LANDING PAGE
SIGNIN OR SIGNUP PAGE
ANALYSING TEXT AND RATING THE USER CONTENT
ANALYSING THE BIAS WORDS AND SUGGESTING THE UNBIASED CONTENT
HISTORY OF THE USER

BiasBuster – Write Fair, Write Aware

Inspiration:

While reading job posts, bios, and messages, we noticed that certain words like “rockstar,” “young,” or “aggressive” are commonly used but can make some people feel excluded based on gender, age, or tone. These words aren’t always meant to harm, but they can still send the wrong message. We wanted to build a tool that helps people become more aware of how their words may sound and helps them write in a way that’s fair, respectful, and inclusive. That’s how BiasBuster was born:

A simple, smart tool to help everyone Write Fair, Write Aware.

Key features

BiasBuster helps you :

Paste any text (like job posts, messages, etc.)
Find biased or exclusive words
Learn why the word might be a problem
Get better word suggestions
See a score showing how inclusive your text is
provides the history of the user
It’s fast, simple, and works in your browser

Development Workflow

Backend: Python and Flask
NLP: Used spaCy to process the text
Logic: We made our own list of biased words and grouped them (gender, age, tone)
Frontend: HTML, CSS, and JavaScript
Scoring: We give a score out of 10 based on how inclusive the text is
Everything runs locally no need for big AI models or internet access.

Key Struggles

Some words are only biased in certain contexts
We had to make the tool helpful without being too critical
Keeping everything simple and quick for users
False positives: Some words can be biased in one context and harmless in another (e.g., "dominant" in sports vs leadership)
UX clarity: Displaying feedback without shaming users or overwhelming them was important. We focused on tone-friendly tooltips and color-coded highlights.

Milestones Achieved

A project that’s easy to deploy, open-source, and accessible to non-tech users
No external tools or paid services needed
Helps users learn and improve their writing
Built in just few days from scratch
Functional NLP analysis without training any models or relying on APIs
Designing a tool that makes people reflect on language and inclusivity

Insights Gained

How to use NLP with spaCy
How to detect bias in real-world writing
How to design simple tools that solve real problems
That small tools can make a big difference
How to build AI tools that are ethical, practical, and helpful
The power of a good user experience even the best AI fails if people don’t enjoy using it