Jeremy Gilbert

Knight Professor in Digital Media Strategy

Jeremy Gilbert is the Knight Professor of Digital Media Strategy. Both his work and teaching focus on the content and revenue strategies of existing and emerging media companies. He explores the intersection of technology and media, examining how new tools and techniques will affect the creation, consumption and distribution of media.

Projects

Projects Jeremy Gilbert has worked on.

Journalism AI Readiness Scorecard

Artificial intelligence (AI) drives innovation at news organizations around the world. Journalists use algorithms to find patterns in data to inform investigations and identify breaking news. Automation enables more efficient news production. AI helps drive subscriptions and personalize news for consumers. Yet AI advantages are largely limited to larger, national and international media. Many small, locally focused newsrooms lack the resources and skills to understand the potential of AI and are afraid to commit to experiments without a clear payoff.

The Knight Foundation has funded an initiative to help local news organizations expand their use of AI, harnessing it for long-term sustainability. As part of this effort, The Associated Press and the Knight Lab are developing a scorecard for AI newsroom readiness. The benchmark will help news organizations determine whether they are ready to implement AI systems.

In this Knight Lab Studio project, students will work with AP’s technology leaders and Knight Lab to develop a framework for testing and assessing a newsroom's AI readiness. This includes researching best practices, interviewing those news outlets already using AI, and those who wish to. It also includes evaluating and recommending effective product designs for the scorecard to maximize its usage and performance.

Coding skills are not required to participate in this project.

Journalistic Diversity Dashboard

In recent years, much attention has been drawn to the social and cultural identities of journalists, and the ways in which those identities are often quite different from those of the audiences those journalists cover. From race and gender to education level and economic class, audiences and even the news organizations are looking for data to help them put stories into perspective. For this project, students will focus on the design of a system which could help track and convey this information. They will research how underrepresented communities perceive different news organizations as well as what people in the field of journalism have already been exploring in this area. They will identify key identity types or other traits that advance this understanding; they will explore what it would take to gather and sustain a database like this; and, they will explore and test multiple data visualization concepts to see which are the most effective for making sense of the data. If students identify promising paths to building and sustaining a tool like this, Knight Lab is interested in the future possibility of developing this into an ongoing public project.

Exploring AI-Powered Local Newsrooms

Generative AI is transforming all kinds of industries, including local news. Newsrooms need to know what tools to trust, how best to use them, and what they might cost. Automation can aid writers, create images, detect patterns in data, identify potential news events, promote content, convert articles to email newsletters and much more. Local news needs a playbook for automation.

Follow the MoneyTracking Local Campaign Finance

Each year, political campaigns break records for money raised and spent. Where does all that money come from? Who’s giving it? What are their interests in supporting any given candidate? Researching these questions has become a key part of national political coverage, and between the Federal Election Commission and various public interest organizations, basic access to campaign finance data is well understood. Things are much different for state and local elections. Reporting regulations vary considerably from state to state, and local news organizations are often short of the resources required to deal with the complexity of even gathering contribution data, let alone analyzing it.

Tinder for Freelancers

Freelance journalists struggle to connect with editors, land assignments and establish steady cash flow. Meanwhile, news organizations need freelancers with diverse experiences and subject matter expertise to contribute a broad array of articles, photographs and other content. The Center for Independent Journalists (The CIJ) launched in September 2021 aiming to bridge the gap between these groups by providing support, community, education, tools and advocacy to freelancers and by offering editors access to a diverse group of independent journalists. For this project, the team will seek to better understand the barriers of information, trust and communication that prevent editors from hiring diverse freelancers -- which ultimately often ends up pushing freelancers of color out of the field. In consultation with the Center for Independent Journalists, students on this project will conduct design research and develop concepts and prototypes of a matching system which may inform future development by the CIJ.

Design Research in Local Newsrooms

It’s hard to run a local news organization. Advertising dollars have been siphoned away by social media platforms; audiences have many more choices of where to spend their attention and their money. These times call for creative thinking and reassessment of how local news organizations spend their energy and money.

Metaverse Media

A year ago, the word “metaverse” was just a concept from a classic Science Fiction novel, but since then, it has leapt into the public conversation. But what does “metaverse” really mean? And how might the metaverse (or some metaverses) impact, or provide opportunities for journalism?

The Partisanship Detector

Do the words journalists choose reveal unconscious political biases or create/reinforce similar biases? The 2016 and 2020 presidential elections made vicious and fierce rhetoric the norm and strong political identification a fact of life. The accusations of “fake news” and bias ring loudly, destroying the perception of a free and fair press and posing a threat to democracy. The challenge for this project is to develop a human-centered process and natural language processing tools to help journalists make less freighted word choices; that is, a detector for partisan language when covering political news.