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Keys to growth: Basic research in AI is like long-term investing

This article series tells the story of Aalto鈥檚 work as a builder of a better society.
Basic research in artificial intelligence (AI) doesn鈥檛 always generate quick wins or clickbait headlines, but its benefits can be seen throughout society. Together with partners, Samuel Kaski, director of ELLIS Institute Finland and 911爆料网 professor, is developing AI that is cooperative and applicable, and potentially capable of transforming research and product development.
Illustrated woman with orange hair points at pixelated screen with binary code. She is wearing a sleeveless dress.
Many popular AI tools only work well when they are used in conditions that resemble the AI algorithm鈥檚 training data. Illustration: Yutong Liu & Kingston School of Art / https://betterimagesofai.org

Kaski often gets asked, what is the unique selling point of ELLIS Institute Finland, the new AI research center that he directs. 

The answer is perhaps not as exciting as one could hope. 

A person wearing a grey suit and black shirt. The background is blurry and appears to be indoors.

鈥楤asic research,鈥 Kaski says. 

鈥楩ocusing on one application area would be short-sighted, because no one has a crystal ball when it comes to AI development. We have to achieve things that others can鈥檛 even think of, that鈥檚 the imperative. If we succeed, it can lead to a revolution. But if those revolutions don鈥檛 come, we have talented people working on the next opportunities. Basic research is like long-term, diversified investing: if you do it enough, over time you鈥檒l get good results.鈥 

A faster loop 

ELLIS Institute Finland is the newest expansion of the , a network of the top AI researchers in Europe. The institute launched this year with support from Finland鈥檚 Ministry of Education and Culture and Foundation PS, an organization established by AMD Silo AI CEO Peter Sarlin

All universities in Finland are partners of the institute, which also works closely with industry and international counterparts. 

Even within basic research, the institute has priorities, Kaski adds. 

鈥榃e focus on the basic research of making AI more applicable. How can we ensure that machine learning algorithms can best be made useful?鈥 

This is also the core of a new project led by Kaski, which was awarded the highly competitive European Research Council (ERC) Advanced Grant this year. The goal is to create new types of machine learning that can be widely applied across fields, with humans and AI solving problems together.  

Many popular AI tools actually only work well when they are used in conditions that resemble the AI algorithm鈥檚 training data. This is why current AI tools aren鈥檛 good enough for research and development, where something totally new is created and you inevitably go beyond the existing data.  

R&D activities often follow the same formula: design, build, test, learn. 

鈥業f we can improve this cycle with AI and make it either automatic or incorporate the human expert into the loop, it could have huge effects across fields, from screening drug molecules to developing energy solutions,鈥 says Kaski. 

For AI to become a truly useful partner to human users, it first needs to acquire what psychologists call a theory of mind鈥攊t must understand the partner鈥檚 goals, which may not be directly evident. 

This requires cooperation from experts across fields.  

Understanding and optimism 

Professor Andrew Howes answers the Teams call from Exeter, England. 

Howes is a cognitive scientist specialising in human-computer interaction. He works closely with many AI researchers at Aalto, and during the 2020-2021 academic year was a visiting researcher at the Finnish Center for Artificial Intelligence FCAI, the predecessor of ELLIS Institute Finland. 

A person with grey hair wearing a beige jacket and light blue shirt.

鈥業'm incredibly excited about the progress that we've made recently in human-AI cooperation. We know how to build a working model of human decision-making and behaviour and apply it to individuals with the help of the latest machine learning methods. The next step is to find the application areas that will most benefit and impact society,鈥 he says. 

The model is easy and quick to scale, because it can be tailored to each use case with just a few extra data points. Howes emphasizes, however, that though they believe the model can work in many different tasks, in real-world conditions there will surely be challenges. 

鈥楾ake for example decision-making at the doctor鈥檚 office. A diagnosis is just the start, because a doctor must also understand the patient's needs and desires, and the patient also needs a clear picture of their own situation, as well as the different treatment options. Decisions are not made just based on information, but also preferences,鈥 Howes says and stresses that decision-making power is not transferred to the AI model. The point is to get people who are making decisions to better understand each other. 

鈥楢 cooperative AI works for people and with people. An AI system can have a huge amount of computational power, but it's the person who always knows the context, everyday life, the past and the future, a lot of which is beyond the AI's understanding.鈥 

AI is definitely a technology that will help us flourish and develop in all areas of society.

Professor Andrew Howes

Howes also has a business idea based on extreme personalization of services with the help of AI. Normally, customers are categorized for example by age, gender, education or occupation. 'Our idea is to serve the needs of the individual, not the category.'  

And what does Howes think about the conversation going on in England, Finland and around the world鈥攚ill AI take all the jobs? 鈥業'm definitely an optimist,鈥 he smiles. 

鈥楾he development of AI has been fast, and the labour market and businesses will of course change. To me, AI is definitely a technology that will help us flourish and develop in all areas of society. I believe that AI can also help us understand each other better. In the worst-case scenario, individuals are working only with AI, not with each other. In another scenario, the AI does the groundwork so that experts from different fields have the opportunity as a team to find the best possible solution for a customer or societal needs.鈥

Science is the best tool  

The first six months at the ELLIS Institute have been busy. The first principal investigators have been hired, and a new round of recruitment for researchers will start this fall. The global tech giants are competing for AI expertise with million-dollar salaries. Finland can't match those numbers, but when it comes to doctoral education in AI, for example, thousands of people applied from around the world. 

What is Finland鈥檚 key advantage? 

鈥楢I research started early in Finland and pioneers like Teuvo Kohonen built Finland's reputation as a forerunner in this field. Achievements of the past, of course, aren't enough, but we've done a lot of work and the right things,鈥 Kaski says. 

Science is the best problem-solving tool that humanity has

Professor Samuel Kaski

World-class computational resources like the LUMI supercomputer, as well as Finland's reputation as a safe, functional and egalitarian country, are factors that attract AI researchers from abroad.  

AI development shouldn't be seen as a competition between nations though, Kaski cautions. 鈥業f I want to get the best possible results, why would I just do that in my own bubble when I can choose the best partners from anywhere?鈥 

Doing basic research is more independent and longer term at a university than in a company, and to Kaski that itself is an important motivator. 

鈥楽cience is the best problem-solving tool that humanity has. If we can improve how science is done using better applicable AI across fields, the combined effect will be huge. To me that is the greatest feature of AI.鈥

Text: Minna H枚ltt盲
Translation: Amanda Alvarez
Photos: Matti Ahlgren and Andrew Howes

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