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Maarten de Rijke

Maarten de Rijke

Who: Maarten de Rijke (1961)
What: University Professor of Artificial Intelligence and Information Retrieval
Studied: Philosophy and Mathematics
First job: Shelf stacker
Favourite place at UvA: The Startup Village at Science Park, a co-working space created from shipping containers. It’s chaotic, it’s chilled out and it’s full of all kinds of people.
Essential: People, creative friction

Search for motivation

‘I wasn’t a good secondary school student; I didn’t really know what I was doing there. Consequently, I didn’t have much drive or motivation, so I did just enough, and no more. Therefore it was no surprise that after I left school, I didn’t go on to university straight away, but instead worked and travelled for three years. During that time, I gradually discovered what I found interesting and what I wanted to study. When the time was right, I went to university to study Philosophy. I was fascinated by the way language can transfer knowledge and reflect something of the world. Language and information transfer are amazing phenomena.’

Philosophy and Mathematics

‘Combining philosophy and mathematics may seem strange but it actually isn’t. It wasn’t long before I realised that relationships between language and the world, or between different languages, required a fair amount of mathematical knowledge. The more I learned, the more I realised that I needed to brush up on that knowledge. The easiest way to do that was to do a degree in Mathematics. After all, that’s what universities are there for, to expand the brain. And at that time, it didn’t cost a fortune to do a second degree, so I could just go ahead and do it. Plus, by that time, I finally had the motivation I had been looking for. I obtained both Master’s degrees with distinction (cum laude) and went on to graduate with a PhD in formal knowledge representations – which is the interface between mathematics and computing science.’

The study of language requires mathematical knowledge.

Search engine technology

‘There comes a time when you want to do something with the theories that you develop. I have specialised in question answering systems – in other words, search engine technology that enables you to connect people with information. I investigate how you can teach a system to give the right answer to a question. This works in a different way to a standard search engine, which basically assesses whether the documents relate to roughly the same things as the search question. Those systems mainly search on word overlap of the question with potentially suitable documents. When you’re looking for the right answer, word overlap is generally not a good indicator, because the answer isn’t in the question – otherwise you wouldn’t be asking it. So, a system must search for words or sentence fragments which are substantially different to the question that is being asked. This makes things harder. Finding enough suitable documents that systems could obtain answers from proved to be a challenge. It took me quite a while. It involves a huge amount of machine learning and self-learning technology, so my research touches on artificial intelligence.’

Urban arrogance

‘After my PhD I worked at CWI, the national research institute for mathematics and computer science in the Netherlands, for a while. Then I spent some time in the UK, after which I returned to the UvA in 1998. There’s a unique UvA DNA. It comes from our connection with the city, from the fact that we don’t have just one campus, but several. There’s also a kind of stubborn streak that’s unique to people at the UvA, a sort of urban arrogance. You always find that in major central cities. That positive, constructive friction is actually a good thing. It sometimes means that decision-making processes are slightly more difficult and take a bit longer but that’s all part of it. The preparatory phase takes longer; you have to go into things in a bit more detail. But the results that you obtain because of this are something you can be proud of, so sometimes a touch of arrogance is called for.’

The international nature of the Master’s has benefits for Dutch students as well.

International benefits

‘I don’t do a lot of teaching nowadays, but I do do the occasional lecture on the Master’s in AI. In recent years this Master’s has become far more international in nature, which has benefits for the Dutch students on the programme as well. People come to study here from all over the world and they all have one objective: to advance their learning and to do something that excites them. These students are highly focused, and work quickly and conscientiously. Keeping up with them wasn’t easy for their Dutch peers. It probably applies to us all: you do things well enough to move up to the next level, where you become average once again. You then work to reach the next level, where you’re a beginner once again. That’s what will happen throughout your life, but all of a sudden you realise that the people you’re comparing yourself with don’t come from round the corner, they come from all over the world. That’s just something you have to get used to.’

University Professor

‘I’ve just been appointed University Professor at the UvA. There are five of us now. We have to think beyond our own faculties and take more of an overall perspective on things. We also represent the UvA in the outside world. My chair is “University Professor of Artificial Intelligence and Information Retrieval”, so my plans involve search engine technology and promoting research and knowledge development. This technology doesn’t exist in isolation – it also has social aspects and impact. These must be investigated in conjunction with other disciplines outside of computing science, such as law or social sciences. And there are also ethical and legal factors involved, which I’m exploring with philosophers. There are plans to appoint more University Professors: one in AI applications, one in Humanities and one in Law. Our job is to work together in partnership to help move the world forward. It certainly keeps us busy!’

People think that robots are taking over the world, that we are losing our autonomy. And they’re right about that.

Fear of technology

‘People think that robots are taking over the world, that we will lose our autonomy, that human values will be lost. And they’re right about that. From the moment we created the first tool, in a way we transferred skills to something else. The latest, obvious example of this is satellite navigation. We can’t read maps any more, our phone does it far better. Machines can process large amounts of information more effectively than people, can summarise more effectively and can interpret medical images more effectively. In the near future many more cognitive skills will be transferred to devices. Some people fear this is going too far. One fear that you never hear, however, is: aren’t we doing far too little? If we let ourselves be constrained by fear, we automatically prevent ourselves from coming up with all kinds of solutions to social problems that we can already see coming. Clearly, we shouldn’t make progress for progress’ sake, but we shouldn’t just stand still for the sake of it either. Lots of things that were conceived with the best of intentions have been abused as well; that will always be the case. But does that mean that we should stop coming up with new ideas? Certainly not. It means that we must educate people, stick with it and understand what’s going on, so that we can intervene appropriately should it be necessary.’