From Human-Centered to Social-Centered Artificial Intelligence: Assessing ChatGPT's Impact through Disruptive Events

Large language models (LLMs) and dialogue agents have existed for years, but the release of recent GPT models has been a watershed moment for artificial intelligence (AI) research and society at large. Immediately recognized for its generative capabilities and versatility, ChatGPT's impressive proficiency across technical and creative domains led to its widespread adoption. While society grapples with the emerging cultural impacts of ChatGPT, critiques of ChatGPT's impact within the machine learning community have coalesced around its performance or other conventional Responsible AI evaluations relating to bias, toxicity, and 'hallucination.' We argue that these latter critiques draw heavily on a particular conceptualization of the 'human-centered' framework, which tends to cast atomized individuals as the key recipients of both the benefits and detriments of technology. In this article, we direct attention to another dimension of LLMs and dialogue agents' impact: their effect on social groups, institutions, and accompanying norms and practices. By illustrating ChatGPT's social impact through three disruptive events, we challenge individualistic approaches in AI development and contribute to ongoing debates around the ethical and responsible implementation of AI systems. We hope this effort will call attention to more comprehensive and longitudinal evaluation tools and compel technologists to go beyond human-centered thinking and ground their efforts through social-centered AI

Longitudinal links between expressive flexibility and friendship quality in adolescence: The moderating effect of social anxiety

Introduction Expressive flexibility, or the ability to both up- and down-regulate emotional expressions in social interactions, is thought as an indicator and a consequence of healthy interpersonal relationships. The present longitudinal study examined bidirectional associations between expressive flexibility and friendship quality in early adolescence. Since prior research found inconsistent results regarding the adaptiveness of expressive flexibility, which indicated the necessity to consider individual variability in the process, we further tested the potential moderating effect of social anxiety in the links from expressive flexibility to friendship quality. Methods Participants from two junior high schools in eastern China (N = 274; 50.4% female; Mage = 13.56) were surveyed at three time points with 6-month intervals. Expressive flexibility, friendship quality, and social anxiety were all assessed via self-reported scales. Results According to the cross-lagged model results, friendship quality significantly predicted increased expressive flexibility over time. Conversely, the longitudinal association from expressive flexibility to friendship quality was not significant, but the interaction between expressive flexibility and social anxiety significantly predicted later friendship quality. Further analyses via the Johnson–Neyman technique revealed that expressive flexibility only positively predicted friendship quality for adolescents with lower levels of social anxiety. Conclusion Our results suggest that expressive flexibility is not always socially adaptive, so practical interventions that aim to improve youths' social adjustment via expressive flexibility training might need to consider the role of individual characteristics

Prompting Large Language Models to Generate Code-Mixed Texts: The Case of South East Asian Languages

While code-mixing is a common linguistic practice in many parts of the world, collecting high-quality and low-cost code-mixed data remains a challenge for natural language processing (NLP) research. The proliferation of Large Language Models (LLMs) in recent times compels one to ask: can these systems be used for data generation? In this article, we explore prompting LLMs in a zero-shot manner to create code-mixed data for five languages in South East Asia (SEA) -- Indonesian, Malay, Chinese, Tagalog, Vietnamese, as well as the creole language Singlish. We find that ChatGPT shows the most potential, capable of producing code-mixed text 68% of the time when the term "code-mixing" is explicitly defined. Moreover, both ChatGPT and InstructGPT's (davinci-003) performances in generating Singlish texts are noteworthy, averaging a 96% success rate across a variety of prompts. The code-mixing proficiency of ChatGPT and InstructGPT, however, is dampened by word choice errors that lead to semantic inaccuracies. Other multilingual models such as BLOOMZ and Flan-T5-XXL are unable to produce code-mixed texts altogether. By highlighting the limited promises of LLMs in a specific form of low-resource data generation, we call for a measured approach when applying similar techniques to other data-scarce NLP contexts

Oral Insulin

Oral insulin is an exciting area of research and development in the field of diabetology. This brief review covers the various approaches used in the development of oral insulin, and highlights some of the recent data related to novel oral insulin preparation

Glycaemic control in people with type 2 diabetes mellitus during and after cancer treatment: A systematic review and meta-analysis

Background Cancer and Diabetes Mellitus (DM) are leading causes of death worldwide and the prevalence of both is escalating. People with co-morbid cancer and DM have increased morbidity and premature mortality compared with cancer patients with no DM. The reasons for this are likely to be multifaceted but will include the impact of hypo/hyperglycaemia and diabetes therapies on cancer treatment and disease progression. A useful step toward addressing this disparity in treatment outcomes is to establish the impact of cancer treatment on diabetes control. Aim The aim of this review is to identify and analyse current evidence reporting glycaemic control (HbA1c) during and after cancer treatment. Methods Systematic searches of published quantitative research relating to comorbid cancer and type 2 diabetes mellitus were conducted using databases, including Medline, Embase, PsychINFO, CINAHL and Web of Science (February 2017). Full text publications were eligible for inclusion if they: were quantitative, published in English language, investigated the effects of cancer treatment on glycaemic control, reported HbA1c (%/mmols/mol) and included adult populations with diabetes. Means, standard deviations and sample sizes were extracted from each paper; missing standard deviations were imputed. The completed datasets were analysed using a random effects model. A mixed-effects analysis was undertaken to calculate mean HbA1c (%/mmols/mol) change over three time periods compared to baseline. Results The available literature exploring glycaemic control post-diagnosis was mixed. There was increased risk of poor glycaemic control during this time if studies of surgical treatment for gastric cancer are excluded, with significant differences between baseline and 12 months (p < 0.001) and baseline and 24 months (p = 0.002). Conclusion We found some evidence to support the contention that glycaemic control during and/or after non-surgical cancer treatment is worsened, and the reasons are not well defined in individual studies. Future studies should consider the reasons why this is the case

Estimating Plasma Glucose from Interstitial Glucose: The Issue of Calibration Algorithms in Commercial Continuous Glucose Monitoring Devices

Evaluation of metabolic control of diabetic people has been classically performed measuring glucose concentrations in blood samples. Due to the potential improvement it offers in diabetes care, continuous glucose monitoring (CGM) in the subcutaneous tissue is gaining popularity among both patients and physicians. However, devices for CGM measure glucose concentration in compartments other than blood, usually the interstitial space. This means that CGM need calibration against blood glucose values, and the accuracy of the estimation of blood glucose will also depend on the calibration algorithm. The complexity of the relationship between glucose dynamics in blood and the interstitial space, contrasts with the simplistic approach of calibration algorithms currently implemented in commercial CGM devices, translating in suboptimal accuracy. The present review will analyze the issue of calibration algorithms for CGM, focusing exclusively on the commercially available glucose sensors

SeamlessM4T-Massively Multilingual & Multimodal Machine Translation

What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages? While recent breakthroughs in text-based models have pushed machine translation coverage beyond 200 languages, unified speech-to-speech translation models have yet to achieve similar strides. More specifically, conventional speech-to-speech translation systems rely on cascaded systems that perform translation progressively, putting high-performing unified systems out of reach. To address these gaps, we introduce SeamlessM4T, a single model that supports speech-to-speech translation, speech-to-text translation, text-to-speech translation, text-to-text translation, and automatic speech recognition for up to 100 languages. To build this, we used 1 million hours of open speech audio data to learn self-supervised speech representations with w2v-BERT 2.0. Subsequently, we created a multimodal corpus of automatically aligned speech translations. Filtered and combined with human-labeled and pseudo-labeled data, we developed the first multilingual system capable of translating from and into English for both speech and text. On FLEURS, SeamlessM4T sets a new standard for translations into multiple target languages, achieving an improvement of 20% BLEU over the previous SOTA in direct speech-to-text translation. Compared to strong cascaded models, SeamlessM4T improves the quality of into-English translation by 1.3 BLEU points in speech-to-text and by 2.6 ASR-BLEU points in speech-to-speech. Tested for robustness, our system performs better against background noises and speaker variations in speech-to-text tasks compared to the current SOTA model. Critically, we evaluated SeamlessM4T on gender bias and added toxicity to assess translation safety. Finally, all contributions in this work are open-sourced and accessible at https://github.com/facebookresearch/seamless_communicatio

Pyridoacridines in the 21st Century

This minireview summarizes the work developed during this Century with compounds containing the pyridoacridine scaffold in its different isomeric forms. The isolation of natural products, syntheses, bioactivities, chelation capacity, and other properties of compounds containing this framework are discussed. For reasons of length, only compounds containing a maximum of seven condensed rings have been considered, with a few exceptions

Early- and advanced non-enzymatic glycation in diabetic vascular complications: the search for therapeutics

Cardiovascular disease is a common complication of diabetes and the leading cause of death among people with diabetes. Because of the huge premature morbidity and mortality associated with diabetes, prevention of vascular complications is a key issue. Although the exact mechanism by which vascular damage occurs in diabetes in not fully understood, numerous studies support the hypothesis of a causal relationship of non-enzymatic glycation with vascular complications. In this review, data which point to an important role of Amadori-modified glycated proteins and advanced glycation endproducts in vascular disease are surveyed. Because of the potential role of early- and advanced non-enzymatic glycation in vascular complications, we also described recent developments of pharmacological inhibitors that inhibit the formation of these glycated products or the biological consequences of glycation and thereby retard the development of vascular complications in diabetes

Toxin-Based Therapeutic Approaches

Protein toxins confer a defense against predation/grazing or a superior pathogenic competence upon the producing organism. Such toxins have been perfected through evolution in poisonous animals/plants and pathogenic bacteria. Over the past five decades, a lot of effort has been invested in studying their mechanism of action, the way they contribute to pathogenicity and in the development of antidotes that neutralize their action. In parallel, many research groups turned to explore the pharmaceutical potential of such toxins when they are used to efficiently impair essential cellular processes and/or damage the integrity of their target cells. The following review summarizes major advances in the field of toxin based therapeutics and offers a comprehensive description of the mode of action of each applied toxin