Large Language Models as Subpopulation Representative Models: A Review

Of the many commercial and scientific opportunities provided by large language models (LLMs; including Open AI's ChatGPT, Meta's LLaMA, and Anthropic's Claude), one of the more intriguing applications has been the simulation of human behavior and opinion. LLMs have been used to generate human simulcra to serve as experimental participants, survey respondents, or other independent agents, with outcomes that often closely parallel the observed behavior of their genuine human counterparts. Here, we specifically consider the feasibility of using LLMs to estimate subpopulation representative models (SRMs). SRMs could provide an alternate or complementary way to measure public opinion among demographic, geographic, or political segments of the population. However, the introduction of new technology to the socio-technical infrastructure does not come without risk. We provide an overview of behavior elicitation techniques for LLMs, and a survey of existing SRM implementations. We offer frameworks for the analysis, development, and practical implementation of LLMs as SRMs, consider potential risks, and suggest directions for future work

Decoupling User Interface Design Using Libraries of Reusable Components

The integration of electronic and mechanical hardware, software and interaction design presents a challenging design space for researchers developing physical user interfaces and interactive artifacts. Currently in the academic research community, physical user interfaces and interactive artifacts are predominantly designed and prototyped either as one-off instances from the ground up, or using functionally rich hardware toolkits and prototyping systems. During this prototyping phase, undertaking an integral design of the interface or interactive artifact’s electronic hardware is frequently constraining due to the tight couplings between the different design realms and the typical need for iterations as the design matures. Several current toolkit designs have consequently embraced component-sharing and component-swapping modular designs with a view to extending flexibility and improving researcher freedom by disentangling and softening the cause-effect couplings. Encouraged by early successes of these toolkits, this research work strives to further enhance these freedoms by pursuing an alternative style and dimension of hardware modularity. Another motivation is our goal to facilitate the design and development of certain classes of interfaces and interactive artifacts for which current electronic design approaches are argued to be restrictively constraining (e.g., relating to scale and complexity). Unfortunately, this goal of a new platform architecture is met with conceptual and technical challenges on the embedded system networking front. In response, this research investigates and extends a growing field of multi-module distributed embedded systems. We identify and characterize a sub-class of these systems, calling them embedded aggregates. We then outline and develop a framework for realizing the embedded aggregate class of systems. Toward this end, this thesis examines several architectures, topologies and communication protocols, making the case for and substantial steps toward the development of a suite of networking protocols and control algorithms to support embedded aggregates. We define a set of protocols, mechanisms and communication packets that collectively form the underlying framework for the aggregates. Following the aggregates design, we develop blades and tiles to support user interface researchers

Enhancing the architecture of interactive evolutionary design for exploring heterogeneous particle swarm dynamics: An in-class experiment

Abstract-We developed Swarm Chemistry 1.2, a new version of the Swarm Chemistry simulator with an enhanced architecture of interactive evolutionary design for exploring heterogeneous self-propelled particle swarm dynamics. In the new version, each evolutionary operator acts locally and visually to part of the population of swarms on a screen, without causing entire generation changes that were used in earlier versions. This new architecture is intended to represent cognitive actions in human thinking and decision making processes more naturally. We tested the effectiveness of the new architecture through an in-class experiment with college students participating as designers as well as evaluators of swarms. We also measured the effects of mixing and mutation operators to the performance improvement of the design processes. The students' responses showed that the designs produced using the new version received significantly higher ratings from students than those produced using the old one, and also that each of the mixing and mutation operators contributed nearly independently to the improvement of the design quality. These results demonstrate the effectiveness of the new architecture of interactive evolutionary design, as well as the importance of having diverse options of action (i.e., multiple evolutionary operators in this context) in iterative design and decision making processes. This work also presents one of the few examples of human-involved experiments on the statistical evaluation of artificial lifeforms, whose quality (such as "livingness") would be hard to assess without using human cognition at this point

Deliberative Technology for Alignment

For humanity to maintain and expand its agency into the future, the most powerful systems we create must be those which act to align the future with the will of humanity. The most powerful systems today are massive institutions like governments, firms, and NGOs. Deliberative technology is already being used across these institutions to help align governance and diplomacy with human will, and modern AI is poised to make this technology significantly better. At the same time, the race to superhuman AGI is already underway, and the AI systems it gives rise to may become the most powerful systems of the future. Failure to align the impact of such powerful AI with the will of humanity may lead to catastrophic consequences, while success may unleash abundance. Right now, there is a window of opportunity to use deliberative technology to align the impact of powerful AI with the will of humanity. Moreover, it may be possible to engineer a symbiotic coupling between powerful AI and deliberative alignment systems such that the quality of alignment improves as AI capabilities increase

TECHNOLOGY ASSESSMENT FOR SUSTAINABILITY IN WATER USE. OPERATIONALIZATION OF A RESPONSIBLE GOVERNANCE BASED IN RESPONSIBLE RESEARCH AND INNOVATION (ANTICIPATION AND INCLUSIVENESS)

The management of sustainability in water resources has underscored the critical importance of determining appropriate decision-making processes and establishing effective governance structures. Gaining comprehensive insights into the decision-making mechanisms and actors involved is pivotal for tackling present as well as prospective issues related to water efficiently. This research evaluates the interplay among water scarcity, responsible technologies for water use, and systems of governance for sustainability amid swift technological progress. Furthermore, it delves into the congruity of said endeavors with the Sustainable Development Goals (SDGs), other sustainability water frameworks and the social and political ecosystem. In this context, the active engagement and participation of societal actors, and not only stakeholders, assume a pivotal role as it significantly impacts the decision-making processes and molds the results of sustainability initiatives. An innovative approach to the concepts of responsibility and sustainability is predicated on the quality of the relationship between the network of societal actors as a key point. This work underscores the importance of establishing strong and comprehensive relationships to address the challenges concerning water management and promote the adoption of sustainable approaches, in co-creation, not only of knowledge but the epistemic subject in the process. This work sheds light on the interrelated domains of water management, sustainability, and regulation. A novel proposal is presented via a simulation exercise and use the socio-technical framework for the purpose of fostering responsible water use. The comprehension and use of responsible technology and innovation in the realm of water u management will be enhanced through the technique of operationalizing open anticipatory governance and executing a simulated experiment. By using a digital deliberation space and establishing a systematic approach towards technology assessment and sustainability, using the relational quality of the network of actors as the key element for co-production of knowledge, science and technology, the present study has produced and materialized an innovative framework.Na sustentabilidade da gestão da água reveste-se de especial importância determinar processos de tomada de decisão adequados e estabelecer estruturas de governação eficazes. Obter uma visão abrangente sobre os mecanismos de tomada de decisão e os atores envolvidos é fundamental para abordar questões presentes e futuras relacionadas ao uso eficiente da água. Este trabalho procura conhecer a interação entre gestão de água, tecnologias responsáveis pelo uso da água e sistemas de governança para a sustentabilidade. Adicionalmente, pretende conhecer a relação com os Sustainable Development Goals (SDGs), outros programas de sustentabilidade, bem como com o ecossistema social e político. Neste contexto, o envolvimento e a participação ativa dos atores sociais, e não apenas de stakeholders, assume um papel fundamental, uma vez que, não só, impactam significativamente os processos de tomada de decisão, mas, também, moldam os resultados das iniciativas de sustentabilidade. Nesta nova aproximação ao conceito de responsabilidade e sustentabilidade encontra-se a qualidade da relação entre a rede de atores sociais como ponto-chave. Sublinha-se a importância de estabelecer uma qualidade relacional enriquecida e abrangente para enfrentar de forma mais estruturada os desafios relativos à gestão da água de forma eficiente e promover a adoção de abordagens sustentáveis. Com este trabalho, procura-se aprofundar os domínios inter-relacionados da gestão da água, sustentabilidade e regulamentação. É elaborada uma proposta de simulação, utilizando uma perspetiva sociotécnica com o objetivo de capacitar a co-constituição como sujeitos e a compreensão e utilização de tecnologia responsável e inovação no âmbito da gestão do uso da água utilizando operacionalização da governação antecipatória aberta. O presente estudo materializa seu carácter de inovação ao utilizar um espaço de deliberação digital e ao estabelecer uma abordagem sistemática para a avaliação da tecnologia e sustentabilidade, usando a qualidade relacional da rede de atores como elemento-chave para a coprodução de conhecimento, ciência e tecnologia e co-constituição do próprio sujeito no processo de deliberação

EVALUATING AND EXTENDING THE CONCEPT OF WISDOM OF CROWDS IN THE CONTEXT OF PROBLEM SOLVING

James Surowiecki in his book on the wisdom of crowds [Jame04] wrote about the decisions made based on the aggregation of information in groups. Knowing the many case studies and anecdotes which show the success of wisdom of crowds, he argues that under certain circumstances the wisdom of crowds is often better than that of any single member in the group. This paper provides a new way of problem solving– using the wisdom of crowds (collective wisdom) to handle continuous decision making problems, especially in a complex and rapidly changing world. By extending the concept of Wisdom of Crowds, the method of using collective wisdom is applied to various fields, from Prisoner‘s Dilemma to simplified stock market. Simulations are built to evaluate this new problem solving method and different aggregation strategies are suggested based on different environments

Assistive technology design and development for acceptable robotics companions for ageing years

© 2013 Farshid Amirabdollahian et al., licensee Versita Sp. z o. o. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs license, which means that the text may be used for non-commercial purposes, provided credit is given to the author.A new stream of research and development responds to changes in life expectancy across the world. It includes technologies which enhance well-being of individuals, specifically for older people. The ACCOMPANY project focuses on home companion technologies and issues surrounding technology development for assistive purposes. The project responds to some overlooked aspects of technology design, divided into multiple areas such as empathic and social human-robot interaction, robot learning and memory visualisation, and monitoring persons’ activities at home. To bring these aspects together, a dedicated task is identified to ensure technological integration of these multiple approaches on an existing robotic platform, Care-O-Bot®3 in the context of a smart-home environment utilising a multitude of sensor arrays. Formative and summative evaluation cycles are then used to assess the emerging prototype towards identifying acceptable behaviours and roles for the robot, for example role as a butler or a trainer, while also comparing user requirements to achieved progress. In a novel approach, the project considers ethical concerns and by highlighting principles such as autonomy, independence, enablement, safety and privacy, it embarks on providing a discussion medium where user views on these principles and the existing tension between some of these principles, for example tension between privacy and autonomy over safety, can be captured and considered in design cycles and throughout project developmentsPeer reviewe

A new direction for public understanding of science: toward a participant-centered model of science engagement.

Engaging the public with science is not an easy task. When presented, scientific findings, public health recommendations, and other scientific information filter through the personal values, beliefs, and biases of members of the public. Science communicators must contend with these differences in order to be effective in cultivating a public understanding of science. Given the importance of scientific understanding for living well in a complex world, increasing science understanding through science engagement is imperative. The field of public engagement with science is dichotomized by a public information deficit approach and a contextualist approach. The deficit approach prizes the factual content of science, its epistemic authority, and its communication to the public while the contextualist approach recognizes the sociocultural embeddedness of science in society, how science is received by publics, and how local knowledges intersect with science. I contend both approaches are incomplete, and I put forth a synthesis. My approach, the participant-centered model of science engagement, incorporates the factual content of science and its epistemic authority, but in a way that is sensitive to context. I argue for a deliberative democratic approach to public engagement with science and articulate a model inspired by learner-centered approaches to teaching in the formal education literature. I outline and assess six participant-centered strategies along with recommendations for particular practices associated with each

Optimization techniques in respiratory control system models

One of the most complex physiological systems whose modeling is still an open study is the respiratory control system where different models have been proposed based on the criterion of minimizing the work of breathing (WOB). The aim of this study is twofold: to compare two known models of the respiratory control system which set the breathing pattern based on quantifying the respiratory work; and to assess the influence of using direct-search or evolutionary optimization algorithms on adjustment of model parameters. This study was carried out using experimental data from a group of healthy volunteers under CO2 incremental inhalation, which were used to adjust the model parameters and to evaluate how much the equations of WOB follow a real breathing pattern. This breathing pattern was characterized by the following variables: tidal volume, inspiratory and expiratory time duration and total minute ventilation. Different optimization algorithms were considered to determine the most appropriate model from physiological viewpoint. Algorithms were used for a double optimization: firstly, to minimize the WOB and secondly to adjust model parameters. The performance of optimization algorithms was also evaluated in terms of convergence rate, solution accuracy and precision. Results showed strong differences in the performance of optimization algorithms according to constraints and topological features of the function to be optimized. In breathing pattern optimization, the sequential quadratic programming technique (SQP) showed the best performance and convergence speed when respiratory work was low. In addition, SQP allowed to implement multiple non-linear constraints through mathematical expressions in the easiest way. Regarding parameter adjustment of the model to experimental data, the evolutionary strategy with covariance matrix and adaptation (CMA-ES) provided the best quality solutions with fast convergence and the best accuracy and precision in both models. CMAES reached the best adjustment because of its good performance on noise and multi-peaked fitness functions. Although one of the studied models has been much more commonly used to simulate respiratory response to CO2 inhalation, results showed that an alternative model has a more appropriate cost function to minimize WOB from a physiological viewpoint according to experimental data.Postprint (author's final draft