Practical and Ethical Problems of Artificial Intelligence
AI systems can perpetuate and amplify existing biases in the data they are trained on. These biases can lead to discrimination in areas such as hiring, lending, and criminal justice.
AI learns patterns from historical data that frequently contain social, economic, and cultural prejudices, resulting in potentially unfair decisions.
The advancement of technologies such as facial recognition and behavior analysis raises serious concerns about individual privacy and mass surveillance.
The constant collection of data to train AI systems raises questions about informed consent and the right to privacy in the digital age.
Many advanced AI systems, especially deep neural networks, function as "black boxes" where even their creators cannot fully explain how specific decisions are made.
This lack of transparency presents fundamental challenges for accountability, especially in critical applications such as medicine or security.
As AI systems become more autonomous and powerful, concerns arise about maintaining human control over these technologies.
Advanced AI systems could develop unexpected behaviors or be vulnerable to malicious manipulations, posing substantial risks to society.
Unequal access to AI technologies could amplify existing disparities between individuals, organizations, and nations.
The concentration of power in technology companies that dominate AI development raises concerns about technological monopolies and unequal distribution of benefits.
DeepFake technology represents an unprecedented threat to the veracity of visual and audio information, enabling the creation of falsified content that is indistinguishable from reality.
Beyond political disinformation, DeepFakes facilitate devastating forms of harassment, identity theft, and psychological manipulation, eroding social trust at a time when verifying the authenticity of digital content is increasingly beyond the reach of ordinary citizens.