AI, the Power of Knowledge and the Future Ahead: An Interview with Head of Ontotext’s R&I Milena Yankova

On March 19, 2019, interviewed Milena Yankova, Head of Research and Innovation for Ontotext. The conversation covered a wide range of topics from the tasks Artificial Intelligence (AI) can handle and the challenges it poses, to "fake news", the intelligent enterprise of the future, cancer and much more. Learn about how machines can and do help people to be more efficient and more creative.

April 5, 2019 10 mins. read Ontotext Interviews


Ontotext and Artificial Intelligence Milena, what kind of projects does Ontotext work on?

Milena Yankova: Ontotext works mainly on commercial and research projects that involve huge volumes of data where we search for meaning. We apply Artificial Intelligence techniques to understand the value locked in this data so we can extract knowledge that can benefit people. At what stage is the development of Artificial Intelligence? What kind of tasks can it currently perform?

Milena Yankova: There are two definitions of Artificial Intelligence. They differ mainly in terms of the motivation behind: why do we create Artificial Intelligence? In the first school of thought, AI aims to mimic the way we, people, think, act, feel, talk. Their motivation is to imitate and through that to understand how people work.

In the other school, the goal is to carry out tasks in a smart way in order to help people. We, in Ontotext, follow the goal of the second school, i.e., we want to help people do their job better. How can businesses benefit from Artificial Intelligence? How do you help?

Milena Yankova: Our work is focused on helping companies make sense of their own knowledge. Within a large enterprise, there is a huge amount of data accumulated over the years – many decisions have been made and different methods have been tested. Some of this knowledge is locked and the company cannot access it. We help our customers unlock it and make it usable so they can be more efficient. We translate their documents, presentations, tables, etc. into structured knowledge that can be processed by machines.

Smart Content Management and Recommendation Tools You work with media companies such as the BBC and the Financial Times. What exactly do you do for them?

Milena Yankova: We help the BBC and the Financial Times to model the knowledge available in various documents so they can manage it.

The BBC keeps information on every show, every actor, every athlete, about all the content that the BBC has ever produced for its departments. That’s the whole history of the BBC! When new content is produced, journalists may say, “Let’s see what has been discussed about mathematics in Sofia in the last 5 years or 15 years ago.” Then this knowledge can be downloaded from the network.

Another thing we do is website recommendations. If you go to a BBC webpage, you will get recommendations for other types of content that are somehow connected to your interests. We do this for the Financial Times as well. You have created the algorithm that recommends content on the webpages of the BBC and the Financial Times?

Milena Yankova: That’s right. This algorithm monitors your interests. In the case of the Financial Times, you have to identify yourself (as it is a paid publication) and each subscriber has an individual profile. So they can decide whether to share information about their interests or not. If they decide to share, the Financial Times keeps track of what they read or find interesting. Then it tracks current news and offers prioritized content that fits the subscriber’s interests. But doesn’t this algorithm put us in an information bubble by filtering the content for us?

Milena Yankova: That’s a very interesting question. The Financial Times has a special department for monitoring people’s behavior. They have different metrics for judging whether some content is interesting or not. The aim of the algorithm is not to present more of the same, but rather go show you topics that you would not think to search for and that are still related to your interests. The aim is the opposite – to expand the soap bubble we live in, giving us different perspectives.

Machines Against Fake News You also have a project in support of the fight against fake news. What exactly is it about and how does it help?

Milena Yankova: It’s a research project called WeVerify and our goal is to help some of the big media and their journalists detect disinformation or the so-called “fake news”. This is a difficult task for the general audience to handle on their own. However, there are journalists who are experts in this field. And they need tools that can assist them in handling this extremely complex problem.

An example of such complexity is an interview given by Barack Obama in Dubai on a particular day. The interview is perfectly animated and it seems like Obama says things he has never actually said. To verify it, we can check the video for any signs that it has been manipulated. Or, we can check whether Barack Obama was in Dubai at the time.

On this particular project, we are working with Deutsche Welle and Agence France-Presse.

Another area often affected by this problem is social media where someone claims that something has happened that actually hasn’t. Sometimes it’s a deliberate manipulation of the information and sometimes it’s inadvertent. Our goal is not to solve the entire problem. I don’t believe that if people can’t manage, we can teach a machine to manage. It’s more a question of facilitating the job the experts so they are able to say if something is fabricated or not.

Artificial vs Human Intelligence How would the smart enterprise of the future look like?

Milena Yankova: In an intelligent enterprise, people focus on doing what they are good at and what gives expression to their creativity, imagination and self-examination, while the machines perform the mundane administrative work. This, however, is the optimistic scenario foreseen by AI developers. What would happen if someday AI overtakes human intellect? There are some predictions that it could happen as soon as 2030. How will we control AI in that case?

Milena Yankova: It’s long since machines have been ahead of us in computational tasks. Whether they can autonomously make decisions that could harm people or not will depend on the power we give them. This issue is irrelevant in the case of businesses as there the decisions are made by people. We don’t give Artificial Intelligence the right to make decisions for us and to manipulate our lives.

One of our customers is from the so-called “Big Four” (the four biggest accounting firms in the world). They have to analyze huge amounts of financial information about many companies. We can do this analysis for them and tell how many companies are there in a particular segment, how many of them have received investment and what the next big technology will be because, currently, there is a lot of investment going into it. This is a knowledge that anyone can get, but it would take much longer than optimal. The pros in this respect are indisputable. But still, is there a risk that AI could replace people at their workplace? How to prepare for a future without employment?

Milena Yankova: Will AI replace us? It’s very likely. It’s possible that some professions we currently have will no longer exist. Just like there are almost no shoemakers or tailors and, if they exist, they are part of the luxury segment. But that doesn’t worry me too much. Because the tasks that we can give computers are usually tasks that bore us and require a lot of computational work. One area where computers will definitely not replace us is our creativity. There has been a significant breakthrough in this respect as well. There already are robot-composers, robot-attorneys, robot-journalists, robot-painters.

Milena Yankova: That’s the challenge! Can we think of something computers can’t do? Yes, computers can make a nice song to entertain us. They can paint a picture that we can hang in the office, but there is no spark. I think artists can relax. What about journalists?

Milena Yankova: What we did for the BBC in the previous Olympics was that we helped journalists publish their reports faster. We minimized the time between the event (and what the journalist wanted to say about it) and the moment the reader or viewer could consume it.

Machines’ Support in the Fight Against Cancer You have launched a research project that will help in the fight against cancer. What is it about?

Milena Yankova: We work in several areas: media, financial institutions, pharma companies and healthcare. This particular project is an R&D project and it is called ExaMode. There are many challenges in this area and we want to help solve them.

When a cancer patient goes to a hospital, an image of the tissue is taken. This is one of the main diagnostic tests. Then, doctors work with this image to assess if there is a tumor and what kind of tumor it is. This process requires great expertise. The doctor needs to know how to collect the data from this image. He needs to know what information this data carry. Then, he has to apply his own knowledge and experience to make the diagnosis.

The goal of this project is to help doctors reduce the time and effort required before making a diagnosis. Machines would never make the diagnosis instead of physicians, not least because of the ethical issue. And we don’t have such ambitions, either. But we can help doctors process the information more efficiently.

The Future Ahead of Us How can young people find their bearing today and what can they put their stakes on to be able to handle all these changes adequately?

Milena Yankova: The professions of the future are related to understanding and processing data, transforming it into information and extracting knowledge from it. The better we understand this process (from gathering facts to connecting them to other facts and interpreting them in the context they appear), the more effective we will be in this information era that is passing into an era of knowledge. What would you advise your children?

Milena Yankova: If they decide to work in IT, I would advise them to better understand the value of the data that machines collect from their interactions with us. Because humans give machines a lot of information. The moment we move around with our mobile phones, those who have access to the data and can interpret it, know where we are. The moment we use our credit cards, they know what we have bought. The moment we like a Facebook post, it’s clear what we are interested in and who our friends are. This is extremely powerful, so literacy in data collection and data processing will be one of the crucial skills of the future.

Bulgaria’s Place in the AI Race Is Bulgaria prepared for such a revolution?

Milena Yankova: Bulgaria is at the forefront of internet speed and the connectivity between people. Bulgaria produces exceptional minds – mathematicians and IT specialists. Many students get scholarships to study around the world and then return here. So we have amazing potential. In the current race for artificial intelligence, the leaders are China and the United States. Where are we?

Milena Yankova: More and more companies are coming to our country. The salaries in the IT sector in Bulgaria are no longer so low. We are as expensive as our colleagues in Poland or the Czech Republic, which have been traditionally preferred so far. Companies come to Bulgaria because of human potential.



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In Ontotext Interviews, we talk to colleagues, partners, customers and leaders in next generation technology trends and standards. We explore topics about semantic technology, enterprise knowledge graph technology, semantic database engines, artificial intelligence systems and other solutions for addressing enterprise data management requirements across various industry verticals. By adding the dimension of human opinion and experience to these complex subject matter, we hope to deepen the understanding and appreciation of such technologies.

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