in ,

AI’s deceptive use in criminal schemes through generative models. #DeceptiveAI

mm

Generative AI, a subset of Artificial Intelligence, has gained prominence for its ability to generate human-like text, images, and audio from vast datasets. However, there is a dark side to Generative AI, as it can be used for deceptive activities by cybercriminals. Phishing emails, financial fraud, social engineering attacks, doxxing, and deepfakes are some of the criminal activities fueled by Generative AI. The misuse of Generative AI has led to significant incidents with critical impacts, such as deepfake scams and political manipulation.

To address the deceptive use of AI-driven generative models, mitigation strategies involving improved safety measures and collaboration among stakeholders are necessary. Human reviewers and automated systems can help detect and prevent fraudulent activities. Collaboration between tech companies, law enforcement agencies, and policymakers is crucial in combating AI-driven deceptions. Looking ahead, education on ethical AI development and the implementation of robust regulatory frameworks are essential to combat the growing threat of AI-driven deception.

In conclusion, while Generative AI offers benefits, it also poses risks that require effective mitigation strategies and ethical AI development practices to ensure a safer technological environment for the future. Balancing innovation with security, promoting transparency, and designing AI models with built-in safeguards are key to addressing the challenges posed by AI-driven deception.

Source link

Source link: https://www.unite.ai/deceptive-ai-exploiting-generative-models-in-criminal-schemes/

What do you think?

Leave a Reply

GIPHY App Key not set. Please check settings

Siri and Google Assistant look to generative AI for a new lease on life

#Siri and Google Assistant turn to generative AI for renewal. #DigitalAssistants

Shallow Neural Networks. Shallow neural networks, a subset of… | by Calin Sandu | Jun, 2024

Subset of neural networks with limited hidden layers. #ShallowNeuralNetworks