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2. Making AI Machines Work for Humans in FoW

Author

Basu Roy, Senjuti, Chen, Lei, Morishima, Atsuyuki, Monedero, James, Bourhis, Pierre, Charoy, François, Danilevsky, Marina, Das, Gautam, Demartini, Gianluca, Dubey, Abishek, Elbassuoni, Shady, Gross-Amblard, David, Hoareau, Emilie, Inoguchi, Munenari, Kenworthy, Jared, Kitahara, Itaru, Lee, Dongwon, Li, Yunyao, Borromeo, Ria Mae, Papotti, Paolo, Rao, Raghav, Roy, Sudeepa, Senellart, Pierre, Tajima, Keishi, Thirumuruganathan, Saravanan, Tommasi, Marion, Umemoto, Kazutoshi, Wiggins, Andrea, Yoshida, Koichiro, Amer-Yahia, Sihem, New Jersey Institute of Technology [Newark] (NJIT), Hong Kong University of Science and Technology (HKUST), Université de Tsukuba = University of Tsukuba, Rutgers University System (Rutgers), Self-adaptation for distributed services and large software systems (SPIRALS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Web Scale Trustworthy Collaborative Service Systems (COAST), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Networks, Systems and Services (LORIA - NSS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), IBM Almaden Research Center [San Jose], IBM, University of Texas at Arlington [Arlington], University of Queensland [Brisbane], Vanderbilt University [Nashville], American University of Beirut [Beyrouth] (AUB), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire d'Informatique de Grenoble (LIG), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), University of Toyama, Pennsylvania State University (Penn State), Penn State System, University of the Philippines Open University (UPOU), Eurecom [Sophia Antipolis], The University of Texas at San Antonio (UTSA), Duke University [Durham], Value from Data (VALDA ), Département d'informatique - ENS Paris (DI-ENS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria), Institut Universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), Kyoto University, Qatar Computing Research Institute [Doha, Qatar] (QCRI), Department of Mathematical Informatics (University of Tokyo), The University of Tokyo (UTokyo), University of Nebraska Omaha, University of Nebraska System, CrowdWorks Inc., ANR-19-P3IA-0003,MIAI,MIAI @ Grenoble Alpes(2019), ANR-16-CE23-0015,HEADWORK,Processus massivement participatifs d'acquisition de données et de connaissances(2016), Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Département d'informatique de l'École normale supérieure (DI-ENS), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Kyoto University [Kyoto], University of Nebraska [Omaha], Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille-Centrale Lille-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Inria de Paris

Subjects
Knowledge management, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], ComputingMilieux_THECOMPUTINGPROFESSION, business.industry, Computer science, media_common.quotation_subject, 05 social sciences, 02 engineering and technology, Crowdsourcing, Work performance, Frontier, Work (electrical), 020204 information systems, Perception, 0202 electrical engineering, electronic engineering, information engineering, 0501 psychology and cognitive sciences, [INFO]Computer Science [cs], business, 050107 human factors, Software, ComputingMilieux_MISCELLANEOUS, Information Systems, media_common
Abstract

The Future of Work (FoW) is witnessing an evolution where AI systems (broadly machines or businesses) are used to the benefit of humans. Work here refers to all forms of paid and unpaid labor in both physical and virtual workplaces and that is enabled by AI systems. This covers crowdsourcing platforms such as Amazon Mechanical Turk, online labor marketplaces such as TaskRabbit and Qapa, but also regular jobs in physical workplaces. Bringing humans back to the frontier of FoW will increase their trust in AI systems and shift their perception to use them as a source of self-improvement, ensure better work performance, and positively shape social and economic outcomes of a society and a nation. To enable that, physical and virtual workplaces will need to capture human traits, behavior, evolving needs, and provide jobs to all. Attitudes, values, opinions regarding the processes and policies will need to be assessed and considered in the design of FoW ecosystems.

Published
2020

3. Fairness in Online Jobs: {A} Case Study on TaskRabbit and Google

Author

Amer-Yahia, Sihem, Elbassuoni, Shady, Ghizzawi, Ahmad, Borromeo, Ria, Hoareau, Emilie, Mulhem, Philippe, Laboratoire d'Informatique de Grenoble (LIG), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), American University of Beirut [Beyrouth] (AUB), University of the Philippines Open University (UPOU), Grenoble Institut d'Administration des Entreprises (UGA INP IAE), Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Modélisation et Recherche d’Information Multimédia [Grenoble] (MRIM ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), and ANR-19-P3IA-0003,MIAI,MIAI @ Grenoble Alpes(2019)

Subjects
[INFO]Computer Science [cs]
Abstract

International audience; Online job marketplaces are becoming very popular. Either jobs or people are ranked by algorithms. For example, Google and Facebook job search return a ranked list of jobs given a search query. TaskRabbit and Fiverr, on the other hand, produce rank-ings of workers for a given query. Qapa, an online marketplace, can be used to rank both workers and jobs. In this paper, we develop a unified framework for fairness to study ranking workers and jobs. We case study two particular sites: Google job search and TaskRabbit. Our framework addresses group fairness where groups are obtained with any combination of protected attributes. We define a measure for unfairness for a given group, query and location. We also define two generic fairness problems that we address in our framework: quantification, such as finding the k groups (resp., queries, locations) for which the site is most or least unfair, and comparison, such as finding the locations at which fairness between two groups differs from all locations, or finding the queries for which fairness at two locations differ from all queries. Since the number of groups, queries and locations can be arbitrarily large, we adapt Fagin top-k algorithms to address our fairness problems. To evaluate our framework, we run extensive experiments on two datasets crawled from TaskRabbit and Google job search.

Published
2020

4. Making AI Machines Work for Humans in FoW

Author

Amer-Yahia, Sihem, primary, Basu Roy, Senjuti, additional, Chen, Lei, additional, Morishima, Atsuyuki, additional, Abello Monedero, James, additional, Bourhis, Pierre, additional, Charoy, François, additional, Danilevsky, Marina, additional, Das, Gautam, additional, Demartini, Gianluca, additional, Elbassuoni, Shady, additional, Gross-Amblard, David, additional, Hoareau, Emilie, additional, Inoguchi, Munenari, additional, Kenworthy, Jared, additional, Kitahara, Itaru, additional, Lee, Dongwon, additional, Li, Yunyao, additional, Borromeo, Ria Mae, additional, Papotti, Paolo, additional, Rao, Raghav, additional, Roy, Sudeepa, additional, Senellart, Pierre, additional, Tajima, Keishi, additional, Thirumuruganathan, Saravanan, additional, Tommasi, Marion, additional, Umemoto, Kazutoshi, additional, Wiggins, Andrea, additional, and Yoshida, Koichiro, additional

Published
2020
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