Helping journalists understand the power of machine learning
Editor’s note: What impact can AI and machine learning have on journalism? That is a question the Google News Initiative is exploring through a partnership with Polis, the international journalism think tank at the London School of Economics and Political Science. The following post is written by Mattia Peretti, who manages the program, called JournalismAI.
In the global survey we conducted last year about the use of artificial intelligence (AI) by news organizations, most respondents highlighted the urgent need to educate and train their newsroom on the potential offered by machine learning and other AI-powered technologies. Improving AI literacy was seen as vital to change culture and improve understanding of new tools and systems:
“AI literacy is crucial. The more the newsroom at large embraces the technology and generates the ideas and expertise for AI projects, the better the outcome.”
The message from newsrooms was loud and clear. So we decided to do something about it. That’s why we’re announcing a free training course produced by JournalismAI in collaboration with VRT News and the Google News Initiative.
This Introduction to Machine Learning is built by journalists, for journalists, and it will help answer questions such as: What is machine learning? How do you train a machine learning model? What can journalists and news organizations do with it and why is it important to use it responsibly?
The course is available in 17 different languages on the Google News Initiative Training Center. By logging in, you can track your progress and get a certificate when you complete the course. The Training Center also has a variety of other courses to help you find, verify and tell news stories online.
The Introduction to Machine Learning is available on the Google News Initiative Training Center in 17 different languages.
It’s a tough time for journalists and news organizations worldwide, as they try to assess the impact that COVID-19 will have on the business and editorial side of the industry. With JournalismAI, we want to play our role in helping to minimize costs and enhance opportunities for the industry through these new technologies. This course complements our recently launched collaborative experiment, as well as our effort to highlight profiles and experiments that show the transformative potential of AI and machine learning in shaping the journalist, and the journalism, of the future.
At the end of the course, you’ll find a list of recommended resources, produced by journalism and technology experts across the world, that have been instrumental in designing our Introduction to Machine Learning and will help you dive even deeper in the world of AI and automation.
And we are not done. After this course, and the previous training module with strategic suggestions on AI adoption, we are planning to design more training resources on AI and machine learning for journalists later this year. Sign up for the JournalismAI newsletter to stay updated.
