Hasil untuk "Human settlements. Communities"

T. M. Vinod Kumar

T. M. Vinod Kumar

Jeremy C. -H. Wang, Ming Hou, David Dunwoody et al.

This paper examines how trust is formed, maintained, or diminished over time in the context of human-autonomy teaming with an optionally piloted aircraft. Whereas traditional factor-based trust models offer a static representation of human confidence in technology, here we discuss how variations in the underlying factors lead to variations in trust, trust thresholds, and human behaviours. Over 200 hours of flight test data collected over a multi-year test campaign from 2021 to 2023 were reviewed. The dispositional-situational-learned, process-performance-purpose, and IMPACTS homeostasis trust models are applied to illuminate trust trends during nominal autonomous flight operations. The results offer promising directions for future studies on trust dynamics and design-for-trust in human-autonomy teaming.

Adrian Arnaiz-Rodriguez, Nina Corvelo Benz, Suhas Thejaswi et al.

Data-driven algorithmic matching systems promise to help human decision makers make better matching decisions in a wide variety of high-stakes application domains, such as healthcare and social service provision. However, existing systems are not designed to achieve human-AI complementarity: decisions made by a human using an algorithmic matching system are not necessarily better than those made by the human or by the algorithm alone. Our work aims to address this gap. To this end, we propose collaborative matching (comatch), a data-driven algorithmic matching system that takes a collaborative approach: rather than making all the matching decisions for a matching task like existing systems, it selects only the decisions that it is the most confident in, deferring the rest to the human decision maker. In the process, comatch optimizes how many decisions it makes and how many it defers to the human decision maker to provably maximize performance. We conduct a large-scale human subject study with $800$ participants to validate the proposed approach. The results demonstrate that the matching outcomes produced by comatch outperform those generated by either human participants or by algorithmic matching on their own. The data gathered in our human subject study and an implementation of our system are available as open source at https://github.com/Networks-Learning/human-AI-complementarity-matching.

Aparecida Dias Terras Gomes

Este relato de experiência teve como objetivo abordar questões de gênero, feminismo e direitos humanos, utilizando o livro Malala, a menina que queria ir para a escola, de Adriana Carranca (2018), com alunos do 7º ano do ensino fundamental em uma escola pública. A história da ativista paquistanesa Malala Yousafzai serviu como base para leitura, fichamento, tertúlia literária, produção de cartas motivacionais e discussões sobre igualdade de gênero, acesso à educação e dos direitos humanos. A metodologia adotou uma abordagem participativa, com o uso de recursos visuais, como vídeos, para ampliar a compreensão e o engajamento dos estudantes. O referencial teórico fundamentou-se nas perspectivas de Spivak (2010) e hooks (2017, 2021), dialogando com teorias feministas e documentos internacionais. O estudo dessa obra incentivou reflexões sobre desigualdade de gênero e educação equitativa, promovendo a desconstrução de estereótipos e o fortalecimento da consciência crítica dos estudantes. A experiência também estimulou o protagonismo juvenil na defesa dos direitos humanos e na promoção da cultura da paz, reforçando o papel da educação na construção de uma sociedade mais justa e igualitária. 

Johan Mottelson

Saskia Laura Schröer, Giovanni Apruzzese, Soheil Human et al.

Our society increasingly benefits from Artificial Intelligence (AI). Unfortunately, more and more evidence shows that AI is also used for offensive purposes. Prior works have revealed various examples of use cases in which the deployment of AI can lead to violation of security and privacy objectives. No extant work, however, has been able to draw a holistic picture of the offensive potential of AI. In this SoK paper we seek to lay the ground for a systematic analysis of the heterogeneous capabilities of offensive AI. In particular we (i) account for AI risks to both humans and systems while (ii) consolidating and distilling knowledge from academic literature, expert opinions, industrial venues, as well as laypeople -- all of which being valuable sources of information on offensive AI. To enable alignment of such diverse sources of knowledge, we devise a common set of criteria reflecting essential technological factors related to offensive AI. With the help of such criteria, we systematically analyze: 95 research papers; 38 InfoSec briefings (from, e.g., BlackHat); the responses of a user study (N=549) entailing individuals with diverse backgrounds and expertise; and the opinion of 12 experts. Our contributions not only reveal concerning ways (some of which overlooked by prior work) in which AI can be offensively used today, but also represent a foothold to address this threat in the years to come.

Nitesh Goyal, Minsuk Chang, Michael Terry

Our ability to build autonomous agents that leverage Generative AI continues to increase by the day. As builders and users of such agents it is unclear what parameters we need to align on before the agents start performing tasks on our behalf. To discover these parameters, we ran a qualitative empirical research study about designing agents that can negotiate during a fictional yet relatable task of selling a camera online. We found that for an agent to perform the task successfully, humans/users and agents need to align over 6 dimensions: 1) Knowledge Schema Alignment 2) Autonomy and Agency Alignment 3) Operational Alignment and Training 4) Reputational Heuristics Alignment 5) Ethics Alignment and 6) Human Engagement Alignment. These empirical findings expand previous work related to process and specification alignment and the need for values and safety in Human-AI interactions. Subsequently we discuss three design directions for designers who are imagining a world filled with Human-Agent collaborations.

Yehor Karpichev, Todd Charter, Jayden Hong et al.

The rise of automation has provided an opportunity to achieve higher efficiency in manufacturing processes, yet it often compromises the flexibility required to promptly respond to evolving market needs and meet the demand for customization. Human-robot collaboration attempts to tackle these challenges by combining the strength and precision of machines with human ingenuity and perceptual understanding. In this paper, we conceptualize and propose an implementation framework for an autonomous, machine learning-based manipulator that incorporates human-in-the-loop principles and leverages Extended Reality (XR) to facilitate intuitive communication and programming between humans and robots. Furthermore, the conceptual framework foresees human involvement directly in the robot learning process, resulting in higher adaptability and task generalization. The paper highlights key technologies enabling the proposed framework, emphasizing the importance of developing the digital ecosystem as a whole. Additionally, we review the existent implementation approaches of XR in human-robot collaboration, showcasing diverse perspectives and methodologies. The challenges and future outlooks are discussed, delving into the major obstacles and potential research avenues of XR for more natural human-robot interaction and integration in the industrial landscape.

Qian Zhu, Dakuo Wang, Shuai Ma et al.

As AI technology continues to advance, the importance of human-AI collaboration becomes increasingly evident, with numerous studies exploring its potential in various fields. One vital field is data science, including feature engineering (FE), where both human ingenuity and AI capabilities play pivotal roles. Despite the existence of AI-generated recommendations for FE, there remains a limited understanding of how to effectively integrate and utilize humans' and AI's knowledge. To address this gap, we design a readily-usable prototype, human\&AI-assisted FE in Jupyter notebooks. It harnesses the strengths of humans and AI to provide feature suggestions to users, seamlessly integrating these recommendations into practical workflows. Using the prototype as a research probe, we conducted an exploratory study to gain valuable insights into data science practitioners' perceptions, usage patterns, and their potential needs when presented with feature suggestions from both humans and AI. Through qualitative analysis, we discovered that the Creator of the feature (i.e., AI or human) significantly influences users' feature selection, and the semantic clarity of the suggested feature greatly impacts its adoption rate. Furthermore, our findings indicate that users perceive both differences and complementarity between features generated by humans and those generated by AI. Lastly, based on our study results, we derived a set of design recommendations for future human&AI FE design. Our findings show the collaborative potential between humans and AI in the field of FE.

Armand Fréjuis Akpa, Augustin Foster Chabossou

The introduction of information and communication technology (ICT) has altered the way society operates things. ICT is used in various sectors, including agriculture. It can be used in the agricultural sector to distribute pricing and encourage agricultural commodity exports. The study aims to investigate the effect of ICT on cashew nut export in Benin using an autoregressive distributed lag (ARDL) approach. Data were collected over the period of 31 years (1990–2020) in Benin. The estimated results showed that mobile cellular telephone subscription is negatively and significantly correlated with cashew nut export in the short-run. However, in the long-run, it exhibits a positive and significant correlation. On the other hand, internet usage had no significant effect on cashew nut export in the short-run, but negatively influenced cashew nut export in the long-run. These results suggest that to increase its cashew nut export, the Beninese government should invest in technological infrastructure to improve internet access by reducing the cost of internet and increasing education that will allow farmers to better understand and use ICT.

David Oluseun Olayungbo, Aziza Zhuparova, Mamdouh Abdulaziz Saleh Al-Faryan et al.

The relationship between oil price movements and stock markets during the COVID-19 pandemic and the geopolitical crisis like the ongoing Russian-Ukraine war is yet unexplored extensively. This study therefore examines the return-correlation effects of oil prices on stock markets and their spillover effects in oil-exporting and European countries using daily closing data. After estimating the GARCH process, we employ the static and dynamic Markov Switching model that allow the relationship between oil price and stock market to switch between two regimes coined the COVID-19 and the Russia-Ukraine war periods. The static model shows stock price returns to respond positively and significantly to oil price returns in Italy, Germany and the US during the Covid-19 period while the response is significantly positive only for US in the Russia-Ukraine war period. As regards the volatility spillover, significant spillover is found from stock to oil market for Nigeria, vice versa for Saudi Arabia and bi-directional volatility spillover found for the US, Italy and Germany during the COVID-19 period. The policy implication is that Nigeria and Saudi Arabia should prioritize financial policy and energy policy respectively while US, Italy and Germany should adopt policy coordination to stabilize oil-stock market volatility during low oil price period like the COVID-19 period.

Christopher Bacon, Ava Gleicher, Emma McCurry et al.

The 60,000 food pantries in the United States are well known for charity-based emergency food assistance and edible food recovery, serving 53 mil­lion people in 2022 (Feeding America, 2023a). Thousands of urban gardens emphasize vegetable production and food justice, but lack strong con­nections to food pantries. We explore how food pantries and urban gardens could partner to trans­form pantries into distribution sites that also become food justice education and organizing spaces. To assess this potential, we engaged in par­ticipatory action research with a leading social ser­vices provider that offers programs supporting both organized urban gardeners and a large urban food pantry in San Jose, California. We conducted and analyzed 21 interviews with food pantry volun­teers and urban gardeners affiliated with the same agency, and eight interviews with other urban gar­deners and food pantry staff from external organi­zations. We found that while both food pantry vol­unteers and urban gardeners expressed concerns about increasing healthy food access and reducing food waste, pantry volunteers were often unfamil­iar with food justice and uncomfortable talking about race and culturally rooted food preferences. These findings were similar with the informants from external organizations. To support urban gar­dener and food pantry volunteer collaboration, we developed a food justice approach to emergency food assistance and food waste management in which both groups co-create onsite vermicompost­ing infrastructure and partner with a university to design a training program focused on diversity, jus­tice, and systemic change. 

E. Kuligowski, S. Gwynne, Hui Xie et al.

Informal settlements and settlements of displaced communities (e.g., humanitarian settlements) provide crucial shelter for people, including those negatively impacted by natural hazards and human-caused crises. However, these settlements are also prone to fire as a ‘secondary incident’. This occurrence can be influenced by the use of flammable materials in the building construction and unsafe fire and electricity practices given the harsh and sudden conditions faced (along with pre-existing economic hardship). Humanitarian practitioners and agencies are increasingly recognizing the importance of addressing the fire safety problem in humanitarian settlements, with a particular focus on community evacuation. This article presents a new method to assess the safety of the areas involved and explores the use of a pedestrian simulation model (Pathfinder), to conduct evacuation analysis in an example settlement given the occurrence of a fire. The goal is to demonstrate the potential for such applications and provide a foundation from which such an application might be formalized and tested across representative scenarios. The Pathfinder tool is widely used in the fire safety community for building evacuations. It is applied here on a larger scale, although examining the same core evacuation factors. The impact of four key factors on evacuation performance is examined (i.e., density, pre-travel delays, route choice, and restricted routes), based on a case study of the community within the Kutupalong refugee camp in Cox’s Bazar, Bangladesh. Study results show that Pathfinder provides insights into evacuation outcomes during settlement fires despite the complexity involved in creating the simulation model. The results also show that the evacuation times produced were sensitive to the four conditions tested and that the prolonged evacuation times resulting from these conditions could lead to serious consequences to settlement residents, especially in cases with fast moving fires. Of course, the accuracy of such estimates is reliant on the data available and the assumptions made to configure the model. However, we have demonstrated that the simulation tool can cope with the scenarios examined and provide insights into the evacuation dynamics produced—establishing the potential of such a tool and the value of more rigorous examination.

Jurriaan van Diggelen, Karel van den Bosch, Mark Neerincx et al.

We propose methods for analysis, design, and evaluation of Meaningful Human Control (MHC) for defense technologies from the perspective of military human-machine teaming (HMT). Our approach is based on three principles. Firstly, MHC should be regarded as a core objective that guides all phases of analysis, design and evaluation. Secondly, MHC affects all parts of the socio-technical system, including humans, machines, AI, interactions, and context. Lastly, MHC should be viewed as a property that spans longer periods of time, encompassing both prior and realtime control by multiple actors. To describe macrolevel design options for achieving MHC, we propose various Team Design Patterns. Furthermore, we present a case study, where we applied some of these methods to envision HMT, involving robots and soldiers in a search and rescue task in a military context.

Mohammad Tahaei, Marios Constantinides, Daniele Quercia et al.

In recent years, the CHI community has seen significant growth in research on Human-Centered Responsible Artificial Intelligence. While different research communities may use different terminology to discuss similar topics, all of this work is ultimately aimed at developing AI that benefits humanity while being grounded in human rights and ethics, and reducing the potential harms of AI. In this special interest group, we aim to bring together researchers from academia and industry interested in these topics to map current and future research trends to advance this important area of research by fostering collaboration and sharing ideas.

Chen Ran, Yao Xueqi, Jiang Xuhui et al.

The field of human settlement construction encompasses a range of spatial designs and management tasks, including urban planning and landscape architecture design. These tasks involve a plethora of instructions and descriptions presented in natural language, which are essential for understanding design requirements and producing effective design solutions. Recent research has sought to integrate natural language processing (NLP) and generative artificial intelligence (AI) into human settlement construction tasks. Due to the efficient processing and analysis capabilities of AI with data, significant successes have been achieved in design within this domain. However, this task still faces several fundamental challenges. The semantic information involved includes complex spatial details, diverse data source formats, high sensitivity to regional culture, and demanding requirements for innovation and rigor in work scenarios. These factors lead to limitations when applying general generative AI in this field, further exacerbated by a lack of high-quality data for model training. To address these challenges, this paper first proposes HSC-GPT, a large-scale language model framework specifically designed for tasks in human settlement construction, considering the unique characteristics of this domain.

Gül Aktürk, Martha B. Lerski

Climate change is borderless, and its impacts are not shared equally by all communities. It causes an imbalance between people by creating a more desirable living environment for some societies while erasing settlements and shelters of some others. Due to floods, sea level rise, destructive storms, drought, and slow-onset factors such as salinization of water and soil, people lose their lands, homes, and natural resources. Catastrophic events force people to move voluntarily or involuntarily. The relocation of communities is a debatable climate adaptation measure which requires utmost care with human rights, ethics, and psychological well-being of individuals upon the issues of discrimination, conflict, and security. As the number of climate-displaced populations grows, the generations-deep connection to their rituals, customs, and ancestral ties with the land, cultural practices, and intangible cultural heritage become endangered. However, intangible heritage is often overlooked in the context of climate displacement. This paper presents reflections based on observations regarding the intangible heritage of voluntarily displaced communities. It begins by examining intangible heritage under the threat of climate displacement, with place-based examples. It then reveals intangible heritage as a catalyst to building resilient communities by advocating for the cultural values of indigenous and all people in climate action planning. It concludes the discussion by presenting the implications of climate displacement in existing intangible heritage initiatives. This article seeks to contribute to the emerging policies of preserving intangible heritage in the context of climate displacement.