The most pressing danger from AI isn't a hypothetical superintelligence but its use as a tool for societal control. The immediate risk is an Orwellian future where AI censors information, rewrites history for political agendas, and enables mass surveillance—a threat far more tangible than science fiction scenarios.

The 'P(doom)' argument is nonsensical because it lacks any plausible mechanism for how an AI could spontaneously gain agency and take over. This fear-mongering distracts from the immediate, tangible dangers of AI: mass production of fake data, political manipulation, and mass hysteria.

While public discourse often focuses on extreme scenarios like AI-driven extinction, the most pressing and tangible dangers are far more ordinary. AI-powered scamming is already a widespread, harmful application. This focus on mundane, real-world negative outcomes is more productive than speculating on distant existential threats.

Public fear of AI often focuses on dystopian, "Terminator"-like scenarios. The more immediate and realistic threat is Orwellian: governments leveraging AI to surveil, censor, and embed subtle political biases into models to control public discourse and undermine freedom.

The emphasis on long-term, unprovable risks like AI superintelligence is a strategic diversion. It shifts regulatory and safety efforts away from addressing tangible, immediate problems like model inaccuracy and security vulnerabilities, effectively resulting in a lack of meaningful oversight today.

The discourse around AI risk has matured beyond sci-fi scenarios like Terminator. The focus is now on immediate, real-world problems such as AI-induced psychosis, the impact of AI romantic companions on birth rates, and the spread of misinformation, requiring a different approach from builders and policymakers.

While the public debates data centers, the AI industry's internal anxiety has moved beyond job displacement. The focus is now on immediate security threats like AI-powered cyber weapons and potential bioweapons, along with alignment risks revealed by recent model security incidents.

Productive AI safety work isn't debating "Terminator" scenarios but building practical cybersecurity tools for immediate threats. This includes creating systems to prevent prompt injection, develop agent swarm "kill switches," and ensure provenance, treating safety as an engineering problem to be solved today.

Research shows that when people are informed about AI's existential risks, their concern for them increases without diminishing their worries about immediate harms like bias and misinformation. This counters the common belief that these two areas of concern compete in a zero-sum "attentional turf war."