While we recently explored how data ethics and security are reshaping geopolitics, the conversation is now shifting toward where that data actually lives: the “Deep Tech” infrastructure. It is one thing to secure a social media feed, but it is quite another to engineer the backbone of Spain’s new €8 billion National Deep Tech Strategy.
We have revisited the theme of “Equidad” (Fairness) several times this year, particularly regarding mandatory licensing and clinical safety. However, the latest move by the European Union to solve the “AI copyright theft” dilemma through formal licensing adds a practical, legal layer to the ethical frameworks we discussed back in May.
At Ambiente Ingegneria, we see this through the lens of precision. Whether we are developing integrated Machine Learning solutions in Python or managing complex PostgreSQL databases, the “Deep” in Deep Tech requires a commitment to standards. In fields like bioinformatics, which is finally hitting the market with force, there is no room for error. We believe that using the metric system and rigorous SI units isn’t just a technical preference—it’s a safety requirement. A single unit conversion error in a biological AI model can have catastrophic results.
This technical rigor is also our best defense against the “cyberpunk” risks mentioned by Anthropic’s Dario Amodei. By following the European AI Act and focusing on data transparency, we can build tools that prevent the automation of fake news and online bullying. Whether it’s a custom Odoo ERP module or a React-based web app, the goal remains the same: high-quality, verified data that serves society.