Recently developed large language models (LLMs) perform surprisingly well in many language-related tasks, ranging from text correction or authentic chat experiences to the production of entirely new texts or even essays. It is natural to get the impression that LLMs know the meaning of natural language expressions and can use them productively. Recent scholarship, however, has questioned the validity of this impression, arguing that LLMs are ultimately incapable of understanding and producing meaningful texts. This paper develops a more optimistic view. (...) Drawing on classic externalist accounts of reference, it argues that LLM-generated texts meet the conditions of successful reference. This holds at least for proper names and so-called paradigm terms. The key insight here is that the LLM may inherit reference from its training-data through a reference-sustaining training mechanism. (shrink)

Human extinction is something generally deemed as undesirable, although some scholars view it as a potential solution to the problems of the Earth since it would reduce the moral evil and the suffering that are brought about by humans. We contend that humans collectively have absolute intrinsic value as sentient, conscious and rational entities, and we should preserve them from extinction. However, severe threats, such as climate change and incurable viruses, might push humanity to the brink of extinction. Should that (...) occur, it might be useful to envision a successor to humans able to preserve and hand down its value. One option would be to resort to humanoid robots that reproduce our salient characteristics by imitation, thanks to AI powered by machine learning. However, the question would arise of how to select the characteristics needed for our successors to thrive. This could prove to be particularly challenging. A way out might come from an algorithm entrusted with this choice. In fact, an algorithmic selection both at the social and at the individual level could be a preferred choice than other traditional ways of making decisions. In this sense, reflecting on human extinction helps us to identify solutions that are also suitable for the problems we face today. (shrink)