1. The pandemic forced many news organizations to innovate how they use technology, rethink how they manage remote staff and make sense of huge amounts of complex information. Covid also demonstrated the importance of tracking data in real-time and making it a central reference for all reporting!
2. The sad reality is that the frequency of how often pandemics occur will only accelerate with climate change, which means newsrooms will need to be at least 10x more efficient in how they collect data — or risk their very own survival.
3. As temperatures rise and the global population grows to 8.5 billion by 2030, humans will live in closer proximity with wild animals that put us at risk of covid-like diseases. …
1.A key premise of computational journalism is that news events can be explained with the same rigor used by scientists to study the natural world. Journalism is going through a process of “mathematization” and eventually evolve into *Information Science*
2.The explosion of data from the web, sensors, mobile devices and satellites, combined with the accessibility to machine learning, creates the ideal environment for transforming how all information around us is sourced.
3. Advances in AI research are already allowing computational journalists to measure issues that were previously impossible to quantify (like counting trees in a desert), and as a result surfacing entirely new analytical baselines for the world around us. …
The growing demand for information during the pandemic has not been met with an adequate increase in journalistic resources. In fact, the opposite has been true. According to the Poynter Institute, in the US alone over 33,000 journalists have been laid off, furloughed, or given pay cuts as a direct consequence of the coronavirus, resulting in a reduced capacity to cover fundamental public health issues. Despite the dire situation, the crisis has shown a secondary, positive side effect: accelerating the speed of journalistic innovation.
Take the case of British local wire service Radar AI. The joint venture between Press Association and Urbs Media leverages machine learning to dynamically generate regionalized COVID-19 news digests, distributed to local news media in the UK. …
Only a few years ago, using artificial intelligence in journalism was cutting edge, but nowadays it is quickly entering the workflow of a growing number of news organizations. The knowledge around machine learning methods is becoming more accessible as the cost of AI projects has gone down since many models are readily available online and can be implemented — even by small newsrooms.
Journalists, who routinely ask questions of their sources, should also be asking questions about an algorithm’s methodology. The rules created for algorithms need to be explicit and understood. The Wall Street Journal has been experimenting with a new approach to explain how AI works by letting readers experiment with it.
“Interactive graphics can provide insights into how algorithms work in a way beyond simply describing its output. They can do this by acting as safe spaces in which readers can experiment with different inputs and immediately see how the computer might respond to it,” said deputy graphics director Elliot Bentley.
“To make this accessible and non-intimidating, it’s important to design a straightforward interface with minimal controls, and also provide informative and immediate feedback,” Bentley added. …
A strategic planning technique, “futurecasting” enables organizations to make decisions about where to focus their growth efforts. At the Associated Press (where I work), we’ve used it to consider an array of provocative — yet plausible — alternative futures that provide the necessary context to explore new opportunities. We collaborated with leading innovation agency Frog Design to imagine the future of the news industry, drive cultural change and embrace innovation.
“It’s essential to look ahead and anticipate change,” said Jaime Holguin, AP’s manager of news development. …
As news consumption patterns change, reporters need to develop new storytelling approaches and master the use of new tools, many of which are now powered by artificial intelligence.
Implementing these smart machines in the newsroom will still demand editorial expertise, though. Because while content can be generated automatically, journalists in new roles such as “automation editors” will need to watch for and correct any errors.
“The current generation of successful automation technology scales the output of human labor, rather than replacing it entirely,” said Nick Haynes, a data scientist at Automated Insights who helped teach the workshop.
Live Like Fiction: thank you for helping turn my blog posts into a book!
As a few of you may already know, I was given the opportunity to turn my viral blog posts here on Medium into a book called Live Like Fiction. It’s filled with inspiring stories, practical strategies and thought-provoking activities to help uncover the best version of yourself.🙌
The book will be released mid-July. In the interim, I am starting this newsletter to share with you stories that combine purpose, inspiration and storytelling. These are the ingredients you will need to turn your dreams into reality! …
Fake news is nothing new. The Roman Emperor Augustus led a campaign of misinformation against Mark Antony, a rival politician and general. The KGB used disinformation throughout the Cold War to enhance its political standing. Today fake news continues to serve as a political tool around the world, and new technologies are enabling individuals to propagate that fake news at unprecedented rates.
One of those new developments, artificial intelligence, can help journalists build a consistent fake news detector, but AI can also empower others to disseminate and even create new forms of misinformation. …
The first wave of this symbiosis was news automation, where artificial intelligence systems generate written stories and alerts directly from data. The goal is not to displace journalists from their jobs — it’s about freeing up their time from labor-intensive tasks so they can do higher-order journalism.
Following the direction set in motion by automation, the next evolution will be about leveraging smart tools that can help journalists augment their own writing. This means AI-powered interfaces capable of providing context to topics in real time and even optimizing a news report based on its dateline and subject matter.
AI will help journalists do more investigative work by analyzing massive sets of data and pointing to relationships not easily visible to even the most experienced reporter. The combination of AI and journalism will contribute to a more informed and efficient society by enabling journalists to conduct deep analysis, uncover corruption, and hold people and institutions accountable. This evolution in journalism comes at a time when fake news seems to cast a shadow over trust in our industry. …