D. Schien, P. Shabajee, James Wickenden, William Picket, Glynn Roberts, C. Preist
We present the DIMPACT /dimpækt/ tool for environmental assessments of digital services. The tool enables digital media providers to calculate energy consumption and associated environmental impact across the entire product system, including datacentres, networks and user devices. It is based on accepted standard methodologies and applies state-of-the-art research. The DIMPACT tool is used by major media organisations for environmental reporting and to support development of strategies to reduce environmental impact. It has significantly advanced the knowledge of carbon emissions of video streaming. The tool is part of the wider DIMPACT project of companies that collaborate to exchange knowledge, engage suppliers and expand the scope of the tool. In this text we provide an overview of workings of tool and its methodological foundation.
{"title":"Demo: The DIMPACT Tool for Environmental Assessment of Digital Services","authors":"D. Schien, P. Shabajee, James Wickenden, William Picket, Glynn Roberts, C. Preist","doi":"10.1145/3530190.3542932","DOIUrl":"https://doi.org/10.1145/3530190.3542932","url":null,"abstract":"We present the DIMPACT /dimpækt/ tool for environmental assessments of digital services. The tool enables digital media providers to calculate energy consumption and associated environmental impact across the entire product system, including datacentres, networks and user devices. It is based on accepted standard methodologies and applies state-of-the-art research. The DIMPACT tool is used by major media organisations for environmental reporting and to support development of strategies to reduce environmental impact. It has significantly advanced the knowledge of carbon emissions of video streaming. The tool is part of the wider DIMPACT project of companies that collaborate to exchange knowledge, engage suppliers and expand the scope of the tool. In this text we provide an overview of workings of tool and its methodological foundation.","PeriodicalId":268672,"journal":{"name":"Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126591191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rahat Jahangir Rony, Anik Sinha, Shajnush Amir, Syeda Shabnam Khan, Anik Saha, Ifti Azad Abeer, Nova Ahmed
Indigenous communities in Bangladesh are comparatively disadvantaged and face several barriers regarding rights. Access to technology and ICT can help indigenous communities open new economic, political, and social dimensions. The recent COVID-19 pandemic necessitated technology adoption for routine use, which is equally important for indigenous communities, but their technology adoption scenario remains unexplored in HCI research. Considering the research gap, we interviewed n=36 (Female 26 and Male 10) indigenous people from six different indigenous communities in Chattogarm and Sylhet divisions in Bangladesh. We found that they are strongly connected in communities, have independent technology access, and have no gender differences. They have a strong interest and eagerness to learn available technologies that help them in their professions, enrich their technical skills, communication, social participation, and expand the business. The study also revealed some challenges while using technology, but that did not negatively impact their usage. The study also discussed the community-centric strengths that helped them fight against the COVID-19 crisis and work for their development. This research impacts HCI literature, revealing the technology adoption scenarios of Indigenous communities in Bangladesh.
{"title":"“I Use YouTube Now in COVID”: Understanding Technology Adoption of Indigenous Communities during COVID-19 Pandemic in Bangladesh","authors":"Rahat Jahangir Rony, Anik Sinha, Shajnush Amir, Syeda Shabnam Khan, Anik Saha, Ifti Azad Abeer, Nova Ahmed","doi":"10.1145/3530190.3534847","DOIUrl":"https://doi.org/10.1145/3530190.3534847","url":null,"abstract":"Indigenous communities in Bangladesh are comparatively disadvantaged and face several barriers regarding rights. Access to technology and ICT can help indigenous communities open new economic, political, and social dimensions. The recent COVID-19 pandemic necessitated technology adoption for routine use, which is equally important for indigenous communities, but their technology adoption scenario remains unexplored in HCI research. Considering the research gap, we interviewed n=36 (Female 26 and Male 10) indigenous people from six different indigenous communities in Chattogarm and Sylhet divisions in Bangladesh. We found that they are strongly connected in communities, have independent technology access, and have no gender differences. They have a strong interest and eagerness to learn available technologies that help them in their professions, enrich their technical skills, communication, social participation, and expand the business. The study also revealed some challenges while using technology, but that did not negatively impact their usage. The study also discussed the community-centric strengths that helped them fight against the COVID-19 crisis and work for their development. This research impacts HCI literature, revealing the technology adoption scenarios of Indigenous communities in Bangladesh.","PeriodicalId":268672,"journal":{"name":"Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117006668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ananth Balashankar, S. Fraiberger, Eric Deregt, M. Gorgens, L. Subramanian
Policy recommendations using observational data typically rely on estimating an econometric model on a sample of observations drawn from an entire population. However, different policy actions could potentially be optimal for different subgroups of a population. In this paper, we propose outcome-aware clustering, a new methodology to segment a population into different clusters and derive cluster-level policy recommendations. Outcome-aware clustering differs from conventional clustering algorithms across two basic dimensions. First, given a specific outcome of interest, outcome-aware clustering segments the population based on selecting a small set of features that closely relate with the outcome variable. Second, the clustering algorithm aims to generate near-homogeneous clusters based on a combination of cluster size-balancing constraints, inter and intra-cluster distances in the reduced feature space. We generate targeted policy recommendations for each outcome-aware cluster based on a standard multivariate regression of a condensed set of actionable policy features (which may partially overlap or differ from the features used for segmentation) from the observational data. We implement our outcome-aware clustering method on the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) dataset to generate targeted policy recommendations for improving farmers outcomes in sub-Saharan Africa. Based on a detailed analysis of the LSMS-ISA, we derive outcome-aware clusters of farmer populations across three sub-Saharan African countries and show that the targeted policy recommendations at the cluster level significantly differ from policies that are generated at the population level.
{"title":"Targeted Policy Recommendations using Outcome-aware Clustering","authors":"Ananth Balashankar, S. Fraiberger, Eric Deregt, M. Gorgens, L. Subramanian","doi":"10.1145/3530190.3534797","DOIUrl":"https://doi.org/10.1145/3530190.3534797","url":null,"abstract":"Policy recommendations using observational data typically rely on estimating an econometric model on a sample of observations drawn from an entire population. However, different policy actions could potentially be optimal for different subgroups of a population. In this paper, we propose outcome-aware clustering, a new methodology to segment a population into different clusters and derive cluster-level policy recommendations. Outcome-aware clustering differs from conventional clustering algorithms across two basic dimensions. First, given a specific outcome of interest, outcome-aware clustering segments the population based on selecting a small set of features that closely relate with the outcome variable. Second, the clustering algorithm aims to generate near-homogeneous clusters based on a combination of cluster size-balancing constraints, inter and intra-cluster distances in the reduced feature space. We generate targeted policy recommendations for each outcome-aware cluster based on a standard multivariate regression of a condensed set of actionable policy features (which may partially overlap or differ from the features used for segmentation) from the observational data. We implement our outcome-aware clustering method on the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) dataset to generate targeted policy recommendations for improving farmers outcomes in sub-Saharan Africa. Based on a detailed analysis of the LSMS-ISA, we derive outcome-aware clusters of farmer populations across three sub-Saharan African countries and show that the targeted policy recommendations at the cluster level significantly differ from policies that are generated at the population level.","PeriodicalId":268672,"journal":{"name":"Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies","volume":"58 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134222438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rushabh Musthyala, Rudrajit Kargupta, Hritish Jain, D. Chakraborty
Policymakers often make decisions based on GDP, unemployment rate, industrial output, etc. The primary methods to obtain or estimate such information are resource-intensive. In order to make timely and well-informed decisions, it is imperative to come up with proxies for these parameters, which can be sampled quickly and efficiently, especially during disruptive events like the COVID-19 pandemic. We explore the use of remotely sensed data for this task. The data has become cheaper to collect than surveys and can be available in real-time. In this work, we present Regional GDP-NightLight (ReGNL), a neural network trained to predict GDP given the nightlights data and geographical coordinates. Taking the case of 50 US states, we find that ReGNL is disruption-agnostic and can predict the GDP for both normal years (2019) and years with a disruptive event (2020). ReGNL outperforms time-series ARIMA methods for prediction, even during the pandemic.
{"title":"Note: ReGNL: Rapid Prediction of GDP during Disruptive Events using Nightlights","authors":"Rushabh Musthyala, Rudrajit Kargupta, Hritish Jain, D. Chakraborty","doi":"10.1145/3530190.3534849","DOIUrl":"https://doi.org/10.1145/3530190.3534849","url":null,"abstract":"Policymakers often make decisions based on GDP, unemployment rate, industrial output, etc. The primary methods to obtain or estimate such information are resource-intensive. In order to make timely and well-informed decisions, it is imperative to come up with proxies for these parameters, which can be sampled quickly and efficiently, especially during disruptive events like the COVID-19 pandemic. We explore the use of remotely sensed data for this task. The data has become cheaper to collect than surveys and can be available in real-time. In this work, we present Regional GDP-NightLight (ReGNL), a neural network trained to predict GDP given the nightlights data and geographical coordinates. Taking the case of 50 US states, we find that ReGNL is disruption-agnostic and can predict the GDP for both normal years (2019) and years with a disruptive event (2020). ReGNL outperforms time-series ARIMA methods for prediction, even during the pandemic.","PeriodicalId":268672,"journal":{"name":"Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124304011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mayank Ratan Bhardwaj, Azal Fatima, Inavamsi Enaganti, Y. Narahari
Sourcing the right quality and quantity of agricultural inputs such as seeds, fertilizers, and pesticides, constitutes a crucial aspect of agricultural input operations. This is a particularly challenging problem being faced by the small and marginal farmers in any emerging economy. Farmer collectives (FCs) which are cooperative societies of farmers, launched under Federal Government initiatives in many countries, offer the prospect of enabling cost-effective procurement of inputs with assured quality. We seek, in this work, sound and explainable mechanisms for the above important use-case. In particular, we propose the use of incentive compatible auction mechanisms that could be used by an FC to procure quality inputs in bulk. The idea is the following. An FC collects from the farmers their individual requirements for inputs and aggregates them into different buckets. For each bucket, the FC identifies suppliers who meet the quality criteria and engages them in a competitive procurement auction. We explore in this paper, two particular types of procurement auctions: volume discount auctions and combinatorial auctions in the framework of Vickrey-Clarke-Groves (VCG) mechanisms. These are explainable mechanisms that induce truthful bids from the suppliers as well as maximize the social welfare. We show their efficacy through carefully designed thought experiments. Our field studies of FCs give us the confidence that such mechanisms, if deployed systematically, can become a game changer, benefiting a massive community of smallholder farmers.
{"title":"Incentive Compatible Mechanisms for Efficient Procurement of Agricultural Inputs for Farmers through Farmer Collectives","authors":"Mayank Ratan Bhardwaj, Azal Fatima, Inavamsi Enaganti, Y. Narahari","doi":"10.1145/3530190.3534842","DOIUrl":"https://doi.org/10.1145/3530190.3534842","url":null,"abstract":"Sourcing the right quality and quantity of agricultural inputs such as seeds, fertilizers, and pesticides, constitutes a crucial aspect of agricultural input operations. This is a particularly challenging problem being faced by the small and marginal farmers in any emerging economy. Farmer collectives (FCs) which are cooperative societies of farmers, launched under Federal Government initiatives in many countries, offer the prospect of enabling cost-effective procurement of inputs with assured quality. We seek, in this work, sound and explainable mechanisms for the above important use-case. In particular, we propose the use of incentive compatible auction mechanisms that could be used by an FC to procure quality inputs in bulk. The idea is the following. An FC collects from the farmers their individual requirements for inputs and aggregates them into different buckets. For each bucket, the FC identifies suppliers who meet the quality criteria and engages them in a competitive procurement auction. We explore in this paper, two particular types of procurement auctions: volume discount auctions and combinatorial auctions in the framework of Vickrey-Clarke-Groves (VCG) mechanisms. These are explainable mechanisms that induce truthful bids from the suppliers as well as maximize the social welfare. We show their efficacy through carefully designed thought experiments. Our field studies of FCs give us the confidence that such mechanisms, if deployed systematically, can become a game changer, benefiting a massive community of smallholder farmers.","PeriodicalId":268672,"journal":{"name":"Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies","volume":"67 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116373287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As community-driven organizations sought to support their constituents through the COVID-19 crisis, many drew on digital volunteers to expand their capacity and reach. However, coordinating the efforts of virtual volunteers is a challenging task with few empirical studies of the associated risks and best practices. In this paper, we report on the activities of CGNet Swara, a citizen journalism platform that published 401 distress calls from vulnerable communities stranded in India due to the imposition of a nationwide lockdown. CGNet mobilized 11 digital volunteers to help these contributors over a period of nearly 2 months. We found that a lack of proper guidance to digital volunteers and outdated organizational policies resulted in demonstrable harms to vulnerable communities. We discuss risks that are inherent in collaborations between organizations extending themselves to crisis response and emergent groups of digital volunteers, and how they can be mitigated by real-time monitoring and development of standard operating procedures relating to impact metrics, verification standards and disclosure policies.
{"title":"Mobilizing Digital Volunteers to Support Underserved Communities in India During COVID-19 Lockdowns","authors":"Devansh Mehta, Vishnu Prasad, Tarun Chitta, Nenavath Srinivas Naik, A. Prakash, Aditya Vashistha","doi":"10.1145/3530190.3534827","DOIUrl":"https://doi.org/10.1145/3530190.3534827","url":null,"abstract":"As community-driven organizations sought to support their constituents through the COVID-19 crisis, many drew on digital volunteers to expand their capacity and reach. However, coordinating the efforts of virtual volunteers is a challenging task with few empirical studies of the associated risks and best practices. In this paper, we report on the activities of CGNet Swara, a citizen journalism platform that published 401 distress calls from vulnerable communities stranded in India due to the imposition of a nationwide lockdown. CGNet mobilized 11 digital volunteers to help these contributors over a period of nearly 2 months. We found that a lack of proper guidance to digital volunteers and outdated organizational policies resulted in demonstrable harms to vulnerable communities. We discuss risks that are inherent in collaborations between organizations extending themselves to crisis response and emergent groups of digital volunteers, and how they can be mitigated by real-time monitoring and development of standard operating procedures relating to impact metrics, verification standards and disclosure policies.","PeriodicalId":268672,"journal":{"name":"Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies","volume":"55 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131711179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The COVID-19 pandemic continues to have a significant impact on people's lives worldwide. Research has shown that these impacts are distinct for different populations and often exasperate existing inequities and challenges. Within this landscape, the experiences of refugees with disabilities and mental health challenges are understudied. There is a need to better understand the challenges that refugees with disabilities and their families face in host countries during the pandemic and investigate strategies used to overcome them to inform future inclusive pandemic preparedness efforts. In this paper, we report findings from interviews conducted during the first year of the COVID-19 pandemic with four experts who serve refugees in the US. Participants described the impact of the pandemic on refugees, explained challenges that the prevailing political conditions of the time added to refugees’ experiences, and identified several strategies for resilience they experienced in the communities they serve.
{"title":"Note: “Fear is Grounded in Reality”: The Impact of the COVID-19 Pandemic on Refugees’ Access to Health and Accessibility Resources in the United States","authors":"Foad Hamidi, Zulekha Karachiwalla","doi":"10.1145/3530190.3534851","DOIUrl":"https://doi.org/10.1145/3530190.3534851","url":null,"abstract":"The COVID-19 pandemic continues to have a significant impact on people's lives worldwide. Research has shown that these impacts are distinct for different populations and often exasperate existing inequities and challenges. Within this landscape, the experiences of refugees with disabilities and mental health challenges are understudied. There is a need to better understand the challenges that refugees with disabilities and their families face in host countries during the pandemic and investigate strategies used to overcome them to inform future inclusive pandemic preparedness efforts. In this paper, we report findings from interviews conducted during the first year of the COVID-19 pandemic with four experts who serve refugees in the US. Participants described the impact of the pandemic on refugees, explained challenges that the prevailing political conditions of the time added to refugees’ experiences, and identified several strategies for resilience they experienced in the communities they serve.","PeriodicalId":268672,"journal":{"name":"Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116802150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies","authors":"","doi":"10.1145/3530190","DOIUrl":"https://doi.org/10.1145/3530190","url":null,"abstract":"","PeriodicalId":268672,"journal":{"name":"Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123986069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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