Meet the JournalismAI Fellows of 2022

The JournalismAI team at the London School of Economics and Political Science has selected the inaugural cohort of JournalismAI Fellows, with support from the Google News Initiative: 46 journalists and technologists from 16 countries across all continents will work together in ten teams for the next six months to explore innovative solutions to improve journalism via the use of AI technologies.

Their projects will explore how a responsible use of AI can contribute to building more sustainable, inclusive, and independent journalism in all parts of the world. From building tools to support investigative journalists in their research, to automatically detecting hate speech on social media, and helping newsrooms identify underreported topics in their coverage, the JournalismAI Fellows will combine the latest AI techniques with traditional reporting methods to innovate how journalism is produced.

The ten Fellowship teams continue the JournalismAI tradition of fostering cross-border and interdisciplinary collaboration, with data scientists, reporters, product managers, researchers and software engineers working together with peers from news organisations in different continents – including collaborations between legacy brands and digital media from India and South Africa, Spain and Australia, as well as Argentina, Paraguay and the Philippines.

Due to the significant amount of exciting project proposals we received – 61 news organisations applying from 35 countries – we selected ten teams of Fellows rather than five as initially planned. Thanks to the support of the Google News Initiative and of our partners at the Northwestern University | Medill’s Knight Lab, we will guide the ten teams in the development of their projects, leading up to the presentation of their products and findings at the 2022 edition of the JournalismAI Festival.

To stay informed about the work of the fellows over the coming months, you can sign up for the JournalismAI newsletter.

The JournalismAI Fellows of 2022 are:

Attack Detector

 Reinaldo Chaves (Project Coordinator) & Schirlei Alves (Data Journalist), Abraji (Brazil)

Fernanda Aguirre Ruiz (Data Analyst and Researcher) & Gibrán Mena (Research and Direction), Data Crítica (Mexico)

Our project aims to train a language model to detect hate speech on social media – in Spanish and Portuguese – directed primarily at journalists and environmental activists. The model will classify the instances of hate speech among their diverse categories and understand why and how they are happening.

Automating Visuals for Machine-Driven Content

 Theresa Poulson (Senior Product Manager) & Tyler Dukes (Investigative Reporter), McClatchy (US)

 Sean Smith (Product Manager) & Mike Stucka (National Data Solutions Editor), Gannett / USA TODAY Network (US)

One of the biggest challenges with AI-made coverage is the ability to generate images that enrich and compliment stories. Images are also key to successful distribution and reaching new audiences. Our project will explore a solution for automatically creating relevant imagery for content made with natural language generation.

Bad Will Hunting

Alet Law (Audience Development Manager) & Tinashe Munyuki (Retention Manager), Daily Maverick (South Africa)

Luis Flores (Data Scientist) & Chris Moran (Head of Editorial Innovation), The Guardian (UK)

Dimitri Tokmetzis (Senior Investigative Journalist and Data Team Lead) & Heleen Emanuel (Data Journalist and Creative Developer), Follow The Money (Netherlands)

Searching and comparing massive datasets for evidence of graft has become a big part of many investigative journalists’ jobs. Our project will use AI to extract NLP entities based on enriched context from long-form text, to do cross-referencing with preexisting knowledge bases/graph models. In doing so, we hope to cut down the time needed in manual curation.

Claim Check

Gina McKeon (Innovation Editor) & Gareth Seneque (Technical Lead – AI/ML), Australian Broadcasting Corporation 

Irene Larraz (Fact-Checking and Data Coordinator) & Rubén Miguez (Chief Technology Officer), Newtral (Spain)

We aim to create a multilingual tool for journalists that uses AI to quickly detect false claims by setting up an alert system through an interface in Teams or Slack. This system will become a central hub for newsrooms to quickly check specific claims, thereby improving accuracy and enhancing the reporting capabilities of newsrooms.

Context Cards

Amanda Strydom (Senior Programme Manager – CivicSignal) & Fadel Thior (Deputy Investigative Manager), Code for Africa / PesaCheck (South Africa)

Ritvvij Parrikh (Director of News Products) & Karn Bhushan (Lead Data Analyst), Times of India

Context Cards is a machine learning model that creates and suggests context — data, bios, summary, location, timeline — to audiences and journalists, alongside an article. It will be trained on newsroom archives, and learn from editors’ feedback. We are building on prior work, including modularjournalism.com, Newscards, and Structured Stories.

Image2Text

Lucila Pinto (Product Manager) & Nicolas Russo (Product Manager), Grupo Octubre (Argentina)

Jaemark Tordecilla (Editor-in-Chief and Head of Digital Media) & Raymund Sarmiento (Chief Technology Officer), GMA News Online (Philippines)

Sara Campos (Product Editor) & Eduardo Ayala (Senior Full-Stack Developer), El Surti (Paraguay)

Image2Text identifies, classifies and describes video and images for newsrooms. Powered by computer vision models, it recognises objects and people in video, images and infographics, and describes them in Spanish and English through natural language. The tool seeks to promote better data governance by including perspectives from the Global South.

Nubia

Joshua Olufemi (Founder and Managing Director) & Emmanuel Alawode (Full-Stack Developer), Dataphyte (Nigeria)

Mads Ommundsen (Journalist & Product Owner) & Frode Norbø (Developer and Designer), Fædrelandsvennen (Norway)

Nubia is an AI-powered reporter that auto-creates development reports and data insights by transforming real time data from satellite/web camera imagery, weather and socioeconomic data into news reports, data insights and advisory that can be distributed directly to the newsroom and general audience.

Parrot

Venetia Menzies (Data and Digital Journalist) & Ademola Bello (Data Journalist), The Times & Sunday Times (UK)

Alessandro Alviani (Product Owner) & Simone Di Stefano (Data Engineer), Ippen Media (Germany)

Parrot is a tool and methodology to help journalists identify and measure the spread of manipulated narratives from state-controlled media. Using AI we will develop an early warning system that clusters and classifies state media generated text and then detects coordinated efforts at its dissemination.

Tracking Influencers

Carmen Aguílar Garcia (Senior Data Journalist) & Przemyslaw Pluta (Head of Platform Solutions), Sky News (UK)

Juliana Fregoso (Project Manager for AI and Special Projects Newsroom) & Matias Contreras (Chief Technology Officer), Infobae (Argentina)

Pier Paolo Bozzano (Journalist and Head of Content Innovation Lab) & Marina Caporlingua (Software Engineer), Il Sole 24 Ore (Italy)

Our project aims to help journalists to investigate influencers on a greater scale using AI techniques and developing a replicable methodology. It will track the brands, products, topics that influencers are sharing, and it will develop a scoring system to flag potential harmful or misleading content for a journalist to investigate further.

What’s there? What’s missing?

Jörg Pfeiffer (Product Manager) & Philipp Gawlik (Language Engineer and Computational Linguist), Bayerischer Rundfunk (Germany)

Martin Paul (Chief of Service, Journalist) & Jaime Avalos Mongil (Junior Data Scientist), MDR / ida (Germany)

BR and MDR are both German public broadcasters with the mandate to provide multifaceted information to different kinds of audiences. We want to use NLP to build a tool that analyses our published content, as well as the reactions of our audiences, to find underreported topics in our publications.