The disadvantaged population is often underserved and marginalized in technology engagement: prior works show they are generally more reluctant and experience more barriers in adopting and engaging with mainstream technology. Here, we contribute to the HCI4D and ICTD literature through a novel ``counter'' case study on Chinese social commerce (e.g., Pinduoduo), which 1) first prospers among the traditionally underserved community from developing regions ahead of the more technologically advantaged communities, and 2) has been heavily engaged by this community. Through 12 in-depth interviews with social commerce users from the traditionally underserved community in Chinese developing regions, we demonstrate how social commerce, acting as a ``virtual bazaar'', brings online the traditional offline socioeconomic lives the community has lived for ages, fits into the community's social, cultural, and economic context, and thus effectively promotes technology inclusivity. Our work provides novel insights and implications for building inclusive technology for the ``next billion'' population.
https://dl.acm.org/doi/abs/10.1145/3491102.3517487
The current mechanisms that drive the development of AI technologies are widely criticized for being tech-oriented and market-led instead of stemming from societal challenges. In Human-Centered AI discourses, and more broadly in Human-Computer Interaction research, initiatives have been proposed to engage experts from various domains of social science in determining how AI should reach our societies, predominantly through informing the adoption policies. Our contribution, however, seeks a more essential role for social sciences, namely to introduce discursive standpoints around what we need AI to be. With a focus on the domain of urbanism, the specific goal has been to elicit – from interviews with 16 urban experts – the imaginaries of how AI can and should impact future cities. Drawing on the social science literature, we present how the notion of "imaginary" has essentially framed this research and how it could reveal an alternative vision of non-human intelligent actors in future cities.
https://dl.acm.org/doi/abs/10.1145/3491102.3517502
As interest within the HCI community expands beyond urban settings, novel tools and devices are being developed to support more sustainable interactions with natural environments and inform conservation action. Yet little is known about the users of these devices, and how their requirements and priorities might affect the usability or operationalization of the devices in the real world. Using the ‘e-seed’, a biomimetic self-drilling interface as a ‘research probe’, we conducted a qualitative user study with 14 subject matter experts in areas like forestry and agriculture to understand the value and limits for devices and systems in ecological restoration and monitoring. We highlight unique challenges in existing ecological practices, opportunities for technological interventions, and the policies and economic constraints affecting the feasibility of such interventions. We present a set of critical design considerations for building and deploying novel devices in natural and semi-natural ecosystems and discuss implications for future research.
https://dl.acm.org/doi/abs/10.1145/3491102.3517664
Ridesharing services do not make data of their availability (supply, utilization, idle time, and idle distance) and surge pricing publicly available. It limits the opportunities to study the spatiotemporal trends of the availability and surge pricing of these services. Only a few research studies conducted in North America analyzed these features for only Uber and Lyft. Despite the interesting observations, the results of prior works are not generalizable or reproducible because i) the datasets collected in previous publications are spatiotemporally sensitive, i.e., previous works do not represent the current availability and surge pricing of ridesharing services in different parts of the world; ii) the analyses presented in previous works are limited in scope (in terms of countries and ridesharing services they studied). Hence, prior works are not generally applicable to ridesharing services operating in different countries. This paper addresses the issue of ridesharing-data unavailability by presenting Ridesharing Measurement Suite (RMS). RMS removes the barrier of entry for analyzing the availability and surge pricing of ridesharing services for ridesharing users, researchers from various scientific domains, and regulators. RMS continuously collects the data of the availability and surge pricing of ridesharing services. It exposes real-time data of these services through \textit{i)} graphical user interfaces and \textit{ii)} public APIs to assist various stakeholders of these services and simplify the data collection and analysis process for future ridesharing research studies. To signify the utility of RMS, we deployed RMS to collect and analyze the availability and surge pricing data of 10 ridesharing services operating in nine countries for eight weeks in pre and during pandemic periods. Using the data collected and analyzed by RMS, we identify that previous articles miscalculated the utilization of ridesharing services as they did not count in the vehicles driving in multiple categories of the same service. We observe that during COVID-19, the supply of ridesharing services decreased by 54\%, utilization of available vehicles increased by 6\%, and a 5$\times$ increase in the surge frequency of services. We also find that surge occurs in a small geographical region, and its intensity reduces by 50\% in about 0.5 miles away from the location of a surge. We present several other interesting observations on ridesharing services' availability and surge pricing.
https://dl.acm.org/doi/abs/10.1145/3491102.3517464
We found significant gaps in the climates and built environments used as settings for studies of HCI outdoors. The experience of using a computer outdoors varies widely depending on location-specific factors such as weather and the availability of electricity. We surveyed 699 papers from CHI venues and found 101 studies involving a person and a computer interacting outdoors for which we could determine the study location. We categorized each study location by climate using the Koppen-Geiger scheme and by built environment using the Recreation Opportunity Spectrum. 91 of 101 studies took place in temperate or continental climates and 82 took place in urban settings. Emerging understanding of the ongoing impacts of climate change increases the importance of investigating HCI outdoors in a wider range of weather conditions. While some primitive natural settings have been preserved against development at great cost, we found no studies of HCI outdoors in those settings.
https://dl.acm.org/doi/abs/10.1145/3491102.3507656