Overview:
As the web developer for three key Microsoft AI initiatives—Fairlearn, InterpretML, and WhiteNoise—I was responsible for bringing these projects to life online. Each of these platforms plays a critical role in advancing responsible and ethical AI, and my work focused on creating seamless and intuitive digital experiences that align with their missions.
Project Highlights:
- Fairlearn: I developed Fairlearn, a user-friendly website that serves as a hub for data scientists aiming to improve the fairness of AI systems. Using the Bootstrap framework, I ensured the site was responsive and accessible, while wireframes designed in Figma guided the layout and functionality. The site offers guides, use cases, and a Python toolkit, enabling the community to assess and mitigate fairness issues in AI.
- InterpretML: For InterpretML, I built a platform that allows users to understand and responsibly deploy machine learning models. The site provides toolkits that explain model behavior, promoting transparency in AI. My development work ensured that users could easily navigate the site and access these critical resources.
- WhiteNoise: WhiteNoise focuses on maintaining privacy while using data for machine learning and analytics. This differential privacy toolkit uses advanced techniques to protect sensitive information, and the website I created clearly communicates its purpose and tools. The responsive design, driven by Bootstrap and Figma wireframes, makes it easy for users to explore and utilize the toolkit.
Tools & Technologies:
- Framework: Bootstrap
- Design & Wireframing: Figma
- Languages: HTML, CSS, JavaScript
Outcome:
These websites have become essential resources for developers, data scientists, and organizations looking to integrate ethical AI practices into their work. My role in developing these sites has contributed to advancing Microsoft’s vision for responsible and fair AI technology.