人文科学最新文献

This research explored the strategic beliefs that people have about science and the extent to which it can explain moral and immoral behaviors. Although people do not believe that science is able to explain certain aspects of their mind, they might nevertheless accept a scientific explanation for their immoral behaviors if that explanation is exculpatory. In a first study, participants reflected on moral and immoral deeds that they performed or that other people performed. Participants were somewhat skeptic that science can account for people's behavior-except for when they reflected on the wrongdoings that they committed. Two further studies suggest that strategic belief in science arises because it enables external attributions for the behavior, outside of the wrongdoers' control. Implications are discussed for science understanding and communication.

Since its launch in November 2022, ChatGPT has become a global phenomenon, sparking widespread public interest in chatbot artificial intelligences (AIs) generally. While not approved for medical use, it is capable of passing all three United States medical licensing exams and offers diagnostic accuracy comparable to a human doctor. It seems inevitable that it, and tools like it, are and will be used by the general public to provide medical diagnostic information or treatment plans. Before we are taken in by the promise of a golden age for chatbot medical AIs, it would be wise to consider the implications of using these tools as either supplements to, or substitutes for, human doctors. With the rise of publicly available chatbot AIs, there has been a keen focus on research into the diagnostic accuracy of these tools. This, however, has left a notable gap in our understanding of the implications for health outcomes of these tools. Diagnosis accuracy is only part of good health care. For example, crucial to positive health outcomes is the doctor-patient relationship. This paper challenges the recent focus on diagnostic accuracy by drawing attention to the causal relationship between doctor-patient relationships and health outcomes arguing that chatbot AIs may even hinder outcomes in numerous ways including subtracting the elements of perception and observation that are crucial to clinical consultations. The paper offers brief suggestions to improve chatbot medical AIs so as to positively impact health outcomes.

There is an ongoing debate about the ethics of research on lifespan extension: roughly, using medical technologies to extend biological human lives beyond the current "natural" limit of about 120 years. At the same time, there is an exploding interest in the use of artificial intelligence (AI) to create "digital twins" of persons, for example by fine-tuning large language models on data specific to particular individuals. In this paper, we consider whether digital twins (or digital doppelgängers, as we refer to them) could be a path toward a kind of life extension-or more precisely, a kind of person extension-that does not rely on biological continuity. We discuss relevant accounts of consciousness and personal identity and argue that digital doppelgängers may at least help us achieve some of the aims or ostensible goods of person-span extension, even if they may not count as literal extensions of our personhood on dominant philosophical accounts. We also consider relational accounts of personhood and discuss how digital doppelgängers may be able to extend personhood in a relational sense, or at least secure some of the goods associated with relevant relationships. We conclude by suggesting that a research program to investigate such issues is relevant to ongoing debates about the ethics of extending the human lifespan.

This letter focuses on the importance of incorporating implicit bias into research integrity education, and the significant impact it can have on creating an equitable research environment.

The publish or perish concept requires academics to ensure that they take part in research and publish the research results in academic journals. The emergency of predatory publishers has led to negativity in the scholarly publishing process. Some researchers are unaware that some publishers are unethical. A study was conducted to determine the extent of predatory publishing in Zimbabwe among academics. A survey was carried out using a multi-method approach at a public university in Zimbabwe. Articles published between 2012 and 2022 were retrieved using the Harzing publish or perish software. In total, 977 articles were retrieved, and after data cleaning using Open Refine, 357 records were analyzed using the journal evaluation rubric and scoring sheet to note the extent of predatory publishing among the various schools. The articles were then classified into 3 sections i.e., predatory, not predatory, and borderline. The findings revealed that predatory publishing is prevalent in the social sciences. The authors recommend the importance of training to create awareness about the dangers of predatory publishing and how to avoid them to improve the scholarly output of the institution, which is key to university ranking.

Yamada and Teixeira da Silva voiced valid concerns with the inadequacies of an online machine learning-based tool to detect predatory journals, and stressed on the urgent need for an automated, open, online-based semi-quantitative system that measures "predatoriness". We agree that the said machine learning-based tool lacks accuracy in its demarcation and identification of journals outside those already found within existing black and white lists, and that its use could have undesirable impact on the community. We note further that the key characteristic of journals being predatory, namely a lack of stringent peer review, would normally not have the visibility necessary for training and informing machine learning-based online tools. This, together with the gray zone of inadequate scholarly practice and the plurality in authors' perception of predatoriness, makes it desirable for any machine-based, quantitative assessment to be complemented or moderated by a community-based, qualitative assessment that would do more justice to both journals and authors.

Current clinical research lacks diversity in those that participate. This lack of diversity is concerning given its importance for successful drug development. The frequency and severity of many diseases, along with the pharmacological properties of therapies, can display significant differences based on patient diversity. A clinical trial population that is more reflective of these differences will help researchers better understand the therapeutic profile of the treatment and provide generalizable knowledge to the medical community. The advent of decentralized clinical trial designs is meant to help address this lack of diversity by using portable digital health technologies and virtual interactions to enhance clinical trial access and broaden participation. By leveraging these technologies, trial conduct can occur at locations other than traditional research sites. This shift in trial location may help address some of the logistical, educational, engagement, and trust barriers that have historically prevented enrollment of diverse populations. However, these types of trials still have limitations. Ethical concerns around justice, equity, and diversity will still exist with decentralized clinical trials, which could be mediated using clinical research vehicles. When utilized, this modality may enhance the scientific design and conduct of clinical trials and better follow these ethical principles. These enhancements and improved ethical direction could be accomplished through increasing community involvement, improving health literacy, supporting more diverse trial sites, creating community-based research footholds, fostering connections with researchers, limiting technical challenges, and preventing data security issues.