After a crisis, regulation is popular. But as memory fades and regulations work, they are increasingly seen as unnecessary hindrances. This amnesia creates a cyclical push for deregulation that sows the seeds of the next crisis.
Positive macroeconomic indicators mask the reality that over half of Americans live paycheck-to-paycheck. This "economic precarity" should be the central problem to solve. Instead, it's often a vulnerability that FinTech companies are designed to exploit for profit.
Funded by tech elites, the "abundance" movement uses appealing goals like building more housing to mask a broader deregulatory agenda. This agenda likely prioritizes the profits of its billionaire backers over public protections for the economically vulnerable.
The belief that technology can solve any problem is dangerous. It dismisses experts' knowledge and the possibility that a tech solution is not feasible, as seen with Theranos. This mindset funds fraudulent or absurd ideas while ignoring practical, human-centered solutions.
The narrative that new financial products are "innovative" is often used to argue against regulation, echoing the same rhetoric that led to the 2008 crisis. This skepticism towards "innovation speak" is crucial as Silicon Valley's language infiltrates finance.
Despite a public image of libertarian self-reliance, the VC industry's success is built on government support. This includes leveraging state-funded R&D (the internet), lobbying for favorable tax laws (carried interest), and accessing pension funds through legal changes.
In a tough economy, companies use AI as a public relations excuse for layoffs or hiring freezes. Claiming that jobs are being replaced by AI sounds more innovative and forward-thinking than simply admitting to financial struggles. This 'AI washing' obscures the true state of the business.
Many FinTech innovations, from crypto to payday lending apps, don't succeed because their technology is superior. Instead, their primary value comes from designing business models that exploit or circumvent existing financial regulations, giving them an unfair advantage over incumbents.
When junior employees are encouraged to use AI from day one, they fail to develop foundational skills. This "deskilling" means they won't be able to spot AI hallucinations or errors, ironically making them less competent and more liable, particularly in fields like law.
Contrary to popular belief, generative AI like LLMs may not get significantly more accurate. As statistical engines that predict the next most likely word, they lack true reasoning or an understanding of "accuracy." This fundamental limitation means they will always be prone to making unfixable mistakes.
The crypto market should have collapsed in 2022, but VCs like Andreessen Horowitz pivoted from funding startups to funding aggressive lobbying. This political spending created favorable laws, giving a patina of legitimacy to an industry whose business models were unviable under existing securities laws.