10:00 a.m.-12:30 p.m.
(New York time)

Personalisation along the entire journey

Personalisation plays a key part in a successful user journey, from targeting a non-subscriber with the right offering at the right time to following a tailored onboarding and retention messaging, to recommending relevant content to users. Carmen Heger, the head of data at Süddeutsche Zeitung, will share how they have built and applied recommender systems for content personalisation, and causal machine learning for targeting marketing and retention campaigns.

Carmen Heger, Head of Data Science, Süddeutsche Zeitung, Germany


Filter bubbles are a choice: How to build successful and responsible news recommendations

The notion of filter bubbles is one that’s generally held up whenever we talk about the topic of personalisation in news. We think that personalisation just means reinforcing whatever the preference of the user, at the expense of the diversity of the user’s news diet. On the other hand, we also want personalisation that works: keeping users more engaged with our content and platforms. Cristina Kadar, the product owner for data science and machine learning at NZZ in Switzerland, will present the approach of NZZ in building responsible news recommendations, informed by user needs and in support of their reader revenue program.

Cristina Kadar, Data Science & Machine Learning Product Owner, NZZ, Switzerland


Building the single customer view at News UK

Understanding your user across their every facet and surface of engagement with your product is a high goal of many publishers. Enabling product improvement, improved marketing, and higher revenue, such a large-scale project also touches many teams in your company and many a technical system. Will Sach, the director of data strategy at News UK, will share with us some of his insights driving the long-term project toward gaining and building on having a single customer view of News UK users.

Will Sach, Director of Data Strategy, News UK, United Kingdom

10:00 a.m.-12:30 p.m.
(New York time)

Generative AI and the law: challenges and opportunities

Generative AI opens up whole new frontiers of complexity when it comes to intellectual property, liability, and competition with large technology companies. We are also, as publishers, likely to use these technologies and have to be mindful of how this usage is handled. Martin d’Halluin, the deputy general counsel at News Corp in New York, will join us to share his views on the challenges and opportunities presented by generative AI given the current legal landscape.

Martin d'Halluin, Deputy General Counsel, News Corp, United States



Bringing generative AI into newsroom tools

Ekstra Bladet’s first experiments with generative AI included summarisations in autogenerated news articles. As the technology matures, scaling its use also means making tools that can be used every day and looking for reliability and quality. Tore G. C. Rich, who is in charge of content automation data projects at Ekstra Bladet, will share with us some of the recent work their team has explored – what worked, but also, what didn’t!

Tore G. C. Rich, Content Automation Manager, Ekstra Bladet, Denmark


Designing guidelines on AI that work for journalists and our users

Much of the chatter about using AI in news content revolves around capabilities: What can AI do, what can it do well, and where can this go awry? But we would be remiss to not consider that the pact of trust we make with our readers and our journalists is at the crossroads of the capabilities of computer systems. Our readers don’t know much about AI, however, and our journalists have to make calls that are sometimes complex for where capabilities should or shouldn’t be used. Katharina Schell, the deputy editor-in-chief at the Austrian Press Agency (APA), has developed a framework to approach these questions internally, and with our users as well.

Katharina Schell, Deputy Editor-in-Chief, APA (Austrian Press Agency), Austria


What the Guardian learned about manual annotation building their quote extracting project

There are more and more methods to machine learn on content, so refining methods that we can use across projects is an important part of scaling ourselves up. Anna Vissens, the lead data scientist at the Guardian, and her team designed an application to extract quotes from content using manual annotation to inform machine learning. She will share with us challenges when it comes to building training data sets, and how we can leverage new emerging technologies such as LLMs to help us with these tasks.

Anna Vissens , Lead Data Scientist, The Guardian, United Kingdom

10:00 a.m.-12:30 p.m.
(New York time)

How Bonnier used analytics and generative AI to create a new aggregation product

Bonnier news wanted to leverage its vast offering across its news titles and optimize the discovery experience of users: its newest product, +Allt (+Everything), gives users access to over 50 titles with one subscription. Hans Hjelm, the product owner for data science at Bonnier News, will share with us how his group used analytics and generative AI to identify and repackage the stories for the users of this new product.

Hans Hjelm, Product Owner, Data Science, Bonnier News, Sweden


Where is Generative AI taking us next?

By now, you’ve read so many headlines (and perhaps attended a few conferences, too) on generative AI and you likely have some ideas for some of the applications our industry is currently exploring, like helping the newsroom make quicker work of tedious tasks, for example. But you’ve also seen how quickly generative AI has advanced in even a few short months, so we have to ask ourselves: where is this taking us? These are some of the big questions that Laura Ellis, the head of technology forecasting at the BBC, is looking at along with her team, in order to imagine how best to apply these technologies in the organisation of the future.

Laura Ellis, Head of Technology Forecasting, BBC, United Kingdom


How to design experiments to explore generative AI technologies

The Futures Lab at Schibsted has explored various generative Ai technologies for applications in our news industry. But the multiplication and speed at which technology is advancing means we have to be smart about how we decide to investigate these technologies, and smart in imaging experiments to test out the potential they represent in their applications to our problems. Yifan Hu, a UX designer in the Futures Lab, will share her approach to investigating these technologies, such as text to mouth movements or gestures.

Yifan Hu, UX Designer, Futures Lab, Schibsted, Norway

10:00 a.m.-12:30 p.m.
(New York time)

Streamlining metrics we use to create a more focused business at the Financial Times

Metrics That Matter, is an initiative to optimize and simplify metrics at the FT and ensure everyone is confident that they are using the right performance numbers in their roles. McKinley Hyden, the director of analytics business impact at the FT, will share with us how her team started from a North Star methodology to create a new framework to tie tactical measures to strategic goals across 7 departments, with new reports and a data catalog.

McKinley Hyden, Director of Analytics Business Impact, Financial Times, United Kingdom


Approaching data democratisation and literacy, from the Guardian to Condé Nast

If data is going to support us across the organisation, it has to be accessible to everyone, in a manner that is both useful and meaningful. But bridging the gap from being a technical asset to becoming a building block for all departments means overcoming hurdles: our own organisations, at times, and raising the bar on data literacy. Mehul Shah, a longtime executive in our field who recently joined Condé Nast as their VP of enterprise data and analytics, will share his insights from building organisations that could realise their ambitions with their data.

Mehul Shah, VP, Enterprise Data & Analytics, Conde Nast, United Kingdom


Using empathy to broaden analytics usage in the newsroom

Many of the tools given to newsrooms to acquire performance insights about content were derived from the tools originally developed for marketers and other core data types. But is this what serves this constituent group best? Yves Van Dooren, who leads analytics for newsrooms of the northern European Mediahuis group, will share some of the work his organization has done to reimagine how reporters and editors can best receive analytics.

Yves Van Dooren, Data Science Business Partner Newsrooms, Mediahuis Belgium, Belgium


How data happened

Taking a look at how data has been used in various societal applications, Chris Wiggins, the chief data scientist at The New York Times, connects these dots with the mathematical and computation approaches that have been used in service of people, organisations, or economies. Chris has written a book, which is an extension of his course at Columbia University, and he’ll be presenting some of the highlights from this history of data, and how it connects to our future with data.

Chris Wiggins, Chief Data Scientist, New York Times, United States