20 Past 4

Inspiration

Our inspiration came from the increase in smoking marijuana and vaping in younger generations, instilling bad habits from a young age due to factors such as lack of education, bad influences, and peer pressure. Statistics show that Canada was ranked as one of the top 5 countries with the highest cannabis use rates in 2020 and when it comes to marijuana, kids who smoke pot tend to start between the ages of 12 and 16. To address the high prevalence of cannabis use in Canada, our team has risen to this challenge by developing interactive simulations that engage and empower the younger generation to make informed decisions about their health and well-being. The fact that kids who smoke pot start at a young age add to the urgency of tackling the issue

What it does

We developed an interactive game, “20 Past 4”, which promotes and empowers the younger generation with the knowledge they need to make informed choices surrounding substance use in daily situations. We do so by educating individuals on how to react to various scenarios, from responding to peer pressure to communicating the negative effects of marijuana use on the environment and personal health. The application provides users with three levels that reflect three possible scenarios, where the responses are fed through Cohere API which classifies all responses as either positive or negative. We used the Cohere Classify playground to help produce test cases and train the API to produce accurate responses. Based on the response, the game prompts the user to try again with a better response or to move onto the next level.

How we built it

This game was built using Python and Pygame on VSCode, and imported Cohere Classification API.

Challenges we ran into

We had difficulty importing the Cohere API as it was the first time we used an API before, and it was resolved through consulting with the company representative. We also had issues with the API-generated responses when prompted with user input, as the classifications would not be 100% accurate. To solve this, we fed more test cases through Cohere's playground classification system to train the API to improve its detection accuracy.

Accomplishments that we're proud of

We are proud to have coded a functional and interactive game using Python and Pygame, and to have implemented an API for the first time.

What we learned

We learned that it is important to constantly keep the judging rubric in mind to maintain the scope of the project, and achieve more efficient research methods when navigating new software. We also learned that help is always available and to take initiative when we are stuck on certain aspects of the project.

What's next for 20 Past 4

We have plans to educate on the impacts of drugs on other elements such as Earth and Fire, where an example of cocaine production causes deforestation. As well, we hope to implement more variations of scenarios where young teens may encounter conflicting scenarios relating to drug use and peer pressure, because not only does it impact their youth but it impacts the environment. We will remain cost-effective because it allows for widespread accessibility where the game can be easily distributed via the internet, reaching a broad audience without the need for expensive physical distribution or marketing.

Built With

• pygame
• python