Exploring Medical Breakthroughs: A Systematic Review of ChatGPT Applications in Healthcare

ChatGPT, a large language model developed by OpenAI, has emerged as a powerful tool in the field of medicine. In this systematic review, we explore the potential of ChatGPT in various medical applications by analyzing articles related to medicine and healthcare. We carefully examined the methodologies, results, and conclusions of these articles to provide a comprehensive overview of the current evidence on the use of ChatGPT in the field of medicine. Through this review, we highlight how ChatGPT has been utilized to streamline and simplify complex tasks, improve patient care, enhance clinical decision-making, and facilitate communication among healthcare professionals. We also discuss the challenges and limitations of using ChatGPT in medicine, including concerns related to privacy, ethical considerations, and potential biases. Despite these challenges, ChatGPT has shown great promise in transforming the landscape of medicine and has the potential to revolutionize healthcare delivery. By synthesizing the findings from these articles, we aim to provide a critical and evidence-based evaluation of the current state of ChatGPT in medicine, and to identify areas for further research and development

Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment

Ensuring alignment, which refers to making models behave in accordance with human intentions [1,2], has become a critical task before deploying large language models (LLMs) in real-world applications. For instance, OpenAI devoted six months to iteratively aligning GPT-4 before its release [3]. However, a major challenge faced by practitioners is the lack of clear guidance on evaluating whether LLM outputs align with social norms, values, and regulations. This obstacle hinders systematic iteration and deployment of LLMs. To address this issue, this paper presents a comprehensive survey of key dimensions that are crucial to consider when assessing LLM trustworthiness. The survey covers seven major categories of LLM trustworthiness: reliability, safety, fairness, resistance to misuse, explainability and reasoning, adherence to social norms, and robustness. Each major category is further divided into several sub-categories, resulting in a total of 29 sub-categories. Additionally, a subset of 8 sub-categories is selected for further investigation, where corresponding measurement studies are designed and conducted on several widely-used LLMs. The measurement results indicate that, in general, more aligned models tend to perform better in terms of overall trustworthiness. However, the effectiveness of alignment varies across the different trustworthiness categories considered. This highlights the importance of conducting more fine-grained analyses, testing, and making continuous improvements on LLM alignment. By shedding light on these key dimensions of LLM trustworthiness, this paper aims to provide valuable insights and guidance to practitioners in the field. Understanding and addressing these concerns will be crucial in achieving reliable and ethically sound deployment of LLMs in various applications

Aspiring india: The Politics of Mothering, Education Reforms, and English

This dissertation is an ethnography of aspirational mobilities emergent under contexts of profound material and social change. To explore the unprecedented expansion of educational aspirations in post market reform India, specifically surging parental desires for English-medium schooling, I conducted fieldwork at a low-fee private English-medium school and a neighboring state-funded Malayalam-medium school in the southern Indian state of Kerala. Further, to record state responses to non-elite educational aspirations, my fieldwork was distributed along diverse agencies that supported and regulated English learning in Kerala and across the country. This dissertation makes two key arguments. Firstly, transitions from a previously austere socialist economy to a consumption saturated society has radically altered gendered everyday lives and unsettled entrenched social hierarchies. Negotiating these changes, non-elite mothers are reimagining possible futures for their children. Since social recognition and economic security was and continues to be entangled with higher education and English proficiencies, this has intensified desires for English-medium schooling from the earliest grades. Secondly, intensifying non-elite desires for English learning reveals how educational systems in India are geared towards meeting the aspirations of privileged citizens. Analyzing the provision of English language learning in state-funded and private school systems, I argue that emergent emphases on conversational skills defines “knowing” English as predicated on the ability to socialize in English. While this shift benefits internationally mobile elite Indians, it marginalizes non-elite learning communities whose pedagogic resources are skewed towards literacy rather than orality skills. To conclude, aspirational mobilities in contemporary India are diverse and even oppositional, and dependent on aspirational locations as well as the resources that groups are able to mobilize

An Exploratory Study on How Math Stories Engage Young Learners in Mathematical Sense-Making

This is an exploratory study of how pedagogy in the form of math stories, shapes young learners’ perceptions, motivations, and sense-making of math concepts. The research is presented in an exploratory documentary, with audio-video data collected through the iPhone. The pilot test of story-driven math learning solutions was conducted by two teachers with eight first grade children from diverse backgrounds in an afterschool program. This study also includes interviews of the teachers, educational leaders and specialists in primary school curricula, children’s literature, and math education. The results of the pilot validated the efficacy of story-driven math learning solutions for mathematical sensemaking and reasoning. By helping the characters students were empowered as young mathematicians. They were motivated and engaged in mathematical modeling, for example, building equations deepened understanding from concrete problems to abstract concepts. The teachers observed the accelerated rate of students’ learning through stories, games, and multimodal activities shaped by a creative, socially interactive, and culturally responsive pedagogy not typically used in their math classes

Economic Espionage as Reality or Rhetoric: Equating Trade Secrecy with National Security

In the last few years, the Economic Espionage Act (EEA), a 1996 statute that criminalizes trade secrecy misappropriation, was amended twice, once to increase the penalties and once to expand the definition of trade secrets and the types of behaviors that are illegal. Recent developments also reveal a pattern of expansion in investigation, indictments, and convictions under the EEA as well as the devotion of large resources by the FBI and other agencies to warn private industry against the global threats of trade secret theft. At the international level, the United States government has been advocating enhanced levels of trade secrecy protection in new regional trade agreements This article asks about the effects these developments on innovation. The article examines the rhetoric the government is using to promote its trade secrecy agenda, uncovering that the argument for greater protection appears to derive at least some of its power from xenophobia, and most importantly, from a conflation of private economic interests with national security concerns, interjecting a new dimension to the moral component of innovation policy debates. Analyzing recent empirical research about innovation policy, we ask about the effects of these recent trends on university research and on private market innovation, including entrepreneurship, information flows and job mobility. We argue that, paradoxically, the effort to protect valuable information and retain the United States’ leadership position could disrupt information flows, interfere with collaborative efforts, and ultimately undermine the inventive capacity of American innovators. The article offers suggestions for reconciling legitimate concerns about national security with the balance intellectual property law traditionally seeks to strike between incentivizing innovation and ensuring the vibrancy of the creative environment. We conclude that a legal regime aimed at protecting incumbency is not one that can also optimally foster innovation