How fearmongering sets policy, from ‘marihuana’ to solar to A.I.

This article generally aligns with a Center Left point of view. Learn more about this AI-generated analysis

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Ideas expressed in the piece

• The column contends that fearmongering and misinformation have repeatedly driven U.S. policy on emerging technologies, from marijuana to solar power to electric vehicles, leading the country to forfeit rather than lose leadership in major industries.
• The piece argues that political decisions around cannabis blurred the line between hemp as an industrial fiber and marijuana as a drug, allowing stigma and sensationalist narratives to suppress a promising material and its associated jobs for decades.
• The article maintains that similar patterns played out with clean energy, pointing to the removal of President Carter’s White House solar panels as an early sign that short-term politics and incumbent interests undercut U.S. leadership in solar manufacturing and supply chains, enabling foreign competitors to dominate that market.
• The column suggests that corporate lobbying, campaign donations, and public resistance all likely contributed to the demise of early electric vehicle efforts such as GM’s EV1, and it emphasizes that even decision-makers later expressed regret for abandoning the technology too soon.
• The piece draws a parallel between these historical examples and the current fight over AI and data centers, stressing that federal agencies — particularly the Defense Department — are already deeply invested in AI, so the public is effectively tied to the technology whether or not communities welcome new facilities.
• The article expresses unease about whether AI will become a broadly beneficial disruptive technology or primarily a tool to further enrich the wealthiest, and it urges readers to scrutinize whose interests are shaping both the promotion of AI and the backlash against it.
• The column ultimately argues that, just as with hemp and solar power, policymakers must separate fact from myth and resist scare tactics when regulating AI and data centers, or risk repeating past mistakes of allowing fear and misinformation to set the rules for transformational technologies.

Different views on the topic

• Some policy analysts argue that concern about AI is not simply hysteria but a rational response to genuine risks such as dual-use military applications, cyber threats, and economic vulnerabilities; these perspectives emphasize that governments, including the United States, must treat AI as a core economic security issue and carefully manage its adoption rather than focusing primarily on lost commercial opportunities^[4].
• In contrast to the column’s focus on fear-driven forfeiture, other experts highlight the long history of the U.S. government actively driving innovation through research funding and procurement, suggesting that public investment and strategic oversight — not just avoiding fearmongering — are central to maintaining technological leadership^[3].
• Research on AI-generated misinformation contends that new systems can rapidly spread false or misleading content, undermining public trust and democratic processes; scholars in this field argue that narratives warning about these harms reflect evidence-based worries and justify robust countermeasures such as inoculation strategies and systematic debunking, rather than being dismissed as mere doomsday storytelling^[2].
• Digital policy advocates at pro-innovation think tanks contend that the bigger danger is not that fearmongering will block AI, but that overbroad or poorly designed regulations will slow beneficial innovation; these analyses credit earlier U.S. digital leadership to a “light-touch” regulatory approach and call for similarly flexible rules that protect rights without treating every new application as a looming catastrophe^[5].
• Fact-checking organizations reviewing viral claims about AI training on personal data report that public anxiety is often fueled by misunderstandings about how companies access and use information, yet they also identify concrete privacy gaps; this work suggests that parts of the debate reflect legitimate consumer protection concerns, not only sensationalism, and that detailed transparency requirements may be as important as challenging exaggerated rhetoric^[1].
• Some economic and security commentators argue that the primary policy failure would be allowing rapid, largely unregulated deployment of AI systems that could destabilize labor markets, concentrate power, or empower adversaries; these voices see stricter guardrails and slower rollout as prudent governance, even if such caution risks ceding some market share, and therefore push back on narratives that frame restraint itself as a repeat of past technological “forfeits”^[4].