Reporting On (and With) Artificial Intelligence

Temperature-detecting cameras. Drones. Technology that police say can predict human feelings. As government agencies quietly deployed new surveillance and predictive tools to monitor their citizens in a time of pandemic and protests, the team at AP compared these tools’ application across nations, and probe how people’s personal data can be sold and mined to expand the knowledge infrastructure of governments and corporations.

As part of the investigation, Varsha Bansal conducted a survey of 150 Uber drivers across different parts of India to find out how many of them had been locked out of their accounts—either temporarily or permanently—due to issues related to facial recognition. This investigative effort prompted the gig workers' union to start collecting their own data to petition the platforms.

Social Sentinel said its AI technology could help schools prevent suicides and shootings. Our investigation found no evidence that any student lives were saved because of an alert from the service. Our project was a comprehensive examination of the use of social media surveillance software on college campuses. We hope more journalists—particularly student journalists—will continue to examine the impact of artificial intelligence.

Lydia Emmanouilidou worked with journalists and researchers to investigate EU-funded high-tech surveillance systems at Greek refugee camps and the Greek border, how they compare to technologies at the U.S.-Mexico border, and U.S.-Greek/European collaboration and lesson-learning on border technology initiatives.

Lighthouse Reports and WIRED teamed up to examine the growing use and deployment of algorithmic risk assessments in European welfare systems across four axes: people, technology, politics, and business. This methodology explains how they developed a hypothesis and used public records laws to obtain the technical materials necessary to test it.

On February 24, 2022, Pulitzer Center grantees Karen Hao and Joanne Cavanaugh Simpson joined Reuters Executive Editor Gina Chua for a conversation on AI accountability. The speakers shared how they got started reporting on algorithms, discussed their challenges and breakthroughs, and offered tips for colleagues interested in covering this urgent, underreported story.

The true scale of oil well abandonment is likely far greater than the official numbers. In this visually stunning and immersive project, Grist and the Texas Observer modeled oil wells that are likely to be abandoned in the coming years and chronicled the experiences of two Texas ranchers struggling to hold oil companies accountable for polluting their properties.

Land banks are vital public agencies who play a key part in turning decrepit, abandoned properties back into viable homes before they attract pests and crime. Using machine learning methods, Eye on Ohio looked at property remediation in several counties to look deeper at a process that has transformed the rust belt over several years.

Using machine learning, The Charlotte Observer and The News & Observer look into a new class of landlords in North Carolina's booming housing market that includes Wall Street hedge funds and other institutional investors. This toolkit is for local and national journalists at a variety of skill levels who are interested in probing the extent of corporate homeownership in their cities, regions, and states.

Amazon Mining Watch uses machine learning to map the scars of mining activities in the Amazonian countries. By constantly analyzing high-resolution and historical satellite images, this tool aims at identifying the fast-paced growth of open-pit mining in the largest rainforest in the world. This database is here to help journalists, activists, and researchers better understand the causes and impacts of the mining industry.

In the Venezuelan Amazon, traces of the devastation caused by illegal mining can be seen from the sky. This investigation arose from a survey of satellite monitoring information, later processed with artificial intelligence, to see and understand in a comprehensive way the evolution of the mining phenomenon in the Venezuelan Guayana, north of the Amazon.

From Freedom of Information requests to using artificial intelligence to analyze satellite imagery, the reporters got their hands on previously unseen data that sheds light on the corruption and systems behind the destruction of the world’s biggest rainforests. Learn about their innovative methodologies.

Algorithms also have the potential to disproportionately harm some of the most vulnerable members of society by deepening pre-existing social and economic gaps and amplifying racial bias. At the Pulitzer Center we believe this is not just a tech story but an accountability and equity one, too, that should be part of every reporter’s beat.

Pulitzer Center grantee Simpson offered her insights on the topic of artificial intelligence and machine learning (including police surveillance), the intersection of technology and society, and how to approach the tensions between the two in emerging AI technologies as a journalist.

The Pulitzer Center encourages proposals that use advanced data mining techniques, such as machine learning and natural language processing, to solve a data or reporting problem related to a journalistic investigation.

The Pulitzer Center is seeking compelling data-driven storytelling, based on original data collection and analysis and strong visuals, that has the potential to shape public discourse and hold the powerful accountable.