By Anabelle Nicoud
Following Ole Reissmann on LinkedIn is a must for anyone seeking AI inspiration, as he regularly posts witty commentary on his AI experiments.
A personal favourite is about how he created a ‘kitchen cabinet’ to help draft an application for CUNY’s AI Journalism Lab – using AI.
Reissmann started his career in editorial, reporting on web and technology, and exploring big data – and developing a keen interest in machine learning and audio.
Over 14 years at Der Spiegel, he has worked at the intersection of editorial, product and innovation.
In January, Reissmann was promoted to Director: AI for Spiegel Gruppe, one of the first European publishers to have announced a partnership with the Californian AI-search company Perplexity.
This is the fourth interview in a series on AI leaders; see here for the previous one with Jane Barrett, Head of AI Strategy at Reuters.
Describe your new role, and what it entails.
I’ve been in editorial for the last 15 years, but my new role is in product development. We see this role as more of an overview of what happens across all departments of the company, ensuring that everyone is aligned with our AI strategy.
Currently, we have an intersectional AI working group that includes editorial, product development, front-end development, organisational development, and the unit that handles design sprints and innovation.
This group meets regularly, currently every two weeks. We set the strategy, maintain an overview, and have various working groups: one is focused on infrastructure; another on our partnership with Perplexity, and a third on digital transformation and upskilling.
In October, we planned a whole week of workshops and sessions on AI for different departments.
We also have a working group dedicated to product development, where we’re currently prototyping. We take these prototypes to potential users, gather feedback, refine them, and aim to release some of these features into the market in the near future.
Tell us more about your experiments.
Our fact-checking unit, separate from the newsroom, is a powerhouse in Germany, responsible for managing our press archive and database, which holds millions of articles.
Impressively, 90% of these articles – a significant resource – are not available on the open web. In the last six to nine months, they’ve developed a feature that allows natural language interaction with the archive.
You can ask questions – for example, in a recent debate about military conscription, the archive pulled up around 250 articles on military service.
You don’t need to read them all; through smart prompting, you get summaries, timelines, and insights into opinion shifts or contradictions between articles, allowing for deeper exploration.
Another exciting project is the Gender Report, which combines gender AI and natural language processing to analyse our articles. It assesses who we’re writing about and whether we’re discussing men or women more frequently.
This can even be done retroactively with years of archived data, allowing us to produce reports. While this isn’t yet a daily task, it gives our editorial teams insights – for instance, we might find we’re focusing too much on older white men, leading to adjustments in our content.
Customisation is also a major focus. Like many others, we’re working towards tailoring content for subscribers based on their interests.
By the end of this year, we hope to have a dedicated space where subscribers can see articles they may have missed, and engage with topics they’re passionate about.
European newsrooms have been creative with machine learning and automation, even before the release of ChatGPT. What are your thoughts on how this innovation has evolved?
We have a list of potential AI applications, and we need to be strategic about prototyping and focusing on areas where we can have real impact.
Some use cases are obvious, like optimising SEO headlines or generating summaries. The question is, what has changed? On one hand, expectations have shifted.
People in the newsroom often ask: “Can’t AI do this already? Why am I still doing it manually?” Sometimes, it’s not about AI, but about improving workflows and processes.
On the other hand, once people start experimenting with AI, new ideas emerge, and there’s a desire to keep up with the technology.
‘We’re running several experiments right now, including a collaboration with a German tech company that’s developed a machine to read our articles and produce podcasts.’
The only human input is at the script review stage, where we can edit the AI-generated script before the machine handles the text-to-speech conversion. It adds in ad breaks, music, and finalises the podcast for publication.
We’re still assessing whether we want to fully implement this, as it’s currently a feasibility study.
Our approach involves making thoughtful investments in internal projects, particularly in areas where our fact-checking and archive expertise sets us apart.
There are also simpler applications like AI-assisted SEO headlines and internal linking. Additionally, we’re conducting user-facing experiments, though we’re not yet ready to deploy them.
You may have heard about our partnership with Perplexity, which I can’t elaborate on, but you can see the potential direction.
The key question for us is whether we want to create a Perplexity-like experience using our premium legal content on our own platform.
As we shift our business model from reach to focusing on more subscribers, building and maintaining user trust is crucial. Subscription is the future, and it’s essential that users trust the content we provide on our site.
About the author, Anabelle Nicoud
A freelance journalist and consultant based in San Francisco, Nicoud currently collaborates with The Audiencers newsletter and the Canadian monthly L’actualité.
She has worked with Apple News+ (2022-2024); helped the editorial teams at La Presse (2015-2019) and Le Devoir (2019-2022) with their digital transformation, while leading ambitious editorial projects that have won prestigious journalism awards in Canada and Quebec.
A former journalist for La Presse and correspondent for Libération in Canada, Nicoud is passionate about the impact of technology on the media, she closely follows issues related to the use of artificial intelligence.
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