresearch/qxresearch-event-1
Python hands on tutorial with 50+ Python Application (10 lines of code) By @xiaowuc2
SAP-samples/codejam-cap-llm
This repository contains the content for the CAP and Generative AI Hub CodeJam. It includes...
diegopacheco/ai-playground
AI POCS: ML, NLP, LLM, Vision, Classification, clustering, GenAI, Transformers, PyTorch, Keras,...
simranjeet97/75DayHard_GenAI_LLM_Challenge
This repository contain my 75Day Hard Generative AI and LLM Learning Challenge.
jedi4ever/learning-llms-and-genai-for-dev-sec-ops
A set of lessons aimed at anyone learning LLM and generative AI concepts, with sections on...