A Pascal's Wager for AI doomers
Fears of a future superintelligent, godlike AI are weighed against more immediate concerns about how current large language models and corporate-controlled tech already shape economies, politics, and everyday life. Commenters argue over whether today’s “mere statistics” systems count as intelligent, how powerful AI can realistically become, and whether the real existential risks stem less from hypothetical rogue AIs than from concentrated corporate power, financial bubbles, and overconfident deployment of imperfect tools. Many see AI as both genuinely transformative and hazardous, urging attention to present harms and governance rather than only to speculative doomsday scenarios.
Nature of AI Intelligence
- Debate over whether LLMs count as “intelligent” or just advanced statistics.
- Some argue emergent internal representations and adaptability qualify as intelligence or at least “cognition,” even if constrained to language.
- Others emphasize we barely understand animal and human intelligence, so declaring language-only models “intelligent” is premature.
- Comparisons made to animal cognition: many non-linguistic animals are clearly intelligent; language may merely “supercharge” preexisting intelligence.
Superintelligence, Power, and Doomerism
- Skeptics argue superintelligent AI is speculative; extraordinary claims need evidence, and current systems still make obvious mistakes.
- Strong criticism of the assumption that higher intelligence automatically yields “godlike” control over complex, nonlinear systems.
- Counterpoint: human intelligence already gives species-level dominance; scaled-up, copyable intelligence with persistent operation and mass propaganda could be qualitatively different.
- Some note that political and institutional power, not lack of brainpower, is the real bottleneck; society already ignores human experts.
Current Capabilities and Limitations
- Many report large productivity gains, especially in coding, troubleshooting, and translation.
- Others see frequent bad judgment, hallucinations, and lack of initiative or stable principles, requiring heavy testing and oversight.
- Disagreement over long‑term trajectory: some expect continued rapid gains; others note perceived regressions and cost pressures.
Economic Bubble and Corporate Dynamics
- Dispute over whether AI spending is a dangerous bubble with circular financing vs. a healthy risk-taking sector driving innovation.
- Concern that huge capex and valuations aren’t yet matched by real value, especially in frontier models, while narrower tools (transcription, summarization, image description) seem solid.
- Some fear systemic fragility; others point to historical bubbles that still left useful infrastructure and capabilities.
Social, Political, and Infrastructure Effects
- Worry that AI acts as mass-access “yes-men,” reinforcing user egos and elite worldviews.
- Concerns about AI-driven scams, astroturfing, psychosis induction, and over-automation of control functions in critical systems.
- Parallel discussion on escaping the “enshittened” internet via home servers and community tech support, possibly aided by local AI assistants.
- Several commenters argue it’s a false choice: we can be concerned both about current corporate harms and future high-end AI risks.