A Layer-3 (network-layer) blacklist risks cutting off innocent CGNAT and cloud users. What you’re proposing is similar to mechanisms that already exist (e.g., access control lists at the ISP level work by asking computer B which requests it wants to reject and rejecting those that originate from computer A). However, implementing any large-scale blocking effort beyond the endpoint (i.e. telling an unrelated computer C to blackhole all requests from computer A to computer B) would be too computationally expensive for a use case as wide and as precise as “every computer on the Internet”.

Also, in your post you mentioned, “A host would need to have a way to identify itself as authoritative, responsible for the IP address in question.” This already happens in the form of BGP though it doesn’t provide cryptographic proof of ownership unless additional mechanisms are in use (RPKI/ROA).

I also agree that there is something that superficially seems to be supernatural. However, I believe that the reason things appear to be supernatural is because all supernatural-looking events (i.e. all correct predictions about a room) are being presented as supernatural despite random guesses accounting for a lot of these. Whether or not these events are actually supernatural may be checked by the experiment I proposed in another reply. Please do tell me your thoughts on that experiment.

Claims of the supernatural are a subset of correct claims. We can’t comment on the supernatural aspect if all we know is that a claim is correct. This is affirming the consequent.

This can be verified by asking people who have had near-death experiences whether or not they experienced something correct in their near-death experiences. Obviously, such experiences are traumatic, and multiple studies show that people can hallucinate due to the release of various neurotransmitters associated with the same.

We want to calculate the probability that someone manifested as a ghost given that they had an interesting near-death experience. We assume that anyone having a true supernatural experience experiences visions that are absolutely true. For each person, there are two possibilities (we’ll calculate the probability of each later).

The first possibility is that a person, in fact, experienced hallucinations. The second possibility is that a person experienced a ghostly manifestation.

Now, we further give people an objective multiple-choice quiz about the positions of various objects in an environment. To generate this quiz, we ask each person to choose the environment they believe themselves to have manifested in. We verify that they have never been to this environment before and did not have any method of knowing about this environment (e.g., if a subject saw a person going into a room and later gave an exact description of the person in the given room, it will be disregarded). We only test people who believe that they experienced a supernatural event. All options are framed in an equivalent manner and are presented in a randomized order to remove cognitive biases and implement double-blind protocols. We further use questions with non-obvious answers such that they differ from previous implementations (e.g., a vision of a surgery table with an overhead light is obvious, and by itself, not indicative of supernatural phenomena).

If the subject hallucinated, we assume that they have a random chance of predicting the positions of various objects. We now repeat this quiz a large number of times in accordance with the law of large numbers. If, after many repetitions, we find a sufficient deviation from the expected result (e.g., if each question had one correct answer and three incorrect answers, with the observed rate of correct answers being 50% instead of 25%), then we would have evidence supporting the existence of ghosts.

If, however, the results show no sufficient deviation from the expected results, then we would find that the probability of a perceived encounter being supernatural is approximately zero.

In this way, we can use scientific methods to test claims of ghost-like phenomena.

NOTE: If we only focus on the 25% of the cases as mentioned in the above example, we find that we are not focusing on the remaining 75% of the cases. Presenting only 25% of the cases, without giving any thought to the remaining 75% of the cases is an incorrect method of analysis as explained above.

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