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Profligacy Day & World Savings Day | Małgorzata Przybyła-Kasperek, PhD, DSc, Associate Professor

30.10.2021 - 13:04 update 07.12.2021 - 11:59
Editors: adrianmachulec
dzienrozrzutnosci

31 October

PROFLIGACY DAY

WORLD SAVINGS DAY

Save the date with our scientists

„Save the date” is a series of articles that have been written to celebrate various unusual holidays. The authors of the presented materials are students, doctoral students and employees of the Faculty of Science and Technology of the University of Silesia.

31th October is celebrated as Profligacy Day & World Savings Day.

Have a read: Małgorzata Przybyła-Kasperek, PhD, DSc:

PrzybylaKasperek

Fot. Tomasz Kawka, UŚ archive

Małgorzata Przybyła-Kasperek, PhD, DSc, Associate Professor


Institute of Computer Science

Saving and profligacy – two antonyms whose day we are celebrating today. Is it possible to reconcile them?

When we talk about saving, we usually refer to money that we put aside to secure our own future. However, in the era of dwindling natural resources, saving takes on a completely different meaning. Food is often wasted and thrown away. Could artificial intelligence help us make efficient use of our food supply and reduce the number of products we throw away? Oh indeed!

We often agree to have our shopping data stored in exchange for benefits offered to loyalty card holders. This type of data is very valuable. The marketing team uses this data to send out personalised advertisements. When a telecommunications company calls with a particularly lucrative offer, it means that an algorithm has identified you as a potential person who wants to cancel the network’s services. It is more profitable for the company to offer additional benefits than to lose a customer.

However, in an era of dwindling natural resources, this type of data, instead of being used for marketing purposes, should be used for efficient management of food supply. A system is being developed which, based on data about our food stocks and their best-before dates, as well as the food preferences of family members and other information, will help us choose a daily menu. This system will also allow us to control the caloric content of the food we eat. Such solutions are possible by using artificial intelligence, automatically generating decision rules on the basis of historical data and the reasoning module, which is an indispensable element of the expert system.

When we talk about profligacy, we usually think of money, which we often spend on unnecessary things that later end up piling up in our closets. However, the other aspect of profligacy is distributed data. What kind of data is it? The kind that is collected independently, by many separate entities. You cannot expect this data to be consistent or to have one format. Using such data for reasoning, classification, or prediction is not straightforward. However, not using such data all at the same time and limiting oneself to only one set is a huge waste and a big risk of making the wrong decisions.

Distributed data are discussed in many different fields of computer science. In the issues of Federated Learning, the main focus is on data protection, no data sharing is allowed between agents/units. Local models are built, then joint decisions are made using fusion methods or meta classifiers. Cloud computing and Fog learning focus on the exchange of data across networks. Also in the Internet of Things issues, simultaneous use of distributed data, accessible from multiple devices, is extremely important.

We should be aware that the future belongs to data, and distributed data in particular. According to the Best Jobs in America survey (https://www.glassdoor.com/List/Best-Jobs-in-America-LST_KQ0,20.htm) the second most sought-after profession is Data Scientist.

Who’s that?


Come find out more 😊 and join our Computer Science degree programme.

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