If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here. You can now also follow MyType on Linkedin, Instagram and Twitter.

Now, let's get started! 

I hope you all had a great summer! We definitely took the time to recharge and used these last few weeks to finalize a project we’ve been working on for months, designed just for you! 

We can finally announce it: the Atex AI Challenge is now live, our accelerator program calling all journalists and newsrooms worldwide! 

A Challenge that aims to be an opportunity to unite forces and face the new challenges of journalism together, powered by Artificial Intelligence. The Atex AI Accelerator Program is a global initiative aimed at tackling the biggest challenges in journalism through the power of Artificial Intelligence. 

Whether it's streamlining news gathering, improving distribution, or boosting subscriptions, we’re looking for your bold AI-driven ideas! 

How to submit your idea

Whether you are a journalist, a newsroom leader, media organization or maybe you are part of an editorial group, the Atex AI Challenge is an opportunity to make a lasting impact. Submissions can range from improving advertising integration to enhancing news personalization and monetization strategies. 

Join the challenge and submit your idea

What’s in it for you?

Selected projects will receive funding (AI credits), technical resources, and expert guidance to develop and validate your idea! 

Our team

This is a major project we’re advancing with the help of a strong team supporting us. First of all, we want to thank Alberto Puliafito - Journalist, co-founder, and director of Slow News - for his work and his article on The FIX Media.
Alberto will help us in selecting the most deserving projects and will be available for personalized training programs.

Join us!

Would you like to help us give visibility to the initiative, collaborate with us, and join the team? You can directly contact Atex at challenge@atex.com  

So, apply now!

The deadline for submitting applications is October 20^th. 
Don’t miss this opportunity! Read the call for applications and submit your idea: https://atex.com/ai/atex-ai-challenge-the-accelerator-program/ 
and share this news with your contacts! 

Do you have an innovative idea and would like to integrate it into your editorial flow? contact our AI team or send me an email (sforni@atex.com) we can do it together! 

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here. You can now also follow MyType on Linkedin, Instagram and Twitter.

Now, let's get started! 

MyType and Factiverse: The first synergy for Fact-Checking directly on the CMS

In recent months, we have increasingly come to understand that the best work is done in teams, combining the skills and experiences of different actors.

At MyType, we know this well, which is why we have always sought to join forces with those who, like us, strive to deliver high-quality services and products in the service of journalism.

Starting today, I want to begin sharing all these valuable collaborations with you, revealing the faces and work of those who help us improve every day: I'm talking about our new collaboration with Factiverse, the company that helps organizations mitigate risk by identifying misinformation and hallucinations.

But let's start from the beginning: why do we need a search engine like Factiverse? And how does it work?

In an era where misinformation is increasingly pervasive, fact-checking is an essential tool for newsrooms to guarantee quality journalism, ensuring reliability and credibility. Accurate fact-checking maintains readers' trust, avoiding unfortunate errors that could compromise the publication's reputation.

Besides being an ethical obligation for journalists, fact-checking combats misinformation and low-quality AI-generated information and ensures that the news is truthful. Verifying and comparing the authenticity of sources is crucial to avoid publishing news based on unconfirmed rumours.

This is why MyType integrates Factiverse's search engine into its CMS, an innovative tool essential for ensuring higher quality and control of facts, with more security and in less time

The ability to quickly verify information with reliable tools is fundamental in a competitive market: speed and accuracy can only be guaranteed by advanced AI-driven technologies. It is within this framework that the new partnership between MyType and Factiverse is established, the first synergy that brings fact-checking directly to the CMS level.

MyType is the first and only CMS to have natively integrated Factisearch from Factiverse. Integrating Factisearch into our CMS means providing concrete help for the journalists who use our system and the model of usage is very simple: the journalist will find a tab next to the writing editor that can be used as a fact-search engine. There, a list of sources will appear, and the tool can confirm or reject the news being written - in 55 languages - thus avoiding falling into false information. Although the verification work of sources remains on the journalist, Factisearch is certainly an extra help, especially in moments of urgency and when there are many news items to write and check.

The floor is yours, Factiverse!

Factiverse has been building their own AI model since 2016 as part of the University of Stavanger research. Factiverse’s model outperforms leading LLMs in a variety of tasks like detecting claims in large amounts of content and finding credible and nuanced sources. “Over 2 billion people are voting this year in countries including the United States, India, Mexico, and South Africa, and the amount of false information on elections is spreading fast. By using Factisearch, journalists can find the most relevant and recent fact-checks from the whole world in 55 languages and quickly get an overview of election disinformation”, says Maria Amelie, CEO and Cofounder of Factiverse.

With Factiverse tools, decision-makers in media verify crucial textual information, news, reports, chatbots and AI content. The goal? Simple, to be the backbone of credibility for businesses worldwide!

And you, what do you think? Would you like to integrate AI into your editorial workflow as well? Would you like to propose some ideas for us to work on together?

Do you have an innovative idea and would like to integrate it into your editorial flow? contact our AI team or send me an email (sforni@atex.com) we can do it together!

There would be no 'digital joynalism' without sharing. If you like this newsletter, you could share it with colleagues, friends and family :)

Share MyType

Ps. It's definitely too hot to continue reading newsletters, isn't it? We at MyType are taking a little summer break ☀️ Talk to you again in September

 👋🏼

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation, and artificial intelligence. 

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here. You can now also follow MyType on Linkedin, Instagram and Twitter.

Now, let's get started! 

I know, I know… we haven't spoken in almost a month. But it has been a very busy month, full of trips, exciting workshops, and very interesting new people.

By the way, last Thursday marked the conclusion of the World News Media Congress organized by WAN-IFRA, which this year was held in Copenhagen. The theme of the 75th edition of the congress was "Shaping the Future of News Media in the AI Era" and expectations were more than met.

There were dozens of panels and talks dedicated to how Artificial Intelligence will change and has already changed the world of journalism. Among the speakers were notable names, including Alex Hardiman, CPO of The New York Times, and Anna Bateson, CEO of the Guardian Media Group. We also took the stage, but we'll talk about that in a moment.

In the past few days, I have had the time to absorb the various ideas and organize my thoughts. These thoughts will later translate into my work. In general, my first impression is that we are all more or less at the same point. Don't get me wrong, there are companies and newsrooms that have used GenAI in new and innovative ways, but generally, the impression is that by May 2024, some functionalities have become the solid foundation of innovation. Summarization, title and lead suggestions, translation (so much so that during the congress it was possible to follow the conferences with automatic transcription and translation in one's own language), content personalization, and SEO optimization are all activities that many have integrated into their systems and that many more have at least tested. It would suffice to open ChatGPT to try one of these functions.

From here, however, emerges a deeper reflection shared by many experts: the importance of customization as a key element in the success of an AI-based project. A newsroom that decides to use a language model to obtain a list of suggested titles for its content cannot be satisfied with a simple drop-down menu with a list of pre-set tones of voice (informal, lively, brilliant, serious), but must take the next step and try to replicate a writing style that reflects that of the publication. This is a simple but useful example to explain the concept od the real difference that will, from now on, be made by content personalization, with an initial phase of fine-tuning and continuous optimization of results based on journalists' feedback.

GenAI is a UX Revolution

Another important theme is integration, which is essential for making the use of AI smooth in various parts of the daily workflow. Understanding how to integrate different AI technologies in the same place and, most importantly, making them pleasant to use will be a decisive and differentiating element. While today the most well-known and widely used Large Language Models (LLMs) provide (more or less) similar performance, the user experience (UX) of digital products will play a fundamental role in determining the performance of these tools and in redesigning editorial products.

Six steps for AI adoption in the newsroom

As I mentioned earlier, at Atex we also gave a speech at the congress. The subtitle of our session was "The Evolution of Newswork and Ethics in a Generative Information Ecosystem" and we invited Hannes Cools, Assistant Professor of 'Human Factor in New Technologies' at the University of Amsterdam, to speak with us. I had previously interviewed him for a newsletter, which you can find here.

After his presentation, I discussed six steps for AI adoption in newsrooms. For about a year, we have been working with a long-standing Atex client, to integrate some AI features into their CMS, that is also one of our product. We have translated our job in six steps for AI adoption in newsrooms. These points are not strict rules because every case is different, but they help us to manage our  AI adoption process.

The first step starts from the problems of the newsrooms. Only when we have identified problems, we can start thinking at the right AI solutions. With the solution in our hand, or better, the idea of the solution, we will start working closely to the newsrooms for the co-design of the AI product. In this phase, we fine-tune the outputs and try to identify the goals to be achieved.

A gift for you

Third, based on our experience, we have decided not to rely on a single AI model but to be flexible in our adoption. For this reason, the AI team constantly evaluates which LLMs work best for a particular request. The fourth point is about the concrete implementation of the AI solution, which we can do natively with Atex products or through APIs.

Fifth, we are a tech company and therefore believe in the value of data. For this reason, we provide to every clients a dashboard to monitor the AI consumption of various tools. This way, they can also understand when, in some circumstances, it might be time to take a step back. Sixth, of course, integrating AI into a system is a continuous cycle. This iterative process helps in refining the AI applications to better meet the evolving needs of the newsroom and ensuring they deliver the intended benefits over time.

Finally, a story that struck me

Among the various sessions I attended, I was particularly struck by the presentation from Onet.pl, online portal in Poland, with 25 years of experience in the digital publishing and internet industry. Like many digital media outlets and beyond, Onet has had to rethink how to engage users and "do" journalism in recent years.

Founded in 1999, Onet continued on its path like most digital media until 2018. At some point, however, they realized that something needed to change, and it was necessary to engage users (who in their case were a vast audience with very different interests) in a targeted way. Thus, from 2021, they began a journey of content personalization for audience segments. With the boom of Generative AI, since 2024, they have practiced what they call 'one-to-one personalization,' meaning the ability to customize the website's homepage for each individual user. So, a young teenager interested in sports will see the news arranged in one way, while a 60-year-old woman will see different news, with different headlines.

Now, 18 million Poles visiting Onet every month enjoy personalized and engaging home pages.

Big opportunity!

Have all these news inspired you? Would you like to integrate AI into your editorial workflow as well?

Contact our AI team or send me an email (sforni@atex.com) we can do it together!

There would be no 'digital joynalism' without sharing. If you like this newsletter, you could share it with colleagues, friends and family :)

Share MyType

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation, and artificial intelligence. 

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here. You can now also follow MyType on Linkedin, Instagram and Twitter.

Now, let's get started! 

Following the success of last month's interview with Jaemark Tordecilla (if you missed it, you can read it here), this month we went inside a newsroom that is very active in the development of AI solutions to optimise workflows.

A journey we took together with Sannuta Raghu, Lead - AI Working Group, News & Journalism at Scroll Media Inc. Scroll is a small newsroom in India, with under 20 journalists, known for their deeply reported longform journalism. 

Among the various very interesting insights that emerged from the interview, I would like to make it very clear that developing AI products and innovating one's own newsroom does not require millionaire capital. Sometimes even with small teams and a lot of expertise you can find decisive solutions to improve your daily work.

I hope this interview can be an inspiration to many small/medium-sized publishers and journalists!

The subtitle of this newsletter is: AI and journalism, opportunity, or threat? To answer this question, we decided to ask experts in the field. So, what is the answer you would give to this first question?

I think we are at this juncture right now:

It’s not yet possible to zoom out and look at the big picture, and we are making decisions and assessing situations based on the information we have today. 

So I would add a good dose of journalistic skepticism and take a ‘Yes, but…’ approach for both the opportunity vantage point and the threat vantage point. Yes, an LLM finds a needle in a haystack for my investigative report and saves me days of high-bandwidth work, but is it built with the human values my news organisation and I value? Yes, the problem of misinformation is real, but does increasing the supply of misinformation with AI mean that people will consume more of it?  We are untangling and wading through many, many grey areas, and this is true with any new adoption of evolving technology. 

In our small newsroom, for example, we are experimenting and building with cautious optimism. Our starting point and hypothesis is that the use of generative AI in our news workflows will make the lives of our journalists easier. But we inspect our output with a fine-tooth comb before we publish because we encounter bias, inaccuracies, misinterpretations, and misrepresentations very often. 

The hope is that the payoff at the end of the end of the opportunity is much, much larger.

In your current job you lead the AI team at Scroll Media. Tell us more about this experience: When did you feel the need to have an in-house AI use case team in the newsroom? How many people work with you? How is the team composed?

In 2019, we had to let go of a big part of our video team. Many organisations worldwide have gone through this in the last 8 years. We decided we will not over-hire here and subsequently lay off colleagues and work on how we could make our video production workflow more resource-effective. For context: In 2018-19, when we were producing an award-winning news-explainer show for India’s biggest OTT platform, our team was at it for 14 hours every weekday for 14 months, performing high-cognitive load tasks.News agency footage in India is limited, which meant that we were relying on complex composite graphics to tell a news story effectively. At the end, we had *one* 12-minute video everyday. This was not sustainable. 

After several rejections, we won a Google Innovation Challenge in 2022 to build an AI-based video production tool for high-quality short-shelf-life videos. This is where we started.

Over the last 18 months, because of our URL-to-mp4 tool, we’ve been able to gain experience in several areas that make up the workflow.

Our working group is composed of 2 engineers, 1 product leader, and 1 editorial leader. A larger policy input group helps shape the direction we want to go in. One engineer and I have been working on all our news and journalism-related AI experiments and POCs everyday. 

We are moving to productizing our URL-to-video tool, and we now work with a project team of 14 (including frontend engineers, backend engineers and product designers) to ship this to market.

What are the main products you have produced for Scroll Media?

Currently, we are working only with generative AI. We are taking an ecosystem approach to building, which means we are prioritising tools and features which could sit within our CMS one day. When our value-add meets market demand, we are moving to productizing (like in the case of our URL-to-video tool). 

The URL-to-video tool is our main product; it set us off on this journey. It is a traffic tool for video production which converts a news article into a video file, optimised for 9:16 social media formats. It cuts production time of videos from several hours to under 5 minutes. We have optimised it for news and journalism standards. It is facts and accuracy-first (Our editor tests and fine-tunes the tool *everyday*).

In our current phase of development (closed beta), the tool is capable of accurate output in English, Hindi and German. We are currently testing for Gujarati, Marathi, Bengali, Malayalam, Kannada and French.

Our other tools in early development and POC stages are: a repository-linked image tagger, two LLM-based research tools to aid our investigative reporting, and a style-guide-based compliance checker and corrector. 

In your years of direct experience with the use of AI in the newsroom, what are some key lessons you have learnt?

There are so many lessons, but let me leave you with three:

Your output is going to be as good or bad as your input data; don’t expect magic. For example, if a model is largely trained on American news articles, one can’t expect nuances specific to journalism in India (which we take for granted) in the news copies we generate. Or that the word ‘president’ invariably throws up an image of Donald Trump or Joe Biden instead of the Indian president, Droupadi Murmu. For a small newsroom like ours (which can’t invest in building a tailor-made model), this becomes an extra hoop to jump through. (I would suggest using the Pareto principle to decide which hoops to jump through first: solving 20% of the problems will lead to achieving 80% of your expected results).

While transitioning to using generative AI in your news production workflow, the workload of your frontline staff carrying out real-world testing is going to increase significantly.  They need to be supported, empathised with, and trained. (Regular check-ins to understand and solve pain-points and being directly accessible when needed to quickly troubleshoot or debug is working well for us.)

A use-of-AI policy built by a diverse group of colleagues is very helpful (especially with the different vantage points different teams bring to the table). 

What advice would you give to an editor who would like to approach the world of AI but does not know how to navigate in this complex and multifaceted field?

With my current experience, I will only be able to speak about using generative AI for news production in a low-resource environment.

I would suggest starting with an important metric (not necessarily the north star metric) your organisation uses, or a problem (again, not necessarily the biggest one) you think needs to be solved in your news organisation, and auditing to see if AI can really help solve it. 

If the answer is yes, I have found that creating customGPTs on ChatGPT serves as good POCs to quickly test if an idea/solution is useful. Depending on your results, you can decide to invest resources or approach senior management to secure buy-in.

Another suggestion would be to foster friendship between editorial and engineering teams. We often speak ‘different’ languages, and A LOT of things get lost in translation. Not working in the usual silos and collaborating everyday has helped me greatly in the last 18 months while building our AI tools. 

Do you have experience in AI and journalism and would you like to tell a wide audience about it? Write to me for an interview on MyType!

Big opportunity!

Did the interview with Sannuta Raghu inspire you and would you like to learn more about how to integrate AI into your editorial work?

Contact our AI team or send me an email (sforni@atex.com) we can do it together!

There would be no 'digital joynalism' without sharing. If you like this newsletter, you could share it with colleagues, friends and family :)

Share MyType

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here. You can now also follow MyType on Linkedin, Instagram and Twitter.

Now, let's get started! 

Before leaving you to read the interview, I will share some extremely practical production notes that helped me a lot in the creation of this newsletter.

The interview took place online, on Zoom, a tool that provided the recording of the call in audio and video format. 
I used an AI transcription tool to obtain the raw transcript of the interview. 
The document had a number of inaccuracies due to the natural conversation between two people: i.e. interjections, repetitions and dialogue far removed from a simple repartee. 
I asked ChatGPT Plus to fix the interview by removing repeated words such as 'um', 'uh' and to format the document for a more comprehensible reading of the text.

This process from transcription to first formatting took:
• 1 minute for transcription
• 10 minutes of brainstorming on ChatGPT Plus

In 11 minutes I had a very good draft of the interview in front of me and I was relieved because, of all the activities I have always detested most in my work, transcription definitely wins first prize.

I spent another 25 minutes sorting out the interview to make it readable and another 10 to layout it on Substack. I also asked ChatGPT to suggest a SEO friendly summary to help me share the content. This saved me at least 15 minutes.

Interesting, isn't it? How do you use AI in your daily work?

I will now leave you to read this month's guest of the month, Jaemark Tordecilla, Nieman '24 Fellow at Harvard University, who has created a chatbot that could be very helful in investigative journalism.

Jaemark, thank you for accepting MyType's invitation. Before we get into the interview, tell us something about yourself.

Yes, sure! Right now I am a Nieman fellow at Harvard University. I'm doing my fellowship here. I didn't really intend to study AI directly, but I was just drawn to it because there have been many, you know, people purporting to be AI experts in the journalism field but all they talk about is the high-level stuff, and we're not seeing any solutions for actual problems in the newsroom. So, I figured there needed to be more people who are trying out solutions that journalists could solve.

Before telling your experience and your project, can you briefly describe the problem that you're trying to solve with your project?

Coming into this, there was this one particular pain point that I wanted to try to solve, which was parsing large volumes of documents and helping journalists try to get through them. In the Philippine context, there are these documents called audit reports, which are government audit reports of each agency and local government. Each reporter is tasked with going through this mountain of documents to figure out if there's a story there. And so they spend hours even just trying to figure out whether they have to dive deeper into the report. The problem is that, usually, people who cover the beat for this agency also cover other beats. So it's a big investment of time to find stories in these documents. But then there's also a payoff because sometimes there are significant anomalies that could be uncovered if you really find the right report and the right story from it. So, I wanted to do a test case for this kind of document about whether a GPT tool could help uncover that information from this type of document. I was in an introduction to AI class, and the professor told us that everything she was teaching us would be obsolete because ChatGPT had released a new feature called Custom GPTs that would allow you to build applications without any coding. So I tried it out, and then I've been thinking about the problem of the documents for a while trying to figure out what implementation I could use. I was thinking about machine learning and other tools. Then I thought about whether I could use Custom GPTs for it, and all in all, it took me maybe a couple of days, and I was able to develop a solution.

How many days you try and maybe what you try for, for became to the final solution?

It took me about 16 hours of work but only because it was my first time approaching this type of bot. In general, once you understand how it works in two to four hours you can create custom models on GPT.

What were the main technical problems you encountered during the development of your project?

First of all, you have to subscribe to ChatGPT Plus to be able to use custom bots to process documents. There are also limitations even if you use the paid version; you're limited to the number of queries you can make in a day, something like 40 questions every two hours, I think, or maybe less than that. I also noticed that ChatGPT has problems dealing with very large documents. So if you give it 100 pages, it's going to perform worse than if you gave it a 25-page document. I don't know the limit, but that's the observation I've had. I've shown it to other Filipino journalists, and they were asking me if we can use the bot to process multiple documents, like an audit report from this year and last year to get observations. I've tried it, and ChatGPT doesn't handle multiple documents well. So those are technical limitations. I mean, it’s possible to upload documents, but it's just the answer degrades because it's a problem elsewhere. I think once ChatGPT finds the answer in one of the documents, it won't process the other document anymore. But that's what I found so far.

Do you have experience in AI and journalism and would you like to tell a wide audience about it? Write to me for an interview on MyType!

What are the main challenges or lessons you learned from using this technology in your project?

Of course. The first is we need to play around with this technology to find how it's going to work for us.

And we have so many challenges, and we need all the help we can get. So think of AI as a tool, maybe like Excel or your word processor, to make your jobs easier. We need to figure out ways to help AI make our jobs easier. The second one is that there are tasks that are good for AI and that there are tasks that are not. And so what I found in this experience is that it's not going to replace our critical thinking. Generative AI it's good for summaries. And so it's going to be more important for journalists to develop that critical thinking facility because that's the value that they bring into the process. The writing maybe can be replaced a little bit by and AI Grammar Checking. And that might go away, but what won't go away is the nose for reporting of a good reporter, the nose for journalism. And so that's the important part.

What advice would you give to a journalist who wants to start studying this field as well?

I think that it's an exciting time to get into these technologies right now because there are no experts, except maybe the people who are developing chatbots directly or doing hardcore AI research. But in the journalism field, there are no experts. So there's an opportunity for people getting into it now to really learn how it works and to find use cases that fits in their own newsrooms. And to figure out, like I said earlier, how to use these technologies to make the lives of journalists easier. In the previous generation, we were behind a lot of the bad actors when it came to publishing on social media and using emerging platforms. And so we had a lot of problems with misinformation and losing our audiences to influencers. And so we can't afford to do that with this new generation of technology. We have to be good at this. Because if all the hype is true and this is going to transform not just our industry but every other industry, we need to be ahead of the curve and figure out how it's going to affect us, how it's going to help us, and what are we going to guard against? And it's particularly important because there's a lot of fear about these technologies and if you don't understand it, then how are you going to cover it as a journalist effectively? And so there's a lot of opportunity to develop expertise in every newsroom out there.

Big announcement!

We are very happy to present you with the new MyType website, which tells you all about the specifics of our innovative CMS!

We really like it but we are looking for feedback, let us know what you think!

There would be no 'digital joynalism' without sharing. If you like this newsletter you could share it with colleagues, friends and family :)

Share MyType

For any ideas, suggestions and thoughts on the subject, don't hesitate to email me at sforni@atex.com.

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here. You can now also follow MyType on Linkedin, Instagram and Twitter.

Now, let's get started! 

What does your newsroom need, for real? When we find ourselves designing digital (and other) solutions to be implemented in newsrooms, it happens that we want to implement something just because it is the trend of the moment. Generative AI is a prime example of this. It is even more evident in the field of journalism, where many functionalities are only amazing on paper while in practice they are of little use or performance. This is why the 'product design' approach is slowly entering journalism as well: thinking in terms of needs, not solutions.

We talked about this with Mattia Peretti, Learning Experience Designer & AI Consultant, who has given valuable advice, on artificial intelligence and much more, on how to approach the world of journalism 'tomorrow'.

Enjoy the reading!

2023 was marked by the boom of Generative Artificial Intelligence which, as expected, also characterized the journalism sector. In this particular field, opinions are divided: is it an opportunity or a threat?

The answer that never satisfies anyone is: both things. AI applied to journalism can represent both an opportunity and a threat. We don’t need to approach the issue as a football derby in which we need to support only one side. It’s important to accept that you must understand what the risks, limitations and possible consequences of use are. However, it would be equally useless to deny that there is a huge opportunity to be taken advantage of, in a responsible way.

There is a lot of talk about Generative AI but technological solutions cannot and must not be limited to this field. What would you advise an editorial team that wants to approach this world to do?

First of all, the fact that a thousand million things can be done with AI and technology should be accepted; therefore, it is important to shift the focus of the question from “What can I do?” to “What do I need to do?”. I often recommend not approaching your strategy by thinking “Wow, everyone does these wonderful things” or rather, “Everyone says they are doing these wonderful things”. It is a very dangerous point to start from because we risk wasting resources and attention on a thousand million things on which we are not going to create real value or from which we do not get what we expect. What I do in my consultancy job is to convince people to start from needs.

To go back to your question, opportunities are found throughout the news production process and therefore AI tools can be used to support the news gathering work, namely the research of news and, therefore, both the social media monitoring work and the ‘dirty’ work, i.e. using tools to analyze large amounts of data. Subsequently also to follow the whole production work, so at the level of content, research, editing and so on and then also at the level of distribution once the content is finished. Finishing up the cycle with monetization, so for example the development of dynamic paywalls with a lot of machine learning work to also seek value from a business point of view.

Very useful use cases could be applied to journalism, such as transcription, summary or translation which, however, precisely because of their simplicity are perceived as uninteresting or boring. So tell us about a couple of experiences that struck you.

I agree with you, those you listed are very useful features but are perceived as boring or now 'obvious' and within everyone's reach. Not to mislead your question, however, I think that the greatest opportunities are found in the news gathering part, especially in investigative journalism. We often find ourselves managing infinite amounts of data which means hours and hours spent sifting through documents that perhaps arrive in a roundabout way.  For example, it happened in a major case like that of the Panama Papers where a great deal of manual work was carried out to understand which parts were more interesting and relevant.

The second, which is my fixation in this period, is to abandon the idea that the journalist's job is to write the article and once written the work is done. Now we have huge opportunities to understand that our readers don't necessarily want to read the whole article. Maybe they are looking for an answer to a single question and that answer is enough for them, or they don't have time and in that little time they prefer to read ten paragraphs of ten different article rather than dedicating the same time to read one in depth. So, in this case, I'm talking about using Generative AI to create 'content packaging' work. Therefore, the articles are written in the same way, but one should no longer limit oneself to saying, "Ok my work is finished". Instead, one should also think that a summary can be generated from that article, taking out three bullet points to make it clearer and maybe change the format of the article depending on the target audience. All this formatting work is not particularly sexy but if it is accompanied by research and selection of what the needs of the audience or the target segment are, it can bring great value to the content, with positive consequences also on monetization.

Over the course of your career, you have (also) specialized in training courses, including online courses on AI and machine learning. If a journalist today could have the opportunity to train on just one topic, what should it be? Why?

I think there is an ever-increasing need for journalists to accept the fact that we are in an era where things are changing so quickly, both technologically and socially, that the need to keep up with the times it is more essential than ever. At the same time there is also a certain amount of pressure, because there are a lot of things to learn and little time to do it. We are no longer in the era in which, at least in anglosaxon journalism, it was said that all journalists had to learn to do a bit of coding or that everyone had to become excellent data journalists. Data understanding part is certainly important and necessary and, perhaps, this is the first answer I would give to your question. However, I don't think having technical skills is necessary for all journalists, I think it is more important to understand the dynamics by which the journalist's work is changing, which are not only technological but also linked, for example, to audience engagement. Another skill on which to train could be the ability to create community engagement; it’s fundamental to learn to develop a relationship with readers from the moment after the content is published. In that part we need to do extra training and understand that the publishing part of the content is almost the beginning of its in digital ‘life’, no longer the end of the work we do on that article.

A few days ago you published a post on Linkedin in which you expressed your intention to start mentoring younger people who are building their careers in media and journalism. Start by answering this question.

Choose three key pieces of advice for a young journalist who wants to start a career in journalism today.

There are many I could say, but I will choose the three most important.

The first is that working in journalism does not simply mean 'being journalists' and writing. You shouldn't think that to do this job you only have to be a writer or anchorman, but there is a myriad of roles that could be even more interesting for some people. It is necessary to have the curiosity to discover these roles and perhaps understand that it can be very interesting to work in journalism also as a product editor or audience engagement editor, for example.

The second piece of advice concerns entering the work market. Over time I understood that the best jobs are not found among job offers. I would really encourage anyone looking to break into this industry to participate in online groups and communities where you can meet others and find inspiration. It is essential to let yourself be carried away by curiosity, participate in events and meetings, online and not. Be careful, it shouldn't be done just for networking but with the idea of ​​being inspired and contaminated.

Another useful element is to create an online image through social networks where we can talk about the interesting things we have discovered and learned from these meetings, from the readings and studies we do every day. From all of these, many interesting things could arise.

From personal experience, good things come if you have this positive outlook towards the world of work and, thank goodness, I see that this is more and more common among the younger generations.

A series of readings suggested by Mattia Peretti:

• AI kills the one-size-fits-all model

• An AI Haunted World

• AI and News: What’s next?

• Generative AI exists because of the transformer

• Which rights do AI and journalists have in common?

• Get Ready for the Great AI Disappointment

There would be no 'digital joynalism' without sharing. If you like this newsletter you could share it with colleagues, friends and family :)

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Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here. You can now also follow MyType on Linkedin, Instagram and Twitter.

Now, let's get started! 

New year, new format!

Starting with this issue, MyType newsletter will feature interviews with experts in Artificial Intelligence related to journalism and the world of communication.

We open this cycle with an interview with Hannes Cools, Assistant Professor in 'Human Factor in New Technologies' at the University of Amsterdam. Enjoy your reading!

The subtitle of this newsletter is: AI and journalism, opportunity, or threat? To answer this question, we decided to ask experts in the field. So, what is the first answer you would give to this question?

Well, I think they are both right. If you're familiar with Noam Chomsky maybe you know he said that ‘technology is usually fairly neutral. It's like a hammer’. It can be both used to put something in the wall, but you could also use it to murder someone. Technology is a tool in that regard, and it can well be used to your benefits, but also to your disadvantage.

On the opportunity side, there are a lot of quick wins. For example, there are a lot of specific processes, like transcription, summarization and other similar ones, that can be helpful. So, it is mostly about efficiency.

However, in some cases it can also be seen as a threat.
I specifically see three challenges for journalism. One is the lack of AI literacy. Journalists sometimes don't know what specific technologies can do, but also what they cannot do and that helps to demystify these technologies.

The other one is authenticity. It is a challenge in the sense that now with very few resources, you can just generate newspaper articles, or you can also generate images. Now, for example, with Google Gemini, which will be released as of next year, you can even generate a text and then a video in just a matter of clicks. I think that is a real challenge for journalism because we will no longer have the monopoly of having the “true facts”. And it's also increasingly hard, I think, to verify if an image is real or not.

Lastly, the third one is about the content paradox. This goes back to what I said that it's easier to write an article but without having a lot of knowledge. So, as a news organization, you can reach the point of generating a lot of articles and personalizing them a lot, but this doesn't necessarily mean there's value in them and that the audiences you're now reaching are interested in them. Overall, I see more challenges, I would say, than opportunities. But there are, of course, also a lot of opportunities.

What are some best practices that newsroom and the technology companies should adopt to implement their conscious use of AI in the newsrooms?

It's quite a hard question. Best practices go back to what I said about the lack of AI literacy, they are not organizing workshops, or even having discussions on these technologies.

I gave a training to journalists, and you would think that they would have already tried or experimented with, for example, ChatGPT but they had not, and they still needed to make an account. They were also a bit fearful of the technology and these kinds of things. Sometimes that OpenAI and other tech companies are also quite vocal about the limitations of these technologies. This also helps to well spark a discussion not only in newsrooms but outside as well.

What evolution do you envision in the relationship between AI and journalism in the short, medium, and long term?

I think that looking into the future is very hard. But of course, there are some things that I'm seeing at the horizon that reflect the future path and impact of AI, more in the long term, specifically for journalists.
I think what will become more important is what I've called in my PhD ‘shared decision making’. In fact, technology will become more well autonomous in helping people while these people will still oversight so to have more automation than there is right now. But these technologies are getting more in charge of decisions than us on a daily basis.

Another important aspect of possible future impact and how it will also affect journalism is regulation. The AI Act that is now still being negotiated, they are saying that if you are using AI and GenAI, you should be explicit to your audience. So that will also influence a potential impact of AI on journalism. It also depends in what way the technology will evolve. Now you see GPT-4 is implemented. It took almost two years to train GPT-3, then it took almost two years to train GPT-4. I'm not sure when GPT-5 will arrive, that could be in two years or could maybe be sooner or way later. Therefore, I think this kind of aspects will also determine how it will further impact journalism. Of course, right now you are seeing the European Union being really keen on imposing guardrails, but the specificity of these guardrails also have a huge impact.

I know one example that actually happened in Belgium: a journalist who used ChatGPT in a newspaper article and there were more than five factual errors in that article. It was about someone who died, an ‘in memoriam’ article. The children of the person contacted the newspaper saying there were a lot of factual errors in there. However, when the next day the article was published, there was a correction in the physical newspaper but there wasn't any word on the fact that ChatGPT was used. In that sense, I believe that whole framework of how well ChatGPT or, even broader, just generative AI tools in general are being implemented in newsrooms is very important. Some of the guidelines that a lot of these news organizations have put forward are very explicit; others less so.

Hence, I think that the impact of AI will also depend on how well the use of AI will or will not flourish in that sense, especially depending on these guardrails.

In your experience, what are the main case studies that you are working on or maybe studied with the news organization?

First one, some days ago, I wrapped up research at the BBC. They're working on personalization. So not so much on generative AI, but they were more working on news recommender systems and using AI to personalize content for specific users. At BBC, they have a platform, the iPlayer. Is a sort of Netflix but for the public broadcaster and what they want to do is to move all their content in there. They want to combine it now with the news component. The news component is of course very specific in that sense that it needs to be diverse.  So, there is a very specific way of personalizing content in that iPlayer and I'm looking at how the editorial values fit into the algorithm since the algorithm is being well trained by engineers who do not 'speak journalism’. And then there are the journalists who step in for a second check to verify if the content is diverse enough, if it is in line with BBC values. And it is like this two-step process where editorial tries to influence decisions that then affect the recommendations system and vice versa. This is done through observations and interviews and now I'm looking at how they are negotiating that recommended system.

Another case study that I did was with a Danish news organization. That case study was more on the perception of AI because that specific news organization was not really working, and still isn’t, working with AI. They are a more so “conservative” news organization in Copenhagen as well as one of the oldest newspapers in the world. And they were very interested in looking into where they should invest resources to implement AI. Therefore, that was more investigating perceptions, maybe also demystifying the technology. Those are two case studies that I've been working on.

That's all for this year! See you there.

There would be no 'digital joynalism' without sharing. If you like this newsletter you could share it with colleagues, friends and family :)

Share MyType

For any ideas, suggestions and thoughts on the subject, don't hesitate to email me at sforni@atex.com.

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

Every fortnight we will explore a topic related to this evolving field to discover the pleasure to do journalism without repeating boring tasks and using technology as a helper, not a substitute. That's what we like to call ‘digital joynalism’.

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here. You can now also follow MyType on Linkedin, Instagram and Twitter.

Now, let's get started! 

It is undeniable: 2023 has indeed been an eventful year for 'things concerning journalism' and for the future of the industry. In fact, many things we will go through together today will inevitably mark 2024 and the years to come.

Here, then, is a (non-exhaustive) list of some key things that happened in journalism in 2023:

Google Search could change forever. Or maybe not.

Artificial intelligence is set to revolutionize online search, with Google being the first to adopt hybrid solutions. These hybrid solutions combine the search engine's relevance, quality, and authoritativeness with a language model that amalgamates information into user-friendly answers. Other conversational search engines, such as Perplexity.ai, You.com, and Neeva AI, are also gaining popularity.

Some argue that Generative AI, particularly tools like ChatGPT, could lead to the death of traditional online searches and the end of web page visits to news outlets. However, it remains unclear how search patterns will change. Publishers will need to rethink their business models and how to monetize clicks on their pages.

Publishers have been trying to adapt to the AI age by making deals with tech companies.

Big publishers have been finding it difficult to adjust to this impending change. Axel Springer and AP's partnership with OpenAI are two examples of the agreements that some have struck with AI startups.

Others have created their own AI language model, like BloombergGPT for financial news, to make use of their archives. There will undoubtedly be more announcements in 2024.

The New York Times sued OpenAI and Microsoft for using their content to drive AI models. This could have big consequences in the market

Year-end bombshell: The New York Times sued OpenAI and Microsoft for using “millions” of articles to train chatbots like ChatGPT, without permission.

The NYT calls this a "free-ride" on their journalism. But OpenAI and Microsoft claim it is “fair use”. The NYT, however, does not go along with this and has pointed out instances of 'hallucinations' in which ChatGPT allegedly misrepresented information from the US newspaper.

The NYT is demanding a compensation, to be quantified in “billions of dollars”, as well as a demand to destroy all chatbot models that are also based on their content. This news could rewrite copyright and AI legislation. Updates will follow.

The New York Times passes ten million paid subscribers.

In between lawsuits, the New York Times has found a way to reach no less than 10 million subscribers. Something truly unthinkable considering the current state of health of publishing.

The New York Times's profitable subscription model and astute investment in non-news offerings are the main reasons for its current state of prosperity.

Despite having its headquarters in the US, NYT has grown over the years to become one of the largest news publishers in Europe, matching some of the largest European publications in terms of staffing and reach.

The role of the ‘AI editor’ is born

2023 was the year that saw a proliferation of searches for AI editors within newsrooms. Figures such as these are key because they play a dual role: on the one hand, they help and advise the rest of the editorial staff on the main trends to follow and can support the product teams in the development of new use cases; on the other hand, they contribute to that feeling of greater 'solidity' of the editorial offices towards the readers.

News organisations have been leaving Twitter and experimenting with new platforms as social traffic declined

The evolution of Twitter into X merits a dedicated chapter in the annals of 2023 history. While it's not quite gone and is still a significant forum for discussions about news, Elon Musk's direction has caused it to decline. Several influential editors have quit, either because their readership has decreased or in opposition to Musk's actions.

However, the fake news control system could become an interesting method of 'controlling' the work of the newspapers themselves.

As social platforms have deprioritised news partnerships, publishers’ social traffic has dropped. “Traffic referrals to the top global news sites from Meta’s Facebook and X, formerly Twitter, has collapsed over the past year, according to data from Similarweb”, Axios reported in October.

While news firms have experimented with other channels such as WhatsApp and Threads, they are by no means replacing Twitter in its former position.

TikTok's exponential growth also for news brands

As Facebook withdraws from the news space, publishers are focusing more and more on Tiktok. About half of the top news publishers in more than 40 countries consistently uploaded content to the Chinese-owned video platform, according to research conducted last year by the Reuters Institute for the Study of Journalism (RISJ).

With 13.1 million followers, youth focused Ladbible held the title of largest publisher on Tiktok as of December 17. Daily Mail, which had a sharp rise in its readership from 4.5 million in December of last year to 7.5 million this year, came next.

AI is forcing us to revise editorial guidelines. But will readers really like this?

An overwhelming majority of readers would like news publishers to tell them when AI has shaped the news coverage they’re seeing. Also for this reason, many editors have rewritten their editorial guidelines, specifying when and where (images, text parts, summaries, translations) Artificial Intelligence was used. But, new research finds, news outlets pay a price when they disclose using generative AI.

As Nieman Lab reports in a long article, that’s the conundrum at the heart of new research from University of Minnesota’s Benjamin Toff and Oxford Internet Institute’s Felix M. Simon. Their working paper “‘Or they could just not use it?’: The paradox of AI disclosure for audience trust in news” is one of the first experiments to examine audience perceptions of AI-generated news.

More than three-quarters of U.S. adults think news articles written by AI would be “a bad thing.”

That's all for this year! See you there.

There would be no 'digital joynalism' without sharing. If you like this newsletter you could share it with colleagues, friends and family :)

Share MyType

For any ideas, suggestions and thoughts on the subject, don't hesitate to email me at sforni@atex.com.

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

Every fortnight we will explore a topic related to this evolving field to discover the pleasure to do journalism without repeating boring tasks and using technology as a helper, not a substitute. That's what we like to call ‘digital joynalism’.

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here. You can now also follow MyType on Linkedin, Instagram and Twitter.

Now, let's get started! 

Welcome back!

It has been a few days since I last wrote here, but it’s been for a good reason.

As of last week, in fact, MyType is no longer just a newsletter, but it has become a brand, complete with its own dedicated website and social network. As a brand, our goal is to spread the culture of 'digital joynalism' a concept-value we have introduced and described in our Manifesto (by the way, we would love to know what you think about it!).

Read the full Manifesto

A CMS designed by journalists for journalists

On our website you can also book a demo to discover our first product: an all-in-one CMS that, among other things, has some built-in generative artificial intelligence features. This is not just a simple writing editor; rather, those who choose MyType CMS will have a tool that will accompany them along the entire news creation journey. From news gathering to production, distribution and finally monetization.

Will AI be our best colleague?

Returning to content and interesting experiences, on Thursday afternoon I had the pleasure of attending the event 'The Reality Factory - Journalism and Information in the Age of Generative AI' in Rome, organized by ANSA, the leading news agency in Italy and one of the most important internationally.

Some lessons learnt 💡

• To deal with Generative AI and all the associated challenges, we will need the courage to overcome the so-called 'technology bias' which is the human tendency to passively accept the results produced by technology (e.g., we don't re-do the math to verify what the calculator says). As Mariarosaria Taddeo, professor of Digital Ethics and Defence Technologies at the Oxford Internet Institute, has well explained, the challenge with Gen AI will be to question what technology produces continuously and critically, to control it and at the same time improve it.

• There is a need for journalism to take courage and become a protagonist in the process, rather than undergo it. How? Through transparency on content production. As Carlo Bartoli, president of the Order of Journalists in Italy, has well described, when I buy a bottle of milk at the supermarket, I demand that it shows provenance, type and nutritional values. Likewise, a news story should show the same degree of detail, specifying what procedures the journalist employed to write that article. Including, of course, the use of Generative AI.

• As it always emerges in meetings where artificial intelligence and journalism are discussed, it is undeniable that Generative AI now is perceived as both a threat and an opportunity. It will therefore be up to newsrooms to learn how to govern the technology without being replaced by it.

• To make the points above a reality, it will be crucial to invest in massive and ongoing training of individual journalists and newsrooms.

Stories & Tools 

• Telegraph journalists told use of ChatGPT will result in same sanctions as plagiarism

• The JournalismAI festival will be held on December 5 and 6. And it is free.

• AI Adoption for Newsrooms: A 10-Step Guide

• The future of journalism is radical collaboration

• The easiest way to transcribe your lengthy interviews

That's all for today!

There would be no 'digital joynalism' without sharing. If you like this newsletter you could share it with colleagues, friends and family :)

Share MyType

For any ideas, suggestions and thoughts on the subject, don't hesitate to email me at sforni@atex.com.

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

Every fortnight we will explore a topic related to this evolving field to discover the pleasure to do journalism without repeating boring tasks and using technology as a helper, not a substitute. That's what we like to call ‘digital joynalism’.

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here.

Now, let's get started! 

ChatGPT can now also surf the big world of internet. A few weeks ago, OpenAI announced that the chatbot will be able to provide users with relevant and up-to-date answers in real time. The new capability of the system is the result of a function called 'Browse with Bing'. This is a browser plug-in that allows ChatGPT to connect to the Internet via Microsoft's search engine API.

The function is currently available for the desktop version of ChatGPT and for the iOS and Android versions of the system. To try it out, you need to be a ChatGPT Plus or Enterprise subscriber. However, the company led by Sam Altman has assured users that the new feature will soon be available to everyone. In this way, OpenAI bridges the gap it had until now with Bard, Google's conversational chatbot that is able to provide answers in real time using Google Search and Perplexity AI.

Increased concern and excitement

While this news has aroused a great deal of curiosity among users, it has also increased concerns on the part of editors and editorial staff, who now see more clearly the threat of these great generative models of 'learning' and improving themselves by assimilating all published articles, past, present and future.

There are two main consequences this may have for editorial offices:

1.        Aggravating ‘zero click searches’ trend

2.        Nobody pays for this content

Goodbye direct traffic to the website

With the update, users will be able to ask ChatGPT questions about current events, and the replies will probably be based on articles from news organizations around the world, who will lose out on traffic if individuals can get the information, they need without ever visiting the original source. It may turn out to be a continuation of the trend in "zero click searches” in which search engine results pages provide users with the information they want without requiring them to click through to articles that may have provided the information in the first place. However, OpenAI also promised to provide “direct links to sources”.

“Search was designed to find the best of the internet”, explained Joey Levin, CEO of US media giant IAC interviewed by Semafor: “These large language models, or generative AI, are designed to steal the best of the internet.”

As Semafor report, that nightmare scenario, for Levin, would turn a Food & Wine review into a simple text recommendation of a bottle of Malbec, without attribution.

“The machine doesn’t drink any wine or swirl any wine or smell any wine”, Levin said.

Nobody pays for this content

The second problem is that large technology companies are not paying newsrooms for scraping content, which is why the news industry is starting to organise itself to stop this 'robbery'. “No one is generating any traffic from allowing it currently, so why let them take it for free with nothing in return?”, says Chris Dicker, a board member for the UK’s Independent Publishers Alliance.

If publishers take no action, their content will continue to be used as sources for Bing Chat and other chatbot. Content tagged NOCACHE “may” be included in Bing Chat answers but only URLs, snippets and titles would be displayed and used in training the model. Content tagged NOARCHIVE will not be included, linked to, or used for training purposes.

Initially, Google has created Google-Extended, a tool for publishers to be able to control access to content on their sites and decide whether they “help improve” Google Bard, its AI-driven chat tool, or not. But a few days ago, Search Engine Land has reported that Google-Extended does not stop Google’s new AI-generated answers in search results pages from using publishers’ content even if they believe they have opted out from all of its AI products.

Will the (real) solution be to block content?

As we said, the UK’s Independent Publishers Alliance and more other newsrooms all over the world are running to block crawling access for OpenAI and Google as soon as possible.

Since August, 47,3% of 1,149 news publishers monitored in a continual survey by open-source archiving system homepages.news have blocked out of ChatGPT’s trawls using robots.txt – the code that tells trawlers what parts of a website they are allowed to access. 45.9% of these blocked OpenAI.

However, not everyone agrees. Sajeeda Merali, chief executive of the Professional Publishers Association, told Press Gazette in August there are disadvantages to opting out.

“[If] ChatGPT is to continue to grow and become an entry point for digital information in the same way that Google search is at the moment then opt-out isn’t really a viable option” she said.

And what do you think about this? Click on the button below to tell us!

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Stories & Tools 

• Canva presents a series of AI powered 'magic' tools

• Authors shocked to find AI ripoffs of their books being sold on Amazon

• What is Deutsche Welle's approach to generative AI?

• How genAI summaries are boosting Daily Maverick’s readership

That's all for today!

There would be no 'digital joynalism' without sharing. If you like this newsletter you could share it with colleagues, friends and family :)

Share MyType

For any ideas, suggestions and thoughts on the subject, don't hesitate to email me at sforni@atex.com!  

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

Every fortnight we will explore a topic related to this evolving field to discover the pleasure to do journalism without repeating boring tasks and using technology as a helper, not a substitute. That's what we like to call ‘digital joynalism’.

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here.

Now, let's get started! 

Today, we’re diving headfirst into a topic that is as controversial as it is transformative - the role of AI in journalism. To do so, I analysed 'Generating Change', a global survey of what news organisations are doing with artificial intelligence made by Charlie Beckett and Mira Yaseen from LSE and JournalismAI Lab.  

The report is based on a survey of 105 news and media organisations from 46 different countries regarding AI and associated technologies. In my analysis, I decided to focus on both the opportunities and the difficulties that newsrooms are facing and will face in integrating AI into their daily work. In the future, I also want to explore the global disparity in AI development and adoption. Here you can find the full report in English and Spanish.  

Before we begin, it is crucial to emphasise that GenAI is the fastest growing technology in media in today’s digital age. The presence of intense dystopian criticisms and exaggerated marketing buzz has overshadowed essential discussions about current issues. Fortunately, a broader awareness and direct engagement with AI now exists, allowing us to thoroughly examine its strengths and weaknesses. 

How AI is being used in journalism today?

In the dynamic intersection of technology and journalism, three core areas stand out:  

1. News gathering 

2. News production 

3. News distribution 

Nearly 75% of organisations interviewed harness AI tools for news gathering, utilising innovations like Optical Character Recognition (OCR) and Speech-to-Text to automate transcription and extract text from images. These tools are instrumental in structuring data post-collection and are complemented by AI applications dedicated to trend detection and news discovery. Such applications, rooted in sophisticated data mining techniques, sift through vast data volumes to identify patterns, offering invaluable insights.  

In the realm of news production, fact-checking chatbots and factual claim-checking algorithms exemplify the integration of AI, enhancing accuracy and credibility.  

The final piece of this intricate puzzle lies in news distribution, where AI-driven SEO tools take centre stage. By amplifying content visibility in searches, these tools not only elevate newsrooms' discoverability but also offer insights into audience preferences, paving the way for tailored and audience-centric content delivery. 

The importance of developing an AI strategy 

The integration of AI in newsrooms is becoming increasingly prevalent, but a strategic approach to its adoption is often lacking. While AI technologies are being employed diversely across media production processes, the survey’s results indicate that many newsrooms lack a formalised AI strategy, attributed to constrained resources and other competing priorities rather than a lack of interest.  

The approaches that do exist are often tailored to specific organisational needs and are evolving to meet the challenges posed by generative AI technologies. Despite this, about a quarter of surveyed newsrooms have reported significant benefits from AI integration, including cost reduction, enhanced efficiency, and streamlined processes in areas like fact-checking, social media monitoring, content distribution, and accounting. These developments underscore the need for more structured strategies to fully harness AI’s potential while ensuring adaptability to the rapidly changing technological landscape. 

The role of technology companies  

A considerable number of respondents called for increased openness from technology companies regarding the data utilisation and system design processes. There is a collective hope for these companies to take a more hands-on approach in educating journalists about AI tools. Collaboration between tech firms, civil society, media and government is viewed as essential to guarantee that technological advancements are coordinated with human-centred values. 

“The worst problem is the monopoly, the absence of control, the black boxes and the fact that they develop tools and technologies that they want us to use without first asking if we want them or how we want them” one respondent answered. 

Also, for this reason, almost 43% of responses emphasised the importance of training journalists and other personnel in AI literacy skills and technologies.  

Human in the loop approach 

Most respondents, over 60%, voiced concerns regarding the ethical dimensions of incorporating AI into journalism. There is a pronounced apprehension about maintaining the pillars of editorial quality, including accuracy, fairness, accountability, and transparency, in the era of AI. Journalists are grappling with the challenge of seamlessly blending AI technologies into the journalistic landscape while ensuring these core values remain uncompromised and integral to the profession. The quest for a balanced integration that enhances efficiency without eroding ethical standards is at the forefront of the conversation.

Feedback indicates that establishing and enforcing ethical standards for the integration of AI emerges as a complex and time-consuming challenge for media entities. The intricacy involved in aligning AI adoption with ethical norms is a significant hurdle for these organisations. 

Stories & Tools 

• Can AI help local newsrooms streamline their newsletters?

• Why Human Writing Is Worth Defending In the Age of ChatGPT

• Perhaps the best transcription tool

• How the BBC fact-checks celebrity deaths

• On Spotify you can listen to all podcasts in your own language, thanks to AI

That's all for today!

There would be no 'digital joynalism' without sharing. We don't want this channel to be a one-way street. So for any ideas, suggestions and thoughts on the subject, don't hesitate to email me at sforni@atex.com!  

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

Every fortnight we will explore a topic related to this evolving field to discover the pleasure to do journalism without repeating boring tasks and using technology as a helper, not a substitute. That's what we like to call ‘digital joynalism’.

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here.

Now, let's get started! 

AI for a more inclusive language 

After days of research, hours of phone calls and interviews around town you are finally ready to publish your article. You feel like you have checked everything; yet you might get a notification reminding you that “in this article there are eight men's names and only two women’s”. Or “out of ten photos in the gallery, only two represent female faces”. If this happens, it is very likely that your editorial team has implemented FT Diversify, a new AI-powered tool that helps publishers create balanced and inclusive content to increase audience engagement and unlock new commercial opportunities. 

The aim of Financial Times Strategies, which presented this tool at Press Gazette's Future of Media Technology conference last week, is to provide a tool for publishers review whether content is inclusive of under-represented audiences. Having this tool will allow newsrooms to increase their 'gender' audience by attracting females, using more inclusive language, and promoting engaging topics and formats.

It offers practical information on how people are interacting with your content and makes recommendations for boosting reach and engagement. 

FT Diversify will be available soon, but at the London event, many insiders held up their phones to frame the QR Code that allows them to sign up for the tool's waiting list. Interest was certainly high.  

Pitfalls are inevitable, but this is a starting point 

The tool analyses text and images to discover whether men and women are being represented equally — a laudable aim, but grey areas remain. For example, how will male actors be classified if they wear a wig or a long dress for entertainment purposes? 

This development made me think about how important it is to always remember to think out of the box, especially when approaching the field of artificial intelligence, where there is so much competition. For 100 people who will ask you to provide top-quality summaries, there will always be more complex and elaborate use cases - like FT Diversity - to reason about. And reasoning will not be enough, continuous testing and reiteration will be necessary to achieve an optimal result.

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Using AI as an assistant 

We at Atex also spoke about our approach to artificial intelligence on stage at the conference organised by Press Gazette, of which we were sponsors. Cesare Navarotto, our Chief Product Officer, told during the “Newsroom productivity - can technology help you do more with less?” session, how we will transform our CMS by integrating artificial intelligence tools.  

Journalists are already using AI-powered tools in a pervasive way: just think of tools for transcription of videos and audios, or translation services, or generative tools such as ChatGPT used for example for quickly producing articles drafts or summaries.   

Microsoft Office, to mention just one, is already incorporating an AI-powered digital assistant and they are constantly releasing new features: editors will expect at least the same level of functionality from their CMSs.  

Yes, but how? 

In our opinion vendors like us can make the difference in the following ways:  

• Product integration: we can directly enhance our products with AI-powered features so that editors won’t need to access external tools to get the help they need.   

• One stop shop: we take care of selecting and integrating the best AI providers for each use case, potentially replacing them behind the scenes in a completely transparent way. Services/add-ons would be activated on top of our existing contracts, no need for the publisher to select and certify a new vendor.  

• Access to publisher’s data: this is probably the most important point. With the publishers’ consent, we can use the content archive in the CMS to fine tune the AI model using prompt engineering techniques so that it generates content in line with the style of the publisher. 

Stories & Tools 

• Six media events to attend in the autumn of 2023

• An incredible (and very simple) article from Financial Times shows how Generative AI works

• Some tips from the author of AP guidelines on how to cover AI

• AI Startup Midjourney Expects $200 Million in Revenue

• Should I give AI a job in my newsroom?

That's all for today!

There would be no 'digital joynalism' without sharing. We don't want this channel to be a one-way street. So for any ideas, suggestions and thoughts on the subject, don't hesitate to email me at sforni@atex.com!  

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

Every fortnight we will explore a topic related to this evolving field to discover the pleasure to do journalism without repeating boring tasks and using technology as a helper, not a substitute. That's what we like to call ‘digital joynalism’.

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here.

Now, let's get started! 

Let's start by setting things straight: artificial intelligence has and will change the way we search for information on online search engines, Google first. In fact, in the coming years, increasingly online search will evolve in hybrid solutions, the result of the union of the search engine (which selects the best results based on relevance, quality and the authoritativeness and reliability of the source) and a language model (which amalgamates information into answers for the user). 

Therefore, there are those who say that Generative AI and in particular tools like ChatGPT represent the death of online searches as we have known them to date. This could also mean the end of web page visits to news outlets, but will this really be the fate that awaits us? 

The 'new' search engines 

Concerns grew when, in May, Google unveiled its Supercharging Search, i.e. a version of its search engine enhanced with generative AI that will provide 'conversational' answers and no longer (not only) a list of pages sorted according to SEO criteria and the PageRank algorithm.   

Let's take for example a question like: "What are the best music festivals in Europe for folk music lovers?". Normally we would get a list of pages to visit to search for the answer by dividing the various information into those more or less relevant to our question. Or we could read the article from our favourite newspaper, which may have overlooked certain details for the sake of brevity. With the new search engine, all this discovery and reading activity will be processed directly by the search engine's AI, which will provide a discursive answer based on a pre-selection of answers. It is not yet clear how the pre-selection will take place. Some words will be highlighted so that users can click on them and go deeper, but if they wish, the answer could be limited to the result suggested by Google.   

Of course, it is not just Google. Microsoft has also integrated Bing, which works in the same way. The same direction is taken by other conversational search engines that are gaining some visibility these days, such as Perplexity.ai, You.com and Neeva AI, which have in fact presented hybrid solutions (search engine and language model).   

How will this impact on publishers?  

Publishers are expressing concern about this way of browsing results, mainly because they fear that users will have less and less need to continue their in-depth study by clicking on a result. Incidentally, this concern about a change in SEO has been alive for some years now.   

In fact, the same thoughts have already emerged in the past regarding the amount of information directly present in SERPs when performing a search, and it has reached its peak with the "Pay Per Position" service that allows websites to be placed in the top spots of the search engine regardless of page structure and content. 

Again, successful content production, which in this case will be measured by the number of times that content is used to generate a 'discursive' response to the user's question, will depend solely on the quality of the information. And it is the same difference that in recent years has favoured relevant and information-rich content over hundreds of 'little articles' written only by complying with some SEO rules and that have contributed to polluting the proliferation of content with irrelevant information written 'for The Search Engines' and not for the end users and readers. Google itself in drafting its guidelines on the use of artificial intelligence to produce text for the web, puts the focus on an extremely specific concept: 'Rewarding quality content, regardless of how it is made.'   

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Hallucination problems

A recurring theme in the field of Generative Artificial Intelligence are the hallucinations that characterise current language models. The risk here too is that the answers provided by the search engine may be correct in form but based on concepts that deviate from reality. And it is not clear how this information is selected. 

Will we overcome the problem of hallucinations? Of course, we will, but the important thing will be timing. The longer it takes for this to happen, the higher the risk of completely losing user trust and credibility is.

Stories & Tools 

• Germany plans to double AI funding in race with China, U.S.

• New Associated Press guidelines on AI (updated August 2023)

• Four CMS Platforms That Have AI Baked In

• Want to know what the future of journalism and AI will be? Join this community!

Big announcement!

Are you ready to unlock the secrets to thriving in the digital age of media? Look no further than the Future of Media Technology Conference 2023 – a one-day masterclass designed exclusively for media industry decision-makers.

Join Atex team in London for a transformative experience as we dive into strategies, solutions, and groundbreaking ideas tailored to empower you in the digital era.

That's all for today!

There would be no 'digital joynalism' without sharing. We don't want this channel to be a one-way street. So for any ideas, suggestions and thoughts on the subject, don't hesitate to email me at sforni@atex.com!  

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

Every fortnight we will explore a topic related to this evolving field to discover the pleasure to do journalism without repeating boring tasks and using technology as a helper, not a substitute. That's what we like to call ‘digital joynalism’.

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here.

Now, let's get started! 

Everyone is talking about us

Don't worry, this is not a self-praising newsletter introduction to this, but rather a general consideration on the relationship between the media and artificial intelligence.

In less than two weeks there have been at least three striking announcements concerning journalism, and that is not to be undermined considering that, it’s usually more of a niche topic rather than a mainstream one.

Something is starting to change. One must be careful, however, to watch the direction things will take as at the moment everything is still superficial and the debate on this issue is still at an early stage. In fact, it’s not uncommon to read alarming headlines about how AI will take over, “writing  articles instead of journalists” when, actually, efforts should be concentrated on developing functions and tools that will simplify, speed up and improve the journalist’s daily effort.

OpenAI flirts with newsrooms

The first announcement was from the Associated Press. The American news agent announced a collaboration with OpenAI, the well-known founder of ChatGPT and other language models. AP will license part of its journalistic archive to OpenAI,  in return gaining access to OpenAI's technology and expertise. Both organisations will benefit from the sharing of their different expertise. Also, as Associated Press wrote in a press release:

But OpenAI hasn’t stopped stop there. A few days later they announced another collaboration, this time with the American Journalism Project (AJP), a leading venture philanthropy working to rebuild local news, which will receive $5 million in OpenAI API credits “to help its grantee organizations assess and deploy emerging AI technologies within their organizations”, announced the company led by Sam Altman.

Even Google gets in on it

Imagine you have an idea to help a colleague and while you're explaining it to them , you directly do all the work for them. That’s about how the meetings must’ve gone between Google, The Washington Post, The Wall Street Journal and The New York Times, who met BigG last Wednesday to discover 'Genesis'. According to The New York Times, Google's new tool can ingest "details of current events" and other information to "generate news copy".

Google's intentions are undoubtedly good – otherwise I don't think they would present such an innovation to the major American newspapers - but their approach is problematic, as it only fuels the fears described above.  

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Finding Newsworthy Documents using Generative AI

Suddenly,  technology starts scanning newsworthy information, documents and events and when it finds everything, it immediately sends you a notification. Would be useful wouldn’t it? The Associated Press has been using a tool developed by SAM (a Canadian social media solutions company) for a few years now, to detect newsworthy events based on natural language processing (NLP) of text-based chatter on Twitter and other social media venues.

SAM alerts expose breaking news events sooner than human journalists could track on their own through manual monitoring of social media. This technology could speed up the discovery of news items and also their publication. Of course, stories still need journalists to be revised and have their fact checked, but having this service available would be very useful.

However  there are also those who have gone further. Professor and media expert Nick Diakolopolous, in a post blog on Generative AI in the Newsroom explained how to use AI to rate the newsworthiness of scientific abstracts in the Newsroom project, a case study published on the arXiv pre-print server, authoritative portal for free distribution of scientific articles. In particular, Diakolopolous paid two professional sci/tech journalists to rate 55 documents on a newsworthiness scale from 1 to 5. Then, he did the same with AI, applying three specific prompts to OpenAI's Gpt 3 and Gpt 3.5 turbo language models. The final result is not a complete victory but it is a starting point.

The right time context and biases

At the same time, there are things that can still be perfectionalized. One is the temporal context. As we know, these models are not trained on up-to-date information on current events topical information. For example, a scientific paper that talks about the latest news on COVID-19 won‘t have a different degree of newsworthiness for AI, simply because it was trained with information up to 2021. The second reason is related to the human biases that we are unknowingly transferring to AI models. Try to think about it, even if we think a news article  is as close to the facts as possible, how often are we led to give weight to specific information that one of our colleagues has not even considered? Experimentation in this regard could continue. One method to avoid these distortions could be to add the editorial line of the editorial office we are writing for, to the prompt. In this way, the model could become more sensitive to what we consider to be news and what not.

Stories & Tools 

• AI ran all the programming on a Swiss radio station for an entire day

• Wix will soon let you create an entire website using only AI prompts.

• Meta, Google, and OpenAI promise the White House they’ll develop AI responsibly

• Watch the 50+ sessions of the JournalismAI Festival on YouTube

• A list of AI tools to detect disinformation

That's all for today!

There would be no 'digital joynalism' without sharing. We don't want this channel to be a one-way street. So for any ideas, suggestions and thoughts on the subject, don't hesitate to email me at sforni@atex.com!  

Have a good weekend,   

Sara   

My name is Sara Forni, AI Product Manager at Atex, and this is MyType, a newsletter dedicated to journalism, innovation and artificial intelligence.   

Every fortnight we will explore a topic related to this evolving field to discover the pleasure of 'digital joynalism' together.

If this mail was forwarded to you and you would also like to receive future releases, you can subscribe to MyType here.

Now, let's get started! 

Could Artificial Intelligence help journalism?  

We know very well how difficult it is to answer this question. Perhaps utopian. We’re unlikely to do it in this newsletter and we probably won't have a clear answer in months or years from now either.   

However, we know that there is a lot of enthusiasm for what technology could offer in terms of helping the journalism sector, from news production to the automation of repetitive tasks. On the other hand, especially in this sector, several problems related to the use of AI in newsrooms are also emerging. For example; the spread of fake news, copyright infringement, plagiarism, or the misattribution of non-existent sources.   
 
At the end of March, a photo of Pope Francis wearing a Moncler jacket while walking through the streets of a major European city, began to circulate and made headlines.

was the prompt - the textual instruction that generated the image that became known as 'Monclero'. The image, passed off by many as a real photograph, was instead a fake made by Pablo Xavier, a bricklayer from Chicago who enjoys making images with Midjourney - one of the generative AI models specialising in the generation of extremely verisimilar images - in his spare time.  

A few days later, the same happened to former US President Donald Trump, who was immortalised in an orange jumpsuit behind bars and put in handcuffs by the police. In that case too, these were fake images, made by Eliot Higgins, founder of the investigative journalism platform Bellingcat and who, as he later declared, 'was only joking'.   

The fear of being replaced 

Many journalists are afraid that AI will replace them. Which is not an unfounded fear. In June, Axel Springer, one of Germany's largest publishers (owner of Bild, Die Welt, and the American Business Insider), announced that some journalists could be replaced by AI.

Although these events may be frightening, one thought arises: what will happen to the cornerstones of editorial work, such as ethics, accuracy, responsibility, and fairness that only a human being can guarantee? The main problem with generative AI, is precisely that of content reliability. Here then, we are at a starting point rather than the end. We would like Artificial Intelligence and its recent developments to be experienced as an opportunity for journalism and not as a threat. We call it a 'conscious revolution'.    

A revolution that has already begun   

We are certainly not the first ones to talk about these topics. For newbies, therefore, we believe it can be very useful to get a general overview and start setting some benchmarks in the field. Many more will follow, episode after episode. 

• Generative AI in the Newsroom, is a project with the aim of collectively develop the capacity for responsible use of generative AI in news production. The project is edited by Nick Diakopoulos*, associate professor in Communication Studies and Computer Science (by courtesy) at Northwestern University (Illinois, USA).  

• JournalismAI, is a global initiative that empowers news organisations to use artificial intelligence responsibly. It’s a project of Polis - the LSE's journalism think-tank – and it is supported by the Google News Initiative. LSE support innovation and capacity-building in news organisations to make the potential of AI more accessible and to counter inequalities in the global news media around AI.  

• Google News Initiative, it is now 20 years since Google invested in the development of projects that combine journalism and innovation. On their website you can find free courses (with certifications) to keep up to date and acquire digital skills, which do no harm. There is also one on the basics of Machine Learning, which is fundamental for understanding how Generative AI works.   

• The Associated Press was one of the first news organizations to leverage artificial intelligence and automation to bolster its core news report. Today, they use machine learning along key points in our value chain, including gathering, producing and distributing the news.  

In this webinar AP showed in 2017 (six years before the arrival of ChatGPT and others) how the newsroom was implementing automation in its systems.  

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Stories & Tools 

• How Reuters integrated AI to classify its videos, decreasing editing and publishing time   

• How The New York Times uses Machine Learning To Make Its Paywall Smarter 

• Become an expert in the field with the JournalismAI Starter Pack 

• 8 artificial intelligence tools for freelancers 

• *Could AI give technology giants more control over the news? Here is one of the Nick Diakopoulos speeches at the Perugia 2023 Journalism International Festival (IJF23)

• Here are all the other webinar at the IJF23

That's all for today!

There would be no 'digital joynalism' without sharing. We don't want this channel to be a one-way street. So for any ideas, suggestions and thoughts on the subject, don't hesitate to email me at sforni@atex.com!  

Have a good weekend,   

Sara