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IncludeMe - Inclusive Data Creates Inclusive Products
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An example of how low representation in ML datasets leads to bad products
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Our website using Google's Cloud Vision API and seeing that it fails to recognize one of the faces. Users can then correct it to contribute
Inspiration
Most tech products use machine learning trained on data where minorities are underrepresented, leading to the products not working well for minorities.
What it does
IncludeMe is a training data crowdsourcing platform where users can earn money for uploading, labeling, and verifying data that companies need to make their products more inclusive.
Anyone can contribute photos and speech clips to improve ML datasets for companies, and are incentivized through monetary rewards for contributing. Other users can verify submissions to maintain the integrity of the data.
How we built it
We used html, css, javascript, and some google cloud APIs
Challenges we ran into
Lack of time to implement the functionalities we wanted
Accomplishments that we're proud of
Creating a demoable prototype in time
What we learned
How to use a new CSS framework called blocks.css, how to use google cloud vision API
What's next for IncludeMe
Implementing the speech recognition tasks and image labeling functionality
Built With
- css3
- git
- github
- google-cloud-vision-api
- google-speech-to-text-api
- html5
- javascript
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