Allocating resources

WHEN SUPPLY AND DEMAND IS NOT THE ANSWER

How do we allocate resources that we do not want to see priced by the free market in accordance with the law of supply and demand? It could be about human organ transplants – or access to a place in school.

Mathematics is an unbeatable tool for matching resources with those who need them. Complex algorithms are able to weigh parameters, such as tissue types and blood groups, or requests from parents and schools. Combined with well-defined rules, transparent selection criteria, computerisation and automated processes, we can save lives, time and money and ensure that our resources end up where they are most needed to support the common good.

AI saving lives, time and money

Professor of Economics Tommy Andersson works with transplant physicians and immunologists from several Swedish hospitals. Countries Sweden and Denmark are currently included the large scheme in which transplantation opportunities are to be optimised with the use of AI and machine learning.

“We have now moved on to the next phase in which the Swedish database has been merged with the Danish one. It is unique in the world in that it spans national borders. In the long term, I hope there will be a Scandinavian database,” says Tommy Andersson.

Algorithms reventing school segregation

The mathematical algorithms can also be used to allocate public housing, or places in schools. Here you can choose to include a number of parameters in the calculation, such as the parents’ wishes and society’s requirements to prevent an increase in school segregation.

“Things have been happening on that front. A number of my colleagues and I helped Lund Municipality with the school placements prior to the school selection period for the autumn 2019. They calculated the distances themselves in the form of student routes to school with the help of an algorithm that we developed.”

The municipality saved 600 hours and was able to send out information to students and their parents four weeks earlier than usual.

“The whole thing is part of a general digitalisation process; however, it is a good example of how even a municipality can save time and money by using its data in an intelligent way,” Tommy Andersson concludes.