Starting My Summer Internship at the Northeastern Civic AI Lab

Starting My Summer Internship at the Northeastern Civic AI Lab

Intro

Hi! I’m Simon Juknelis, a rising high school senior at Noble and Greenough in Dedham, MA, and this week, I am beginning my work as an intern at the Civic AI Lab at Northeastern University. I’ve always been interested in building projects that help other people and make an impact, and that’s what I hope to achieve over the course of this internship.
The lab’s overall mission is to build new technology solutions that create equitable positive impacts and that empower all members of society. To achieve this goal, the lab works with non-profit organizations such as the National Science Foundation and UNESCO as well as tech industry leaders such as Twitch and Meta. The lab has done research into a large number of areas such as preventing disinformation using AI and data labeling work, and I’m very excited to get to work with this team! Participatory Design
Our lab’s work over the coming months will involve building software solutions for use by and to benefit gig workers. As such, I read up on the methodological framework of participatory design. Participatory design encapsulates the idea of giving the users of a product the power to shape it to fit their needs. Participatory design can be carried out with interviews and workshop sessions with a sample of potential users of the product. The future users should be given the ability to give suggestions during the ideation phase of the product as well as at various stages throughout its development. Our lab will be using participatory design over the next few months in order to conduct our research and build solutions. As we work on finding research participants and setting up interviews, I decided to test my technical skills by building a small web plugin called ProductWords, which allows users to look through Amazon products, add them to a list, and see statistics about them.

Participatory Design for Gig Workers

In fields like gig work, there can often be a large power imbalance between a single worker, on one hand, and the corporate clients and work platforms, on the other hand, that provide the gig worker’s income. As such, when tools are designed for gig workers, they are often designed without gig workers’ actual needs in mind, and instead are designed by the platforms based on what they think the workers need or even based on what would benefit them or the clients. As such, participatory design is an important tool to ensure that tools built for gig workers actually benefit those workers.

Designing Tools for Gig Workers with Figma

Part of our lab’s work will involve using a software platform called Figma for UI/UX design. One of the main benefits of using a service like Figma is the collaborative benefits it provides. It allows for ideas about interface layout, animations, and functionality to be more easily communicated between team members, and multiple team members can work together on the same files to create a unified design workspace. I used Figma to design the interface for ProductWords. Doing it this way was especially helpful because I have not yet finished implementing all of these visual elements into ProductWords, but I still have a good sense of what I want the final product to look like and I’ll be able to look back on this Figma doc to see what I should implement.

Data Visualizations for Gig Workers

Our lab is also planning on making extensive use of data visualization in our research on the gig economy. One common and easy-to-understand form of data visualization is the word cloud, which displays words at a size corresponding to their frequency in a given text. One of the resources our team was using described how to create a word cloud using a Python library; however, as I was building ProductWords as a web plugin, I needed to find a way to do this with JavaScript. I found a JavaScript library called D3 which is a general-purpose solution for creating visual representations of data to be displayed on web pages. Combined with an extension for D3 created by Jason Davies, I was able to create word clouds based on the descriptions of the Amazon products in the list.

Other Technical Aspects

One of the main reasons I decided to make this web plugin was that I wanted to practice some of the features of web plugins that we might want to use for our lab’s research. With ProductWords, I implemented web scraping (pulling the Amazon item description and price information), a popup page, and communication between the web-scraper background script and the popup script.
ProductWords is not a very useful plugin yet, but I got some good practice implementing the features that will probably be necessary for any version of the web plugin(s) our lab will work on, and maybe it could even be used as a jumping-off point that gets evolved into our final product.