This paper examines whether contemporary generative artificial intelligence (GAI), especially large language models (LLMs), can be regarded as a “cognitive subject” in the epistemic sense relevant to the production and endorsement of knowledge claims. GAI systems increasingly participate in writing, research, and decision-making workflows and can display striking competence in information processing and task-directed problem solving. Yet, the thesis that GAI is a cognitive subject is stronger than the observation that GAI contributes as a cognitive tool. Therefore, we propose an explicit set of necessary and sufficient conditions for cognitive subjecthood and evaluate each condition in light of recent philosophical and empirical scholarship. The analysis supports a two-part conclusion: (i) present-day GAI can reasonably be described as a cognitively significant contributor to knowledge production, but (ii) it does not satisfy the conditions for cognitive subjecthood , largely because robust intentionality, metacognitive self-representation, and consciousness-related indicator properties are not established.

Ethical issues in the contemporary Chinese fundraising industry are increasingly foregrounded, and effective governance has emerged as a particularly important and urgent priority. However, this issue has not received sufficient theoretical and practical attention. We apply a range of tools (factual and value-based, inductive and deductive approaches; historical and logical dialectics; and comparative analysis) to briefly describe the historical development of domestic and international fundraising ethics. We clarify its importance by drawing on a factual description of the main ethical issues in the fundraising industry. A comparative analysis of the three main ethical theories of utilitarianism, deontology and virtue ethics reveals that virtue ethics is more adaptable in guiding fundraising behavior in contemporary China. In order to effectively address the many ethical issues in the fundraising industry, we argue that a process approach should be adopted that draws on a virtue ethics perspective, which focuses on the character of fundraisers at the time of qualification. We optimize the code of fundraising ethics by drawing on a combination of character and normative provisions, and regulate fundraising behavior, which enables us to shape fundraisers’ professional virtues. Fundraising performance is evaluated by referring to fundraising results, motivation and emotion. We find that while there are still some ethical dilemmas and conflicts in the fundraising industry, issues of good and evil, right and wrong and value ranking still lack a consensus and are open-ended. Future research needs to address this limitation.

In the contemporary realm of digital art, generative AI (GAI) systems, including text-to-image models, produce high-quality artworks within seconds, thereby disrupting the existing digital art ecosystem. This raises a pivotal question: can generative AI be regarded as an aesthetic subject? This inquiry represents a frontier issue situated at the crossroads of analytical aesthetics and neuroscience. An aesthetic subject is defined by the universal and non-utilitarian character of the emotions, pleasure, and judgments experienced during the aesthetic process. To determine whether generative AI qualifies as an aesthetic subject, reliance on mere intuition or technological observations is insufficient. Rather, it is necessary to revisit the notion of the “aesthetic subject” rooted in analytical philosophy and integrate it with recent advancements in neuroaesthetic evidence. This study examines the problem through seven lenses—aesthetic judgment; emotional internality; artistic imaginativity; meaning; artistic creativity; consciousness; and intentionality—while also comparing aesthetic functions with fundamental aesthetic distinctions. It provides a prudent evaluation of this matter. Specifically, the analysis proceeds from the simplest to the most complex components to determine their verifiability or falsifiability; subsequently, by integrating these findings, a comprehensive conclusion is drawn regarding the status of generative AI as an aesthetic subject. Adopting a stance of weak epistemology and utilizing the aforementioned theoretical framework, this paper concludes that, at present, generative artificial intelligence cannot be considered an aesthetic subject.