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Futurist Dr. Mariana Todorova: Young People Should Develop Skills Like Mental Flexibility, Empathy, and Social Intelligence

Dr. Mariana Todorova
© Dr. Mariana Todorova

Dr. Mariana Todorova is a futurist, assistant professor at the Bulgarian Academy of Sciences, a former advisor to the President of Bulgaria, a former member of the Parliament, a regular speaker at future-focused events, co-chair at the Bulgarian node of The Millenium Project, and even has her own startup. 

Todorova is developing a new methodology for scientific forecasting, a combination of counterfactual analysis and scenario building. She has experience with the US state department and the Chinese Academy of Governance. We met her at a Hacking HR meetup dedicated to the future of work and asked her to tell us more about her expectations for what’s coming in the realm of education, jobs,  politics, and artificial intelligence.

Trending Topics: What does a futurist do and how did you start your career in this field?

Mariana Todorova: Back in 2004 when I was about to start my Ph.D., I could pick between Philosophy and Futurology. I chose the latter as it was a very interesting opportunity to prepare for the future. In general, futurists try in a purely theoretical way to build models, theories and strategies for the future. People in the field of futurology can work as scientists, writers, business consultants. I have done most of these things and recently started developing my own startup – a blockchain-based liquid democracy platform, so I guess entrepreneurship is an option as well.

Can you tell us more about this liquid democracy project?

In practice, liquid democracy is delegated voting. Imagine we are a part of the same community and we have to make decisions on certain topics. If I feel like I understand the subject, I will use my right to vote directly. But if I decide I am not qualified to provide a meaningful contribution, then I can give my voting right to someone else, an expert in the field. I am trying to create this in a digital environment so that more people participate in debates and share their perspectives on important questions.  By using blockchain-based smart contracts, we can reduce the risk of manipulation. The application of this platform is not limited just to political elections – it can be implemented in corporate structures, non-profit organizations, or any community that’s not in the same location but has to make decisions. 

Any feedback from the political circles?

I had the opportunity to talk with several representatives of political parties and they are open to testing it for internal communication. To be honest, for the time being, it will be very difficult for such a platform to be used for political elections because it would require a legislation change. As you can see, even the electronic voting has not been approved yet. But this is the future – countries in South America, for example Argentina, also have similar projects.

Let’s put politics aside for a minute and talk about education. What advice would you give to young people who are not sure what to study at university? Is there any point at all in enrolling in a university program?

I still believe that universities are important. No matter how disciplined or self-motivated a given individual is and most people are not, universities give you this extra push to learn. That said, I agree that many universities offer outdated programs, not relevant to what people will need in the future. 

First of all, I would advise young people to follow the analyses provided by futurists and think whether their field of interest is not in danger of automation. There is no reason to panic. However, today’s youngsters should definitely develop skills like mental flexibility, critical thinking, empathy, as well as social and emotional intelligence. They should be ready to reinvent themselves every few years and consider designing new professions themselves – after all the jobs of the future will be created by humans.

What jobs do you think will have the brightest future?

This is a tricky forecast even for me to make. Think about the biggest problems in the world today – climate change, plastic pollution, food, overpopulation and resource scarcity, demographic crisis, gender and racial equality, etc. – everyone who is working on solving an urgent global problem will be valuable. I believe that another important group is that of personal mentors, coaches, psychologists who would help people find their way in a quickly-changing environment. 

You have experience with China, the United States and of course, Bulgaria and Europe. Can you compare the artificial intelligence (AI) strategies of these very different regions?

China and the United States are the two powerhouses in the field of AI. They are the favorites to create an Artificial General Intelligence. The main difference between them is in the source of progress. In China, most advances come from the work of government-backed centralized research institutions whereas in the US, startups and companies like Google, Facebook, Amazon play a much bigger role. Both approaches have pros and cons. In the latter case, corporates want to make money which more or less defines the type of AI products that are being created. Researchers in China do not feel the pressure of having to make money but I think that their isolation from the rest of the world somewhat slows them down. Unfortunately, in Bulgaria and Europe as a whole, we are still far behind.

What’s the problem you see with the European approach? Is it a smaller market or a lack of financing?

Well, there is plenty of money coming from the EU but in my opinion, the mechanism of how projects are chosen for funding should be reexamined. Right now, financing is just not equally accessible for everyone and on top of that, government structures are not always qualified to select the projects with the highest probability of success.

Is an AI more suitable to take such decisions?

Many people support this perspective. They make the argument that decisions made by an AI will be objective. However, we should be really careful – the logic of an AI is based on quantitative parameters, which sometimes may lead us to forget the qualitative side. Also, depending on the data we use, biases will more often than not still exist.

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