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    Susan Stein

    Technology

    How a traditional book publisher is positioning itself as the Google of legal journals 

    by Susanne Stein Published 10 March 2023 in Technology • 5 min read

     Susanne Stein, managing partner of Vienna’s MANZ Publishers, explains how she harnessed Artificial Intelligence to transform the company from a traditional publishing house to a cutting-edge online legal publisher.

    One of the advantages of being a family business is that you can take a five-year horizon on decisions and not worry about quarterly reporting – but it is also necessary to be aware of the tensions created by the decisions you make. Within a family business, you always end up asking yourself, “What would my grandfather do?” On the one hand, you need to hold on to some of the tradition and some of the history, but at the same time, every generation must find its own path.

    A case in point was the decision to sell our printing company in 2001. As the fifth-generation owner of a publishing house, it was hard for us to stop printing books. But it was clear that what printing was in the 20th century, artificial intelligence and software engineering are going to be in the 21st century.

    MANZ’s digitalization journey began with my father in the 1970s, after he had travelled to the US and saw the first computer-assisted legal research databases from Westlaw, the company that is now owned by Thomson Reuters. He came back to Europe and founded the RDB Rechtsdatenbank which has evolved to become the leading database of relevant legal journals, collections of decisions, commentaries and handbooks for law in Austria.

    A regulatory push

    The Ministry of Justice has set the pace for technological adoption in legal publishing by making much of its data public and, more to the point, free. While it’s true that the biggest

    competitor you can have as a publisher is free data, it does drive competition and improvements within the sector. It also pushed us to move quickly and to evolve to offer our customers extra features and more information.

    The challenges we now face are centered on artificial intelligence and products like ChatGPT, the artificial intelligence chatbot developed by OpenAI which launched in November last year. Responding to these challenges is not something for the future. We have already brought examples to market. Last November, we launched a product as part of our RDB Rechtsdatenbank called RDB Genjus based on this type of generative AI, but we trained it ourselves. Instead of searching through all the data available online, it is more precise, which is important for our customers.

    Susanne stein

    The technology is not wholly there just yet, as we offer the AI search function only within documents that exist in our database. This reduces the chance of mistakes. So, a user cannot, for example, upload a document and then search for a similar document, but as soon as they have found a document within our database that is relevant, we then do offer the AI search. This reduces mistakes to less than 1%. 

    For the past 25 years, searches have been based on machine learning – broadly defined as the capability of a machine to imitate intelligent human behavior by using vast amounts of data – and this certainly remains the direction of travel, though it is unlikely that we will continue to use machine learning in the way that we do today.

    Better than Google

    Our search capabilities have always been good, but the next step is to take a more linguistic approach to search. In every article we publish, we mark specific words as important, so users had to know broadly for which legal point they were searching. The use of natural language, as well as the ability of a computer program to understand human language as it is spoken and written, will add considerable value. It will help provide more nuance, more differentiation, and deeper content. In short, it will help users search accurately in a world where there is even more information. The ongoing challenge is that of natural legal language. It requires computers to understand language at a high level.

    We always compare ourselves to what Google is doing, and for legal language, it is not yet especially good – even more so for German legal language. What research there is, is going into English.

    Our content is our data treasure, and we want to get as much as possible out of it for our customers. It has been a long journey from print to digital, but by harnessing the power of AI we hope to make our family business fit for another five generations.

     

    How to harness the power of AI in your organization

    1.Make sure you have some of the skills in-house
    As a publishing company, data science has become increasingly relevant for us. Over the past last few years, we have tried to build up our internal software engineering experience. We have used external sources in the past but have now reached the point where we need access to that expertise on a regular basis.
    2. Structured data and standards within your data are a key asset
    Although the use of generative AI means that you don’t need as much structured data, it helps considerably with training. The standards and the structure in the data accelerate the process of bringing new members of staff up to speed.
    3. Start with a small use case to pilot the data platform and the setup
    In the past, our data platforms were set up by an external provider. Now, we do it within our own infrastructure. You could, of course, start with a large project, but a small pilot allows you to test everything.
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    Authors

    Susanne Stein

    Managing Partner of MANZ Publishing

    Susanne Stein became Managing Partner of MANZ Publishing in 2006. Since then, she has streamlined the business, merged the business titles, and brought the publisher back under full family ownership. She completed IMD’s Transformational Leader program in 2021.

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