NYC Media Lab announces inaugural cohort of AI & Local News challenge
NYC Media Lab is thrilled to announce the inaugural cohort for the AI & Local News Challenge!
Over the first half of 2022, the five selected teams will be building AI applications for local news to support quality information for local news audiences and sustainable news outlets. The teams represent a dynamic mix of technological and journalistic backgrounds, ranging from news organizations and startups to university research and development.
Support for the AI & Local News Challenge comes from Knight Foundation.
Ready to meet our five teams? We present you…
Team members: Zhouhan Chen, Joshua Tucker
Information Tracer is a real-time, cross-platform information gathering system that contextualizes and quantifies information spread. Their technology can monitor trending stories, facilitate fact checking, and help newsroom reporters collect writing material for the spread of news across multiple platforms.
More specifically, given a query, e.g., a keyword, URL, or hashtag, Information Tracer collects posts that share the query from multiple social media platforms —Twitter, Facebook, YouTube, Reddit, Gab, etc. The system then applies network science and Natural Language Processing techniques to visualize information spread and provide actionable metrics, which are accessible via an interactive web interface and API endpoints.
Both members of Information Tracer are part of the Center for Social Media and Politics at New York University. They have a deep interest in understanding how people use social media, how news spreads, and how to prevent the spread of misinformation. They build tools and design interventions to mitigate the harm of hate speech and fake news. The team looks forward to collaborating with news outlets to improve the overall online news ecosystem.
Team members: Jessica Davis, Steve Dorsey, Danny Sanchez, Mike Stucka, Eric Ulken
At Gannett, news automation is the fuel that helps achieve greater relevance by delivering hyperlocal information at scale to drive digital subscription growth. Localizer uses news automation techniques, such as Natural Language Generation, to parse data into local stories. This frees reporters to create deeply reported journalism that can’t be done by a machine.
The team’s challenge is to operationalize this work and build out a robust content calendar with the ultimate goal of creating one local story in multiple formats (articles, newsletters, graphics, audio scripts) every weekday for each of the local newsrooms across their Network.
The News Automation Team has been at the forefront of pilot concepts through Localizer’s project, producing hyperlocal articles for COVID-19 case and vaccination trackers, hurricane coverage, a US Census data release, and real estate trends in the past year.
The team is a mix of experienced journalists and product partners with backgrounds in data reporting, software development, product management, audience development, and content strategy. The current cross-divisional effort consists of and draws on experience from previous automation efforts at GateHouse Media and Gannett prior to the companies’ merger.
Team members: Philip Allin, Christopher Brennan, Natalia Gutierrez, Reagan Nunnally
Overtone has built a Natural Language Processing (NLP) tool that finds and sorts online content by quality. Their AI assesses content based on various journalistic signals that demonstrate human value-add in articles. Their data suggests that readers understand when they see quality, and subscribe to it at higher rates. This tech also helps publishers sort through articles and archives almost instantaneously.
Overtone is currently expanding these “quality scores” from English to other languages, beginning with Spanish. Spanish is an obvious choice for US markets, and has global potential. The team aims to release the API and Feeds versions of their technology in Spanish, as there is great journalism out there that doesn’t reach the audience it should.
Overtone believes in the power of independent media, especially at the local level, which can use AI to inform and engage audiences of all backgrounds and interests. They are the only startup looking to improve the quality of news online by using AI to assess journalistic value of the text itself, rather than mere clicks or shares.
Founded by a team with decades of experience in journalism, AI, enterprise, and startup, Overtone expressed their excitement to be working with NYC Media Lab on this crucial project.
Team members: Harshit Agarwal, Swapneel Mehta, Surabhi Ranjan, Shwetanshu Singh
SimPPL (read: sim-people) is a simulator of user activity on social networks. It tracks engagement with news stories, develops a model conditioned on individual attitudes toward news-sharing, and measures user behavior to guide content generation and digital distribution.
Knowledge of the history of conversations as they relate to audience engagement is an incredibly powerful tool to direct journalists and media orgs. With the advent of probabilistic AI to analyze richly structured online interactions, this is becoming an increasingly lucrative direction for organizations to explore.
SimPPL is a team of researchers and engineers driven by the common agenda of using AI for social good. They bring a keen understanding of news and information propagation on digital platforms, particularly Twitter, Reddit, and Facebook. Team members have worked on both sides of the aisle, deploying AI-based tools for cross-domain applications involving news and social media, while researching their impact on other consumers of digital content.
SimPPL’s goal is to build a product that empowers stakeholders, enables audits of existing news-sharing campaigns, and provides support for decisions about content creation and publication online.
Social Fabric for Publishers
Team members: Brad Friedman, Evan Friedman
As publishers look to expand their offerings to news readers, Social Fabric for Publishers helps publishers bring the social conversation directly to consumers. The team’s technology makes it scalable to share topical conversations across a publisher’s article pages, giving media outlets new ways to drive engagement in addition to personalization features that tap into users’ social graphs.
Social Fabric for Publishers is a New York-based startup with a mixed background in media, technology, and product. They believe in the power of social media and news, and encourage media organizations to become stakeholders in the conversation — similar to tech companies.
The team’s primary goal is to enable news organizations to participate in the digital public square in a way that unlocks new business opportunities, and drives healthier social conversations, which can help news organizations overcome the various challenges they face, including polarization, misinformation, and disinformation.
We look forward to seeing what these innovative teams produce, as we mentor them along the way. The AI & Local News Challenge officially begins in mid-February and will conclude with a Demo Day in May 2022.
The AI & Local News Challenge is part of the AI & Local News Initiative that includes partner organizations Associated Press, the Brown Institute’s Local News Lab, NYC Media Lab, and Partnership on AI. Read about the Knight Foundation industry survey to look at the landscape of AI and news here.