Human-AI Collaboration Enables More Empathic Conversations in Text-based Peer-to-Peer Mental Health Support

This repository contains a demo for our Human-AI Collaboration Approach For Enabling More Empathic Conversations in Text-based Peer-to-Peer Mental Health Support.

[arxiv preprint] [project webpage]

If this code helps you in your research, please cite the following publication:

@article{Sharma2022Human,
  title={Human-AI Collaboration Enables More Empathic Conversations in Text-based Peer-to-Peer Mental Health Support},
  author={Sharma, Ashish and Lin, Inna W and Miner, Adam S and Atkins, David C and Althoff, Tim},
  journal={Nature Machine Intelligence (in press)},
  year={2022},
}

Introduction

We develop Hailey, an AI-in-the-loop agent that provides just-in-time feedback to help participants who provide support (peer supporters) respond more empathically to those seeking help (support seekers). We evaluate Hailey in a randomized controlled trial with real-world peer supporters on TalkLife (N=300). We show that our Human-AI collaboration approach leads to a 19.60% increase in conversational empathy between peers overall.

Quickstart

1. Prerequisites

Our framework can be compiled on Python 3 environments. The modules used in our code can be installed using:

$ pip install -r requirements.txt

2. Run API

We will use an API to request just-in-feedback. To run the API, please run the following command:

$ python api.py

Note: In this demo, the API only works with a sample example. To create a generalized version, use empathic rewriting.

3. Start the Demo

Open hailey_demo in your browser to start the demo.