Italy's Richest Man Warns: We're Training AI Systems to Make Ourselves Obsolete

Andrea Pignataro, who according to the latest rankings has overtaken Italy's traditional wealth leaders, presented a vision of the future in which human labor becomes a byproduct of technology. In his view, the economy has entered a phase of "self-destructive learning," where every interaction with digital systems serves as free training material for models striving for full autonomy. Pignataro emphasizes that this process is happening thoughtlessly, and companies chasing short-term margins risk losing control over the unique know-how that has so far been the domain of humans. „Nutriamo ogni giorno gli stessi sistemi che ci rendono superflui.” (We feed the same systems that make us superfluous every day.) — Andrea Pignataro These statements have met with mixed reactions from experts. The newspaper "Il Sole 24 ORE" described Pignataro's pessimism as a "false apocalypse," pointing out that while systemic risk exists, technology has historically created more jobs than it has eliminated. However, Pignataro's authority in the Big Data sector means his voice is treated with the utmost seriousness by digital regulations and political bodies. Fears of technology have accompanied us since the Industrial Revolution, when Luddites destroyed mechanical looms. The difference is that the current revolution strikes not at muscles, but at intellect, making social groups previously resistant to automation feel threatened. The billionaire advocates for the introduction of new legal frameworks to protect data sovereignty. He points out that without strict rules on intellectual property, Europe could become merely a supplier of informational fuel for American and Chinese giants. The controversy lies in the fact that the Ion Group, managed by Pignataro, operates at the intersection of banking and data analytics, utilizing precisely the mechanisms whose consequences its leader warns against. Nevertheless, the debate initiated by Italy's richest man could accelerate work on taxing algorithms and strengthening protection for the labor market against the uncontrolled dominance of automation.