What does it mean to be massively against AI? (pythonbynight.com)

The author wrestles with what it means to be “massively against AI,” arguing that much of the backlash—especially on platforms like Mastodon—stems from the ambiguity and marketing-laden use of the term “AI” rather than concrete technical objections. They flip the question to expose how being “pro‑AI” can mean very different things: enthusiastically deploying LLM-driven chatbots for customer service, normalizing agentic chat companions for teens, or backing massive infrastructure investments (the post cites OpenAI’s trillion‑dollar scale) that may rely on public subsidies. That range shows why a single pro/anti label is unhelpful. For practitioners and policymakers the takeaway is practical: debate isn’t just about capabilities but about tradeoffs—workflow gains from LLMs and agentic tooling versus ethical, social and economic risks. Adoption in engineering teams is “hit or miss,” with some thoughtful technical deep dives but widespread discomfort because major companies won’t discuss AI without acknowledging harms. The piece implies the field needs clearer definitions, transparent incentives around infrastructure funding, and accountable deployment practices before many people will “wholeheartedly embrace” these tools.