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Mattia Peretti

March 14th, 2023

“It’s not rocket science”, and other things participants learned about AI on the JournalismAI Discovery course


Estimated reading time: 5 minutes

Mattia Peretti

March 14th, 2023

“It’s not rocket science”, and other things participants learned about AI on the JournalismAI Discovery course


Estimated reading time: 5 minutes

“The course helped me understand some concepts about AI – which is what I expected – but not with this kind of precision and simplicity. Now I really understand the power of AI, as well as the limitations of some technologies that came up in the last couple of years. I decided to go deeper and keep studying this field after this course.”

When you create a learning experience, like an online course, this is exactly the type of feedback you hope to receive from participants.

When I started designing the JournalismAI Discovery course, I wanted to build a learning experience that journalists – busy and time-poor as they are – could use to really understand what AI technologies can do for them, without having to dedicate too much time or effort to the experience.

Considering that participants reported a 52% increase in their self-assessed AI literacy after taking the course, it’s safe to say that it went very well.

My colleague Brandon Roberts, who created the content for the course, has already shared some of the main things we learned. But in studying the feedback we received from the participants, I was amazed by the breadth of what they learned from the course.

So I decided to group their learnings in a few categories and put together a little summary where you can see what participants learned thanks to JournalismAI Discovery – directly in their own words. (Some quotes are slightly edited for clarity.)

If this makes you want to take the course yourself, you are in luck: sign up for our newsletter to be informed when registrations re-open in the next few months!


Seeing the wide range of examples of how AI technologies have already been used across newsrooms and some of the mechanics behind how they were implemented. This is incredibly important in order to make a case for adopting the technologies within our own newsrooms.

By far, what Discovery course-takers loved the most was finding in the course many examples, use cases, and existing AI journalism projects. Participants were excited to discover how many AI applications already exist, and how much there is to learn from them.


 I have learned that it can be used for gathering information, to produce news, to enhance our relationship with the audience and in the process of distribution.

And it wasn’t only the amount of examples. The ubiquity of AI applications across the journalistic process was also one of the main reported learnings.


 AI is not a magical super intelligence. It can augment and innovate journalism if properly utilised.

All the examples helped demystify AI and clarify its true potential for newsrooms.


 We need to better understand why AI works in a certain way in a certain setting.

 You have to be aware of the boundaries and risks while working with AI.

But it’s not all power and opportunities. As we like to say at JournalismAI, with new powers come new responsibilities. Participants told us they learned about the limitations of AI and the risks its application poses.


 The use of AI in journalism is not necessarily expensive or impossible without enormous resources. But you have to know your problem, the type of technology you want to use, and how and where to collect the data.

JournalismAI Discovery helped democratise AI by making it more accessible for journalists and giving them the confidence that it can be used by everyone, even with limited resources or technical expertise. Or as another participant concisely put it: “It’s not rocket science.”


 I understand more about the role of data and algorithms. Concepts such as supervised and unsupervised machine learning were very useful.

Participants learned the fundamental role that data plays in all AI journalism projects, and how different applications require different types of data and different approaches to using it.


 I learned the definitions of AI-related terminology (e.g. machine learning, NLP).

They learned things they didn’t know about AI by studying the definitions, and learning about different research areas, as well as different types of AI.


 Learning about the production process in a very methodological way. I found the most value from Modules 4 and 5. Having a clearly defined project guide really helped me shape a proposal that I have on using AI within my own newsroom.

And it wasn’t all theory. We helped course-takers understand how to approach strategy and design their implementation process. For many of them, it will help them start their first AI journalism project.


 Getting started is easier than many think, but it requires the right mindset and resources.

 Always ask yourself what assumptions you’re carrying with you into your AI journalism projects.

 We have to ask the right questions and understand if the AI can solve our problem.

These are some of my favourite comments – so much so that I had to include all three of them! A lot of the content from JournalismAI Discovery was devoted to sharing tips and important lessons on mindset and methodology – equally, if not more, important than the technology itself.


A screenshot of one of the modules of JournalismAI Discovery from my inbox.


 We need to understand and learn how to make the most of AI technology to deliver great journalism.

 Journalists need to upskill to remain at the forefront of the changes taking places across AI technologies.

Most participants left the course with the conviction that AI is essentially unavoidable. Journalists, like many other sectors in society, must learn to understand its applications and its implications. We are incredibly excited to read that 94% of course-takers are ‘likely’ or ‘very likely’ to recommend their colleagues to take the JournalismAI Discovery course in the near future.


 Human intervention is still very much needed. Technology cannot replace the news skills of journalists.

And maybe, most importantly, participants understood that AI can’t and won’t replace journalists. As I said in a previous post: “The truth is that artificial intelligence is not nearly as intelligent as it would need to be to replace you. It can take away some tasks that we normally do. But it’s us who decide what those tasks are, based on what tools we decide to build with AI.


The first edition of JournalismAI Discovery was a fantastic experience – for us as a team and much so for the participants, who embraced the opportunity to learn about AI along with fellow journalists from all over the world.

We are proud of what we were able to achieve with this course, and we look forward to improving it and making it available again to a new cohort of journalists and media professionals very soon.

Wherever you are based in the world, stay tuned for the return of JournalismAI Discovery. Stay curious, and stay ambitious like our Discovery participants:

I think that AI in Journalism is giving innovators, media professionals, and entrepreneurs a huge opportunity to solve many issues that persisted for many years in the industry. Even someone like me, born and raised in a developing country, was inspired to do something meaningful with AI. I found many encouraging signs that there is a huge potential and I decided to embrace the challenge. I even sent a memo to my colleagues that we must become the first newsroom to implement AI projects in Mongolia.


If you want to take part in the next edition of JournalismAI Discovery, sign up for our newsletter to be informed when registrations re-open in 2023.

JournalismAI is a global initiative of Polis and it’s supported by the Google News Initiative. Our mission is to empower news organisations to use artificial intelligence responsibly.

About the author

Mattia Peretti

Posted In: JournalismAI | Project Update

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