1. Here is the subset: any algorithm, which is learning based, trained on a large data set, and modifies or generates content.

2. I would argue that translation engines have their positives and negatives, but a lot of them are negative, because they lead to translators losing their jobs, and a loss in general for the magical qualities of language learning.

3. Predictive text: I think people should not be presented with possible next words, and think of them on their own, because that means they will be more thoughtful in their writing and less automatic. Also, with a higher barrier to writing something, they will probably write less and what they do write will be of greater significance.

4. I am against all LLMs, including wildlife camera trap analysis. There is an overabundance of hiding behind research when we really already know the problem fairly well. It's a fringe piece of conservation research anyway.

5. Visual impairments: one can always appeal to helping the disabled and impaired, but I think the tradeoff is not worth the technological enslavement.

6. My problem is categorically with AI, not with how it is applied, PRECISELY BECAUSE AI cannot be applied in an ethical way, since human beings en masse will inevitably have a sufficient number of bad actors to make the net effect always negative. It's human nature.