Due to confirmation bias, humans tend not to consider themselves to have gender biases. Thus, raising workers’ awareness, especially from the management level is essential. However, most of the “Gender Equality Lessons” in organizations are taken place as contextual/ boring lectures, and most workers/ managers do not take them seriously into it. WE WILL CHANGE THIS. With our gaming system and NLP, the game will help the workers/managers to understand and realize if they are “secretly” holding gender discrimination ideas. Also, the interactive and gaming scenario change the “lesson” into a more “story-telling” game.
The game will help the players to better understand gender equity. Not like normal surveys in which most participants will self-claim themselves to not have gender bias, our game is more like a “double-blind experiment”. The players are been evaluate on their actual sexual thoughts consciously. Through the interactive game, players will have a clue about gender discrimination in the workplace.
We mainly developed the program in Python with Pygame library. With Decision Tree and Natural Language Process, we tried to make the game as a simulation of real-life scenarios where discrimination over gender could happen.
Even in the 21st century, gender discrimination still exists, particularly in the Tech field. Yet people might be tired of this old topic and might not be interested in being preached on that. Thus, aiming to provide a real feeling on the current-day discrimination in workplace, we developed a program providing a manager role for the user to decide what employee he or she wants to use. Then, we will provide a perspective from the employee, interacting with the user’s own decision and thus could cause users to ruminate on their daily lives and small thought directed to discrimination.
After deciding what the game will be about and what tech stack we would like to use—Pygame, we started making the vague idea more and more concrete and split them into different steps. We had UI designers, story writers, data scientists, and software development engineers. We all provided different perspectives regarding the implementation, art, efficiency, etc.
After several rounds of brainstorming, we started to split the task among every teammate, drawing, programming, data training, etc. We decided to make the game look more like a leadership game instead of a didactic program.
Importing the machine learning model from JupyterNoteBook (.ipynb) to a Python file (.py) took us quite some time to figure out the exact way. Moreover, all of us are first-time hackers and have very limited experience in game design, so learning how to use Pygame to design a game was also a main challenge.
As a team of first-time hackers, we managed to build a game that is able to identify potential gender bias deeply entrenched within each individual. We’re both proud of our idea (the ambition of raising awareness of potential gender bias in the workplace) and our efforts to start from scratch and learn along the way.
Technically speaking, we’ve learned how to use Python (Pygame specifically) to develop an interactive game. We’ve also improved our knowledge in areas such as machine learning. UIDesign has also been a key to our project.
What’s more meaningful is what we’ve learned through our planning of the game. It was a lesson for us to always keep in mind that potential gender biases may exist around us or even in our minds.
Add more decision-making plots and situations for the player. After the player saw their scores, show them workers’ perspectives to let them better realize the impact of their behavior and gender discrimination idea on others. Add a time record function in the game, to better measure whether the player has gender discrimination or not. If the player hesitates for a long time during making decisions, then it is highly likely that he/she is trying to hide his/her true thoughts,