What problems does the AI Act aim to solve?
An analysis of the key challenges the AI Act addresses - from algorithmic discrimination and lack of transparency to the need for accountability in AI decision-making systems.
In recent years, artificial intelligence has moved from experimental technology to infrastructure used in many economic sectors.
Companies use AI systems to analyze large amounts of data, automate tasks, and support strategic decisions.
This evolution has brought new opportunities, but also a series of risks that have attracted the attention of legislators.
It is precisely to address these critical issues that the Artificial Intelligence Act was introduced.
The problem of algorithmic discrimination
One of the most discussed risks concerns the possibility that an AI system produces discriminatory results.
This can happen when the data used to train the algorithm reflects biases already present in reality.
In these cases, the system can amplify these distortions instead of correcting them.
Transparency and accountability
Another problem concerns the difficulty in understanding how some AI systems make decisions.
Many advanced models function as true "black boxes", making it complex to explain why a particular decision was made.
The AI Act therefore introduces rules aimed at improving transparency and accountability in the use of artificial intelligence.
Conclusion
The goal of the regulation is not to limit innovation, but to create a framework of trust that allows companies to develop and use AI systems in a safe and responsible manner.