I'm scared about biological computing
Experiments that hook living neurons to computers to play games like Doom are prompting unease about whether we’re inching toward creating conscious or suffering biological machines. Commenters argue over where, if anywhere, a moral line should be drawn: some compare it to existing animal agriculture and vegan ethics, others question whether small neuron cultures are meaningfully “seeing” or “playing” anything at all. Alongside concerns about hype and misinformation (often amplified by YouTube), the exchange highlights deeper uncertainty about what consciousness is, how we would recognize it in non-human substrates, and what rights or safeguards might be owed to future biologically based AIs.
Ethical analogies with animals and veganism
- Many comments compare biocomputing ethics to factory farming, breeding animals to want to be eaten, or decerebrated animals.
- Disagreement over whether vegan ethics are directly relevant: some see the core issue as sentience and suffering; others as “rigging” preferences (e.g., dogs bred to love work, hypothetical pigs bred to want to be eaten).
- Several note everyone “draws a line” (plants vs animals vs specific animals), and accuse some arguments of being inconsistent or relativistic.
- Some argue lab-grown or non-sentient substrates would largely dissolve vegan objections; others say the underlying moral questions would persist.
Consciousness and moral status
- Large subthread on whether silicon AIs and biological computers can be conscious.
- Thought experiments invoked: “China brain,” Chinese room, split-brain patients, philosophical zombies.
- Positions range from:
- Strong materialism (“consciousness emerges from physical processes; in principle anything could be conscious”),
- To hard skepticism (“consciousness is an incoherent or religiously inherited concept”),
- To views centering consciousness on emotion/brainstem and “felt homeostasis,” implying petri-dish networks are likely non-conscious.
- Debate on free will and whether humans themselves are just prediction engines / LLM-like.
Doom-playing neuron experiments
- Multiple commenters stress the neurons are not receiving raw visual input; a conventional neural network encodes game state into electrode signals and decodes outputs.
- Skepticism that the neurons are truly “seeing” or “playing Doom” versus adding structured noise; some call popular descriptions misleading or “ghost stories.”
- Others emphasize that, despite hype, there is substantive neuroscience and interesting proof-of-concept learning, especially in simpler “pong” setups without heavy preprocessing.
- A researcher-like voice explains electrode-count limitations and defends the use of autoencoders.
Prospects and fears of biological computing
- Some argue biocomputers are inevitable and vastly more energy-efficient, potentially enabling “brains in jars” and new intelligence substrates.
- Others dismiss strong extrapolations (e.g., rapid “Claude’s law” scaling, live-animal networks) as speculative or ethically horrific.
- Concern that, absent clear theories of consciousness, we risk creating suffering systems (biological or AI) without knowing where to draw ethical lines.
Media, hype, and epistemic quality
- Frustration that YouTube-driven narratives and superficial reading distort public understanding of these experiments.
- Counterpoint: books and other media can mislead too; the real issue is critical thinking and algorithmic amplification of bad ideas.