Intro
The adoption of dogs from shelters is a rewarding yet often challenging endeavor. By harnessing the power of artificial intelligence, particularly language models, my goal is to simplify this process for potential dog owners while putting dogs at shelters in the spotlight. Working with Dierenbescherming Foundation Nederland has provided invaluable insights into the constraints and possibilities within the pet adoption ecosystem.
Challenge
Through my initial phase of discovery and research, I pinpointed several challenges:
- Overwhelming Choices: The vast number of breeds, sizes, and personalities make the decision-making process difficult.
- Misalignment of Expectations: Many adopters are not well-matched with their chosen dogs, leading to failed adoptions.
- Lack of Visibility: Dogs in shelters often don't get the visibility they deserve.
- Time-Intensive: The existing adoption process can be lengthy and exhausting.
My project, Woofah, focuses primarily on solving these challenges by streamlining and personalizing the adoption process.
Constraints
Building a solution was not without its challenges. There were constraints like the quality and consistency of data from shelters, ensuring the language model's suggestions were accurate, and respecting user privacy.
Research
Through extensive interviews and discussions, it became apparent that using a language model could be a potential solution for the identified issues. I zeroed in on the code review process and hypothesized that a language model could assist in streamlining this procedure.
Iterations
Upon developing the initial prototype, multiple rounds of user testing were carried out. Feedback from shelter staff and potential adopters played an essential role in making necessary adjustments to the system.
Key Features
- Personalization: Using OpenAI's API, the system identifies user preferences to suggest the most compatible dogs.
- Increased Visibility: The platform brings often-overlooked dogs into the spotlight, increasing their chances of adoption.
- Efficiency: By narrowing down choices, the application significantly cuts down the time spent on searching and deciding.
- User Experience: The Next.js and Supabase tech stack allows for a responsive, robust, and user-friendly application.
Outro
The Woofah project demonstrates the transformative power of AI and web technologies in addressing real-world issues like pet adoption. While still a work in progress, the initial results are promising, and the impact could be profound.
The next steps involve refining the model, extending the collaboration with shelters, and measuring the long-term impact of the platform on adoption rates.
Thank you for exploring this project. I continue to leverage technology to address societal challenges, one paw at a time.
