Paula Jordaliza, mathematician: “Algorithms do not work alone. Everyone who uses them must know what they are doing and why these decisions are being made” | Technology

Paola Jordaliza (Valladolid, 29) uses mathematics to try to make society more just. The young researcher, winner of the Vicent Caselles Prize awarded annually by the Royal Spanish Mathematical Society (RSME) and the BBVA Foundation, has developed a system for correcting the bias of artificial intelligence (AI) algorithms, capable of making more accurate predictions than any expert. “The problem is that these decisions are not always socially responsible,” Gordaleza explains in a video call. A researcher at the Basque Center of Applied Mathematics in Bilbao and associate professor at the Public University of Navarra, she began studying a method to eliminate algorithmic biases during her PhD at the University of Toulouse, when AI was not yet under the scrutiny of regulators and public opinion. “Things have evolved very quickly over the past five years. Now more than ever, it is important to work on the effects of artificial intelligence on people’s lives,” says the researcher.

Ask. Do you use artificial intelligence a lot in your work?

Answer. I like to remember that I am, first and foremost, a mathematician, and what I do is research mathematics. My work consists of the foundation of the theoretical foundations needed to develop any technology, particularly artificial intelligence. So I deal more with the study of mathematical problems and how, once these issues have been solved from a theoretical point of view, they can be applied to real problems. In my case, we are talking about machine learning and algorithmic fairness, which are included in the field of artificial intelligence.

s. How are mathematics and artificial intelligence related?

R was found. Mathematics is behind all scientific and technological developments, and in recent years, artificial intelligence has become the most common form of progress. What mathematics does is establish the theoretical foundations for solving the problems we face, which in the case of my research would be the algorithmic biases of AI.

s. What is computational bias?

R was found. It is somewhat complicated to explain, since they are words that have been used so much, they have been given many meanings depending on the context. In statistics, a biased object is something that does not behave as expected. Whereas, if we go to the field of artificial intelligence, where this word is used a lot, it refers more to tendencies or biases for or against a group or an individual based on certain characteristics, such as gender or skin color. Perhaps this is what contributes to the fact that algorithms cause fear and mistrust in people.

s. What is this?

R was found. We are witnessing widespread use of AI systems and algorithms in particular, and this manifests itself in aspects that directly affect people’s lives. Grant credits, in selecting personnel for a job or in the clinical field, to decide who will provide treatment or make a diagnosis. There are many examples, but this is probably the most popular. Of course, the fact that algorithms can decide on these issues generates fear and anxiety in the population. This will happen until they receive assurances that these algorithms are fair, reliable, and explainable.

s. What can be done to remove this fear?

R was found. This is where the importance of mathematics can be seen, as it helps us understand how algorithms work and is a tool for opening the black box of artificial intelligence. It is important that the message gets across that algorithms do not work alone, and that everyone who uses them knows what they are doing and why these decisions are being made. This would go a long way in reducing people’s mistrust of you.

R was found. You talked about prejudice and discrimination. Are algorithms racist?

s. Algorithms are not racist or sexist. Algorithms learn from data. Machine learning is a form of artificial intelligence that is capable of making predictions and creating connections from huge databases, and is able to manage them at high speed. The problem comes when this data is not of good quality. For this reason, it is necessary to bet on the existence of high-quality databases that are unbiased with regard to variables that may contain sensitive information, such as race, gender, disability, sexual orientation or any other information that may be subject to discrimination.

s. This is your search.

R was found. The idea was to try to create two sub-groups of the population, say, men and women, that are as similar as possible in the rest of the characteristics. In this way, I tried to omit the gender information so that the algorithms could not learn the gender of the people and retain the information provided by the rest of the database.

s. Society has improved when it comes to discrimination. Why are there still so many prejudices?

R was found. It is not a problem of society. In the end, a tool is used that learns from historical data and that is biased, this is how the algorithm learns it. What needs to be done going forward is to encourage research, because it is a matter of knowledge, and the boundaries of knowledge are getting more and more complex. If we are to improve, we need multidisciplinary teams made up of mathematicians, statisticians, computer scientists and more professionals who in turn contribute to the cause. All points of view are needed, not just the mathematical one, which also needs to be greatly improved.

s. how?

R was found. Certainly, an academic and research career must be promoted, for high-quality research to focus exclusively on AI, but with very solid mathematical rules that ensure that what is done with algorithms is reliable, safe, and fair. To achieve this, there must be a motivation for young people to be drawn into this profession, which is very difficult in these times. It is important to improve the conditions of this profession, especially in the early stages. Previously, at the age of 30, I was already a tenured master, while now, at the age of 29, I would still start as an assistant.

s. When you talk about motivation, do you refer to finances?

R was found. Partially, but there are also other factors to consider. For example, the feeling that you are advancing in your career and that you are getting more and more relevant positions. Feeling appreciated is essential to stay in Spain and keep trying.

s. I got my PhD in France. Do you think there are more possibilities abroad?

R was found. There are many possibilities, but also in Spain. The math that is done here and the research that is done here is of high quality. I have already had this experience of living abroad and I am sure that during my career I will also have other opportunities to do international studies, which is undoubtedly something that gives great value to your career and provides a lot of projection. But my ultimate goal is to stay in Spain, where research, at least in my field, is advancing a lot, and the importance that AI gains will give us a lot to work on.

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