Pushing media into new spaces.

Knight Lab Studio is an interdisciplinary class where Northwestern students, faculty, and professional staff work together at the intersection of storytelling, design, and technology: all media and platforms are fair game. As we work on these problems, we produce cutting-edge digital work, research, and thought — innovating across every part of the media-making process.

Our process combines user and audience research, design thinking, critical and analytical work, iterative building, storytelling, new technology, and a healthy dose of experimentation--often within the confines of a single, specific problem.

Applications for the Spring 2026 Studio class are closed. We can let you know when we announce the next round of projects!

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Zach Wise
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Zach Wise
The Podcast Discoverability group present their findings to the rest of the studio class.

Join Us

Build new tools and tell new stories.

Each quarter, we pull together multidisciplinary teams of Northwestern students, faculty, and professionals to collaborate on projects we believe are important for the future of media. That could mean everything from making obscure data more available to journalists to solving questions around how to best navigate space in virtual reality. The Lab places students at the center of these important problems for 10 weeks. We work together to identify problems and to find solutions.

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The Podcast Discoverability group discuss design options.

The class is a team-based, cooperative lab experience for students who want to create and explore new tools, stories, story forms, and physical devices.

Our most successful students are driven and motivated; they possess the curiosity and determination to drive and sustain a project from start to finish. They are comfortable with ambiguity, and have a strong desire to identify lines of questioning and paths to find the answers. We expect students to spend at least six hours a week on the project outside of class times. Synthesizing the work you do and communicating it clearly to your teammates and to the instructional team will be crucial; you should expect to spend a portion of each week doing this.

The class is cross-listed as JOUR 342 and EECS 397/497. For Spring, it meets Tues/Thurs, 2:00-3:50pm.

Applications for Spring 2026 are closed.

Projects running in Spring 2026.

Bedrock: Human Ground Truth for Generative AI

In an era of "agentic journalism," the role of the reporter is shifting from content creator to truth architect. As audiences increasingly consume news through AI agents—like ChatGPT, Apple Intelligence, or specialized wearables—the traditional article is becoming a secondary format. The primary value of journalism now lies in the verified human reporting that prevents these agents from hallucinating.

Bedrock is a studio project focused on creating a High-Fidelity Reporting Package (HFRP). This is a machine-readable "ground truth artifact" that allows a journalist to package field-verified data (claims, media, and context) into a structured format. Once the human "mines" the truth, AI agents can then reliably refine and distribute that truth into podcasts, vertical videos, or interactive alerts without losing the original reporting's nuance.

CensusBotTapping AI to help reporters use high-value, high-complexity data

With over 1000 tables, almost 28,000 variables, and hundreds of thousands of geographies, American Community Survey data can be overwhelming. Reporters struggle with understanding geographic summary levels, knowing what tables are available, and understanding the definitions of technical terminology. This project aims to build a conversational AI tool that taps general Census documentation as well as our knowledge from building Census Reporter to help users more casually ask for guidance and get plain language answers that help them find data from the American Community Survey, whether through Census Reporter or other means.

Mirror: Synthetic Audience Auditing

As newsrooms shift from "article factories" to "knowledge engines," understanding how different communities perceive a story is crucial for maintaining trust. Mirror is an editorial auditing tool that uses "digital twins"—AI-generated representations of real audience segments—to simulate how diverse groups might respond to journalism before it is published.

Building on concepts from Kaveh Waddell's Verso and recent research from Northwestern, Stanford, and Google DeepMind, this project explores the potential of agent-based modeling in news. Studies have shown that generative agents built from qualitative interviews can replicate human responses with 85% accuracy. Mirror leverages this capability not to replace human engagement, but to scale it—allowing journalists to identify blind spots, tone issues, and potential biases when resources for real-world focus groups are limited.

Newsroom Strategies for the Federated WebBuilding and engaging audiences beyond platform control

For at least fifteen years, news publishers and independent journalists have built their audiences on centralized platforms—Twitter, Facebook, Instagram, YouTube. But platform instability, algorithm changes, and the threat of deplatforming have exposed the vulnerability of this model. News organizations and independent journalists who've built significant followings can lose everything overnight due to one moderation decision or ownership change. Federated social media platforms like BlueSky and Mastodon are built on the promise of putting more control in the hands of creators, but pose new challenges of their own. Newsletter-oriented publishing tools like Substack and Ghost provide another way to stay in touch with audiences, but what are the tradeoffs a publisher has to consider when choosing tools like these? How should newsrooms and independent publishers build and maintain engaged audiences in this new landscape?

Questions?

Reach out to the Knight Lab team. Want to stay in the loop? We can let you know when we announce the next round of projects!

Frequently asked questions

  • When are Applications Due?

    Applications are due by Wednesday, Feb 11th at 9AM.

  • When will I know if I got in?

    Students will know if they are accepted before Northwestern registration opens. Typically we contact students 1-2 days after the deadline (Wednesday, Feb 11th at 9AM).

  • When is the class held?

    Tues/Thurs, 2:00-3:50pm

  • What does this count for?

    You can take this course for JOUR 342 and EECS 397/497 credit.

  • I’m not sure I’m technical enough.

    Some, but not all, of our projects require technical know-how. And all of our projects have important non-technical roles.

  • I applied last time but didn’t get in.

    Ugh, that sucks. But we’d love for you to try again! We admire tenacity, and a new round of projects requires a new round of people.

  • How long is your application?

    It’s low-key and takes about 8 minutes to fill out.

  • How do I apply?

    The link to the application is on each project page. Below is a link to the application, just make sure you read the project descriptions first.

    Apply to a Project

Project Results

Prototypes, research, guides and presentations from projects that have run in the Knight Lab Studio.
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Projects

Projects that have run in the Knight Lab Studio.

Upcoming Projects

Knight Lab Studio projects running in Spring 2026.

Bedrock: Human Ground Truth for Generative AI

In an era of "agentic journalism," the role of the reporter is shifting from content creator to truth architect. As audiences increasingly consume news through AI agents—like ChatGPT, Apple Intelligence, or specialized wearables—the traditional article is becoming a secondary format. The primary value of journalism now lies in the verified human reporting that prevents these agents from hallucinating.

Bedrock is a studio project focused on creating a High-Fidelity Reporting Package (HFRP). This is a machine-readable "ground truth artifact" that allows a journalist to package field-verified data (claims, media, and context) into a structured format. Once the human "mines" the truth, AI agents can then reliably refine and distribute that truth into podcasts, vertical videos, or interactive alerts without losing the original reporting's nuance.

CensusBotTapping AI to help reporters use high-value, high-complexity data

With over 1000 tables, almost 28,000 variables, and hundreds of thousands of geographies, American Community Survey data can be overwhelming. Reporters struggle with understanding geographic summary levels, knowing what tables are available, and understanding the definitions of technical terminology. This project aims to build a conversational AI tool that taps general Census documentation as well as our knowledge from building Census Reporter to help users more casually ask for guidance and get plain language answers that help them find data from the American Community Survey, whether through Census Reporter or other means.

Mirror: Synthetic Audience Auditing

As newsrooms shift from "article factories" to "knowledge engines," understanding how different communities perceive a story is crucial for maintaining trust. Mirror is an editorial auditing tool that uses "digital twins"—AI-generated representations of real audience segments—to simulate how diverse groups might respond to journalism before it is published.

Building on concepts from Kaveh Waddell's Verso and recent research from Northwestern, Stanford, and Google DeepMind, this project explores the potential of agent-based modeling in news. Studies have shown that generative agents built from qualitative interviews can replicate human responses with 85% accuracy. Mirror leverages this capability not to replace human engagement, but to scale it—allowing journalists to identify blind spots, tone issues, and potential biases when resources for real-world focus groups are limited.

Newsroom Strategies for the Federated WebBuilding and engaging audiences beyond platform control

For at least fifteen years, news publishers and independent journalists have built their audiences on centralized platforms—Twitter, Facebook, Instagram, YouTube. But platform instability, algorithm changes, and the threat of deplatforming have exposed the vulnerability of this model. News organizations and independent journalists who've built significant followings can lose everything overnight due to one moderation decision or ownership change. Federated social media platforms like BlueSky and Mastodon are built on the promise of putting more control in the hands of creators, but pose new challenges of their own. Newsletter-oriented publishing tools like Substack and Ghost provide another way to stay in touch with audiences, but what are the tradeoffs a publisher has to consider when choosing tools like these? How should newsrooms and independent publishers build and maintain engaged audiences in this new landscape?

Design Research

Inspiration and Ideation

Auditing the NewsEvaluating News Quality on Smart Speakers

Alexa, Siri, Google Home, Cortana—smart speakers and agents are now used by about 20% of US homes. People use them to ask about weather, set timers, play games, get information, or listen to the news. But are these devices delivering high-quality news and information or could they be misinforming and sharing “junk” news? This project aims to find out. By developing an audit method that defines what queries to audit and systematically collects data on the results over time for those queries from several different smart speakers, the project will allow for an assessment and comparison of news quality from these different devices.

Civic Engagement with City Bureau

As local news organizations shrink, many civic advocates fear that no one will be monitoring the day-to-day processes that make city governments run. As part of their innovative approach to closing news gaps and promoting civic engagement, Chicago’s City Bureau has developed their “Documenters” program to train citizens to observe and record public meetings. As they develop this team of citizen journalists, they are now considering the complementary question: what is the most effective way to make the work they produce available and useful to Chicagoans?

For this project, the Northwestern student team will conduct design research and prototyping to explore solutions. Students will be expected to be in close contact with City Bureau’s team, with current documenters, and with engaged citizens who want to stay informed about what’s happening at the heart of these civic processes. Students should be prepared to go out into Chicago to meet with these people face to face for interviews, observations, and prototype testing.

ProPublica Illinois

Students will design, develop, prototype and test one tool for community engagement, with a likely focus on the listening and information gathering stage.

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Mixed Reality

Virtual, Augmented... It's all Reality

Augmented Reality Visualizations

An experimental design project that explores visualizing data in three dimensions for augmented reality. Visualizations that can be examined and inspected by physically getting closer or understood by walking around them, open up exciting possibilities for how we communicate complex ideas and data that reveals hidden truths.

Exploring Data Visualization in VR

An experimental design project, in which we students are analyzing methods for communicating data visually and exploring how those principles might be transferred and transformed in a 360 environment.

Photojournalism in 3D for VR and Beyond

In this project, students will use modern approaches to making 3D images both with hardware and software processing.

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Product

Our most solution-oriented projects.

Creative Co-Author

Creative Co-author is a creative writing enhancement tool that focuses primarily on pounding out the first draft. It is type-ahead cranked up to eleven. It types ahead, lurks behind, and generally peers over your shoulder while you pound out words in a speed-draft writing reverie.

Storytelling with GIFsFacilitate simple visual social sharing.

This project will build upon prototypes and research conducted in the Fall 2019 Studio class, but participation is open to any interested student. As the open-web continues to die, storytellers need tools that help them create sharable artifacts suitable for a variety of social networks and platforms. Brevity and portability are of the utmost importance. This project is concerned with designing a tool that allows novice storytellers to create simple 5 frame (5 images) GIFS that when combined with text for the post, are sharable on a variety of platforms and social networks. This iteration of the project will be focused on UX and UI design and building a sustainable application for the creation of visual stories saved in the GIF file format.

Storyline: Charts that tell stories.

One of the most common problems we see in data storytelling is how and when to introduce an editorial layer onto a visualization. Mobile devices afford us very little real estate to work with, and interactivity must be limited. But without a “story” layer, users are left without the context to understand what events might impact or inform a trend. They see something going up or down but don’t see why. “Storyline” will be a tool for creating stories around line graphs.

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Sensors

Using sensors to collect information about our environment.

Environmental Reporting with Sensors

Sensor journalism uses sensors to collect information about our environment. It opens new possibilities for journalists enabling them to collect and process data that might not be available or at a level of detail not previously available.

Privacy Mirror

The average person today that has a smartphone, walks around leaking information about themselves over radio signals. WiFi, bluetooth and NFC radiate personal information into the public airwaves. These signals can tell you a lot about a person without their knowledge. To raise awareness around privacy and security for digital devices, this project will seek to create a “mirror” that reflects back information that is radiating out from anyone who stands in front of it. Frequencies include: RFID cell phones, WiFi, bluetooth, Misc RF at 900Mhz 2.4Ghz 5Ghz

SensorGrid API and Dashboard

SensorGrid is Knight Lab's experimental prototype environmental sensor wireless network system. This project will focus on the design and development of the web API and user dashboard for SensorGrid data management and presentation.

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