AI & Local News Challenge
The AI & Local News Challenge — supported by Knight Foundation — is an opportunity for startup, university and news organization teams to develop and advance projects that use AI to address the needs of local news organizations and audiences.
Read more about how to apply and what we’re looking for in Challenge applications in the FAQ below.
Deadline: 11:59pm ET February 20th, 2023.
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Please join us for one of our upcoming info sessions (Fri, Jan 27 1:00 PM ET & Mon, Feb 6 12:00 PM) to learn more about the Challenge.
Frequently Asked Questions
How do I apply?
To apply, please read the FAQ in its entirety and complete the application form.
The deadline to apply is 11:59pm ET February 20th, 2023.
What are the application questions?
To get to know your team and project, we require answers to the following questions. Please answer clearly and concisely. We’ve included suggested paragraph counts for each question. There’s a 2,000-letter maximum limit for each response.
- Describe your project concept. What application of artificial intelligence is your team interested in creating to benefit news organizations, journalists and/or news audiences? (2-3 paragraphs)
- Describe the problem or gap that your project addresses. How will your project help local and regional news organizations continue to produce quality journalism and meet their audience's information needs? (2-3 paragraphs)
- Which technologies are implemented in your project? (1-2 paragraphs)
- Why do you want to take part in this program? How does this project fit into your team's trajectory? (1-2 paragraphs)
- How is your team uniquely qualified to approach this challenge? Include technical capabilities and previous product experience if applicable (1-2 paragraphs)
- How will your team and project bring an awareness of diversity and inclusion in news and artificial intelligence to your work? (1-2 paragraphs)
How does the application process work?
After the application deadline, we’ll send our long list of applications for external feedback. Then, we’ll schedule interviews with finalists. Teams will be notified of their acceptance into the program and expected to confirm their participation shortly after. We’ll also inform teams that aren’t accepted.
When does the program run?
The program will run in spring 2023. After completing some preliminary onboarding and orientation activities, weekly cohort meetings will begin in March 2023. The program will conclude midyear 2023.
What's expected of participating teams?
Teams commit to being available for weekly remote cohort sessions and to work at least 10 hours a week outside of meetings on their projects. Please make sure that you have enough time available to commit to making your project the best it can be.
We expect that teams explore a project focus of AI and local news throughout the program. However, we anticipate that teams may iterate and modify their projects from their original proposal during the course of the Challenge.
Who can apply?
Applications are open to university teams, startup teams and teams based at news organizations.
What are the location requirements for participating teams?
Startups and news organization teams should serve customers based in the United States and have a United States presence and/or be registered in the United States.
University team leads should be affiliated with US-based universities.
What size teams can apply?
The team participating in the program must be between 2 and 5 members. The startups or organizations that teams are affiliated with can be larger.
If you’re currently working solo, please consider looking for a collaborator to join you in the application.
What types of projects are we looking for?
We’re looking for projects that use tools under the broad umbrella of artificial intelligence that have the potential to enhance and enable quality journalism and/or sustainable news organizations, in particular local news. Those tools and approaches include–but are not limited to — automation, algorithms, machine learning, computer vision, deep learning, recommendation systems, natural language processing and natural language generation.
We prefer projects that are past the early discovery phase. The projects that will best match this Challenge should already have a theory of which problems they might solve for which customers. Teams should be ready to receive feedback and prototype and iterate on their project through the Challenge and potentially to pilot with news organizations.
What kind of teams are we looking for?
We’re looking for interdisciplinary teams with experience in fields including–but not limited to — product development, software development, computer science, creative technology, data science, advertising tech, video production, audio production, business, operations, investigative journalism and engagement journalism.
We don’t require experience building products for journalists or news organizations, but we do expect a curiosity and willingness to learn the nuances of the ever-changing local news industry.
What teams or projects wouldn’t be a good fit for this program?
We are looking for teams that are ready to apply AI to use cases that meet current needs in the field of journalism.
Teams that are working on projects that are primarily research will not be a good fit for this program.
We’re excited about working with innovative approaches and emerging technologies that highlight near-term opportunities and paths forward. Projects based around technologies that are not ready to scale up or for production work and won’t be in the next one to two years are not a good fit for this program.
What support will participating teams receive?
Participating teams will each receive awards of up to $7,500.
In addition to the funds, teams will benefit from the structure of the Challenge, hearing from guest speakers, feedback from people in the media and technology industries, guidance from the team at the NYC Media Lab and our network, and support in explaining your work through a short project presentation.
Do we take equity? Who owns intellectual property developed during the Challenge?
No. We do not take equity or any stake in companies or technologies developed as part of the Challenge. We do not take ownership of any intellectual property developed by teams during the Challenge.
How will NYC Media Lab connect teams to news organizations and experts?
As part of the Challenge, we will try to create opportunities for teams to understand industry needs and/or receive feedback on their projects through one-on-one meetings. This might include introductions to people from news organizations and other topic experts or mentors. These meetings are primarily designed for research and not as intros to prospective clients.
What happens at the end of the Challenge?
At the end of the program teams will present their work as part of a Demo Day. Project details and excerpts from the Demo Day presentations, may be showcased and shared with the general public and the NYC Media Lab community.
Follow-on funding May be awarded to some teams after the Challenge.
After the Challenge, we encourage the cohort to keep in touch, keep supporting each other, and to share their learnings. teams may have the opportunity to further develop project pilots and experiments with partner news organizations.
Who has participated in NYC Media Lab Challenges in the past?
NYC Media Lab has hosted past Challenges with tech and media companies and philanthropic organizations. Take a look at some of the participants in our recent programs:
- Verizon 5G EdTech Challenge
- New York Times R&D Fellowships
- Havas Lean Venture Studio for Retail Challenge
Read about the five teams from the first cohort of the AI & Local News Challenge in their end-of-program blog posts:
- AI & Local News Challenge, Information Tracer | NYU Tandon School of Engineering
- AI & Local News Challenge, Gannett/USA TODAY Network’s Localizer news automation program | NYU Tandon School of Engineering
- AI & Local News Challenge, Overtone | NYU Tandon School of Engineering
- AI & Local News Challenge, Building SimPPL for Local News | NYU Tandon School of Engineering
- AI & Local News Challenge, Social Fabric | NYU Tandon School of Engineering
What did participants from the first AI & Local News Cohort say about the program?
- “The program has exceeded my expectations in terms of receiving a lot of feedback, having a high frequency of cohort meetings, having a team channel to ask questions, and providing high-quality speakers and judges. I hope you keep doing this program.” -Zhouhan Chen, Information Tracer
- “Due to this challenge, we were able to turn a student project into a product.” -Swapneel Mehta, SimPPL
- “We made a lot of headway in bringing awareness to our story-generation solution to the newsrooms, obtaining feedback from them, and making corrections.” -Jessica Davis, Localizer
Is this a startup accelerator or incubator?
Not exactly. The primary purpose of the AI & Local News Challenge is to cultivate individuals, ideas, and awareness around AI, automation and the needs of local news. Through this program participants will learn about the local news ecosystem and how tech companies that serve news orgs have made it work. There may be some opportunities to learn about building a startup as part of the program, but in general we expect that participants drive their own startup journeys.
Why AI and local news?
In journalism, artificial intelligence and automation tools create powerful opportunities to evolve and improve processes and workflows at all stages of news work including newsgathering, story creation, distribution, audience engagement and business models for news. Right now, many news organizations — especially at the local level — are experiencing serious economic challenges and many communities are facing a dearth of high-quality reporting about what’s happening in their governments and neighborhoods.
Read more about the intersection of AI and local news in this survey of AI efforts in the news industry conducted by Knight Foundation working with industry experts John Keefe and Jeremy Merrill, and Youyou Zhou.
Artificial Intelligence in Local News: A survey of US newsrooms’ AI readiness from the Associated Press
The State of Local News: The 2022 Report from the Local News Initiative at Northwestern
Check out our info session slides from last year for a few examples of AI news projects.
Who can I contact with further questions?
Get in touch with AI and Local News Community and Project Lead Matt MacVey at email@example.com