Pub Date : 2022-01-27DOI: 10.1162/99608f92.a6dbaef3
N. Smith, M. Idris, Friederike Schüür, Rita Ko
With 82.4 million forcibly displaced people, we need new approaches to the global refugee crisis. The Hive, the innovation lab at USA for UNHCR, uses data, machine learning (ML), and other emerging technologies to improve lives for refugees in coordination and collaboration with UNHCR (United Nations High Commissioner for Refugees), known as the UN Refugee Agency. We outline five challenges in successfully leveraging data and emerging technologies in the humanitarian space that tend to be overlooked and share the Hive’s approach and evolution to tackling these challenges. From assembling the right team and finding the right partners to inclusive and impactful data innovation, the Hive has worked to apply industry techniques to the nonprofit sector since 2015. We hope that our insights can help guide data innovation efforts at other organizations in the humanitarian space.
{"title":"Data for Good, What Is It Good For?: Challenges, Opportunities, and Data Innovation in Service of Refugees","authors":"N. Smith, M. Idris, Friederike Schüür, Rita Ko","doi":"10.1162/99608f92.a6dbaef3","DOIUrl":"https://doi.org/10.1162/99608f92.a6dbaef3","url":null,"abstract":"With 82.4 million forcibly displaced people, we need new approaches to the global refugee crisis. The Hive, the innovation lab at USA for UNHCR, uses data, machine learning (ML), and other emerging technologies to improve lives for refugees in coordination and collaboration with UNHCR (United Nations High Commissioner for Refugees), known as the UN Refugee Agency. We outline five challenges in successfully leveraging data and emerging technologies in the humanitarian space that tend to be overlooked and share the Hive’s approach and evolution to tackling these challenges. From assembling the right team and finding the right partners to inclusive and impactful data innovation, the Hive has worked to apply industry techniques to the nonprofit sector since 2015. We hope that our insights can help guide data innovation efforts at other organizations in the humanitarian space.","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49113954","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}
Pub Date : 2022-01-27DOI: 10.1162/99608f92.5a0c7aaf
K. Kunzmann, Camilla Lingjærde, Sheila Bird, Sylvia Richardson
{"title":"The How Matters: Simulation-Based Assessment of the Potential Contributions of Lateral Flow Device Tests for Keeping Schools Open and COVID-Safe in England","authors":"K. Kunzmann, Camilla Lingjærde, Sheila Bird, Sylvia Richardson","doi":"10.1162/99608f92.5a0c7aaf","DOIUrl":"https://doi.org/10.1162/99608f92.5a0c7aaf","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45303499","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}
Pub Date : 2022-01-27DOI: 10.1162/99608f92.f09b190b
Thomas Casey
Editor’s Note: Social media has long been accused of contributing to mental health issues, but this call to action cuts to the heart of the matter: engagement with the platform has become the most important metric, and the algorithms that best produce results tap into negative bias of the users. Thomas Casey makes the case for a financial model that would be more beneficial to users of these platforms and society overall.
{"title":"Rethinking Engagement: Challenging the Financial Model of Social Media Platforms","authors":"Thomas Casey","doi":"10.1162/99608f92.f09b190b","DOIUrl":"https://doi.org/10.1162/99608f92.f09b190b","url":null,"abstract":"Editor’s Note: Social media has long been accused of contributing to mental health issues, but this call to action cuts to the heart of the matter: engagement with the platform has become the most important metric, and the algorithms that best produce results tap into negative bias of the users. Thomas Casey makes the case for a financial model that would be more beneficial to users of these platforms and society overall.","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45583790","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}
Pub Date : 2022-01-27DOI: 10.1162/99608f92.2f71a69e
Benedict Dooley
{"title":"The Role of FOMO in Digital Transformation","authors":"Benedict Dooley","doi":"10.1162/99608f92.2f71a69e","DOIUrl":"https://doi.org/10.1162/99608f92.2f71a69e","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46592674","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}
Pub Date : 2022-01-27DOI: 10.1162/99608f92.1b5c3b7b
L. Sharabi
Column Editor’s Note: Dating apps and online matchmaking are now a commonplace way for couples to meet and relationships to form. As human communications expert Liesel Sharabi explains, the algorithms underlying the matchmaking have evolved enormously in complexity over recent years, and our relationship with online dating apps have become a long-term prospect.
{"title":"Finding Love on a First Data: Matching Algorithms in Online Dating","authors":"L. Sharabi","doi":"10.1162/99608f92.1b5c3b7b","DOIUrl":"https://doi.org/10.1162/99608f92.1b5c3b7b","url":null,"abstract":"Column Editor’s Note: Dating apps and online matchmaking are now a commonplace way for couples to meet and relationships to form. As human communications expert Liesel Sharabi explains, the algorithms underlying the matchmaking have evolved enormously in complexity over recent years, and our relationship with online dating apps have become a long-term prospect.","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46277253","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}
Pub Date : 2022-01-27DOI: 10.1162/99608f92.162a0e48
Raiford Smith
{"title":"The Future of AI in Business: Chewbacca, Chatbots, and Why I Won’t Win at Ms. Pac Man","authors":"Raiford Smith","doi":"10.1162/99608f92.162a0e48","DOIUrl":"https://doi.org/10.1162/99608f92.162a0e48","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47640151","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}
Pub Date : 2022-01-27DOI: 10.1162/99608f92.a4d9a7c7
K. Donato, L. Singh, A. Arab, Elizabeth Jacobs, Douglas Post
{"title":"Misinformation about COVID-19 and Venezuelan Migration: Trends in Twitter Conversation during a Pandemic","authors":"K. Donato, L. Singh, A. Arab, Elizabeth Jacobs, Douglas Post","doi":"10.1162/99608f92.a4d9a7c7","DOIUrl":"https://doi.org/10.1162/99608f92.a4d9a7c7","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42568079","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}
Pub Date : 2022-01-27DOI: 10.1162/99608f92.68b503ea
Y. Weinstein
{"title":"Inspiring Quantum Data Analysts","authors":"Y. Weinstein","doi":"10.1162/99608f92.68b503ea","DOIUrl":"https://doi.org/10.1162/99608f92.68b503ea","url":null,"abstract":"","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42148573","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}
Pub Date : 2022-01-27DOI: 10.1162/99608f92.69c5328d
M. Kieferová, Y. Sanders
. Data-processing algorithms often require that the data is prepared in appropriate structures that are readily accessible or can be prepared on demand. Quantum computers derive their power from storing and manipulating quantum superpositions and could potentially speed up data science tasks. However, they often require input in the form of a quantum state that encodes a nonquantum data set. Here we describe some of the challenges of encoding nonquantum data for use by quantum computers
{"title":"Assume a Quantum Dataset","authors":"M. Kieferová, Y. Sanders","doi":"10.1162/99608f92.69c5328d","DOIUrl":"https://doi.org/10.1162/99608f92.69c5328d","url":null,"abstract":". Data-processing algorithms often require that the data is prepared in appropriate structures that are readily accessible or can be prepared on demand. Quantum computers derive their power from storing and manipulating quantum superpositions and could potentially speed up data science tasks. However, they often require input in the form of a quantum state that encodes a nonquantum data set. Here we describe some of the challenges of encoding nonquantum data for use by quantum computers","PeriodicalId":73195,"journal":{"name":"Harvard data science review","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48933433","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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