Hanff argues that current penalties are insufficient deterrents for tech giants, who often treat fines as a cost of doing business. He advocates for stronger regulatory measures to prevent companies from profiting from illegal data practices, emphasizing the need for global treaties and enhanced legal frameworks like the EU's Digital Markets Act. Hanff plans to lobby for legislative changes in Brussels to ensure that companies respect privacy and data protection laws, aiming to prevent the repetition of past regulatory failures and protect fundamental human rights.
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- The author argues against deleting AI models trained on unlawfully obtained data due to the significant environmental impact of retraining them.
- Proposes placing AI models into the public domain if they are found to have been trained unlawfully, as a deterrent to companies profiting from illegal data usage.
- Highlights the need for global cooperation and stronger legal frameworks to enforce compliance with data protection laws and prevent unlawful AI training.
- Emphasizes the importance of learning from past regulatory failures to ensure effective deterrents and consequences for companies that violate legal obligations.