Niko Tsakalakis, L. Carmichael, Sophie Stalla-Bourdillon, L. Moreau, D. Huynh, Ayah Helal
Automated decision making continues to be used for a variety of purposes within a multitude of sectors. Ultimately, what makes a ‘good’ explanation is a focus not only for the designers and developers of AI systems, but for many disciplines, including law, philosophy, psychology, history, sociology and human-computer interaction. Given that the generation of compliant, valid and effective explanations for AI requires a high-level of critical, interdisciplinary thinking and collaboration, this area is therefore of particular interest for Web Science. The workshop ‘Explanations for AI: Computable or Not?’ (exAI’20) aims to bring together researchers, practitioners and representatives of those subjected to socially-sensitive decision-making to exchange ideas, methods and challenges as part of an interdisciplinary discussion on explanations for AI. It is hoped that this workshop will build a cross-sectoral, multi-disciplinary and international network of people focusing on explanations for AI, and an agenda to drive this work forward. exAI’20 will hold two position paper sessions, where the panel members and workshop attendees will debate the following key issues in an interactive dialogue: The sessions are hoped to stimulate a lively debate on whether explanations for AI are computable or not by providing time for an interactive discussion after each paper. The discussion will uncover key arguments for and against the computability of explanations for AI related to socially-sensitive decision-making. An introductory keynote from the team behind the project PLEAD (Provenance-Driven & Legally Grounded Explanations for Automated Decisions) will present use cases, scenarios and the practical experience of explanations for AI. The keynote will serve as a starting point for the discussions during the paper sessions about the rationale, technologies and/or organisations measures used; and, accounts from different perspectives – e.g. software designers, implementers and those subject to automated decision-making. By the end of this workshop, attendees will have gained a good insight into the critiques and the advantages of explanations for AI, including the extent in which explanations can or should be made computable. They will have the opportunity to participate and inform the discussions on complex topics about AI explainability, such as the legal requirements for explanations, the extent in which data ethics may drive explanations for AI, reflections on the similarities and differences of explanations for AI decisions and manual decisions, as well as what makes a ‘good’ explanation and the etymology of explanations for socially-sensitive decisions. exAI’20 is supported by the Engineering and Physical Sciences Research Council [grant number EP/S027238/1]. We would like to thank the organizers of the Web Science 2019 conference for agreeing to host our workshop and for their support.
{"title":"Explanations for AI: Computable or Not?","authors":"Niko Tsakalakis, L. Carmichael, Sophie Stalla-Bourdillon, L. Moreau, D. Huynh, Ayah Helal","doi":"10.1145/3394332.3402900","DOIUrl":"https://doi.org/10.1145/3394332.3402900","url":null,"abstract":"Automated decision making continues to be used for a variety of purposes within a multitude of sectors. Ultimately, what makes a ‘good’ explanation is a focus not only for the designers and developers of AI systems, but for many disciplines, including law, philosophy, psychology, history, sociology and human-computer interaction. Given that the generation of compliant, valid and effective explanations for AI requires a high-level of critical, interdisciplinary thinking and collaboration, this area is therefore of particular interest for Web Science. The workshop ‘Explanations for AI: Computable or Not?’ (exAI’20) aims to bring together researchers, practitioners and representatives of those subjected to socially-sensitive decision-making to exchange ideas, methods and challenges as part of an interdisciplinary discussion on explanations for AI. It is hoped that this workshop will build a cross-sectoral, multi-disciplinary and international network of people focusing on explanations for AI, and an agenda to drive this work forward. exAI’20 will hold two position paper sessions, where the panel members and workshop attendees will debate the following key issues in an interactive dialogue: The sessions are hoped to stimulate a lively debate on whether explanations for AI are computable or not by providing time for an interactive discussion after each paper. The discussion will uncover key arguments for and against the computability of explanations for AI related to socially-sensitive decision-making. An introductory keynote from the team behind the project PLEAD (Provenance-Driven & Legally Grounded Explanations for Automated Decisions) will present use cases, scenarios and the practical experience of explanations for AI. The keynote will serve as a starting point for the discussions during the paper sessions about the rationale, technologies and/or organisations measures used; and, accounts from different perspectives – e.g. software designers, implementers and those subject to automated decision-making. By the end of this workshop, attendees will have gained a good insight into the critiques and the advantages of explanations for AI, including the extent in which explanations can or should be made computable. They will have the opportunity to participate and inform the discussions on complex topics about AI explainability, such as the legal requirements for explanations, the extent in which data ethics may drive explanations for AI, reflections on the similarities and differences of explanations for AI decisions and manual decisions, as well as what makes a ‘good’ explanation and the etymology of explanations for socially-sensitive decisions. exAI’20 is supported by the Engineering and Physical Sciences Research Council [grant number EP/S027238/1]. We would like to thank the organizers of the Web Science 2019 conference for agreeing to host our workshop and for their support.","PeriodicalId":435721,"journal":{"name":"Companion Publication of the 12th ACM Conference on Web Science","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123452999","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}
Recommender systems and content personalization systems use algorithms that optimize for a given factor.We are interested in developing content recommendation algorithms that optimize for user well-being. In previous work, we showed that content can have large, significant impacts on users’ well-being. In this paper, we present the results of two large studies that show (1) people sometimes come to social media with the specific goal of improving their well-being and (2) that personalization systems can effectively recommend social media content that improves well-being.
{"title":"Improving Emotional Well-Being on Social Media with Collaborative Filtering","authors":"J. Golbeck","doi":"10.1145/3394332.3402833","DOIUrl":"https://doi.org/10.1145/3394332.3402833","url":null,"abstract":"Recommender systems and content personalization systems use algorithms that optimize for a given factor.We are interested in developing content recommendation algorithms that optimize for user well-being. In previous work, we showed that content can have large, significant impacts on users’ well-being. In this paper, we present the results of two large studies that show (1) people sometimes come to social media with the specific goal of improving their well-being and (2) that personalization systems can effectively recommend social media content that improves well-being.","PeriodicalId":435721,"journal":{"name":"Companion Publication of the 12th ACM Conference on Web Science","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130528207","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}
This paper applies a trans-disciplinary analysis on the issue of data sovereignty, from an African perspective. The paper interrogates the residence of data and the African prerogatives for its processing. Harvesting from experiences in Zimbabwean health systems, this paper suggests that African governments can steward the collection and appropriate use of data resources, applying the principles of data sovereignty.
{"title":"Data Sovereignty: A Perspective From Zimbabwe","authors":"M. Mawere, G. Stam","doi":"10.1145/3394332.3402823","DOIUrl":"https://doi.org/10.1145/3394332.3402823","url":null,"abstract":"This paper applies a trans-disciplinary analysis on the issue of data sovereignty, from an African perspective. The paper interrogates the residence of data and the African prerogatives for its processing. Harvesting from experiences in Zimbabwean health systems, this paper suggests that African governments can steward the collection and appropriate use of data resources, applying the principles of data sovereignty.","PeriodicalId":435721,"journal":{"name":"Companion Publication of the 12th ACM Conference on Web Science","volume":"350 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123117023","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}
In this paper we discuss how to improve business sustainability of services for digital inclusion through value modeling and analysis using the e3-value method. Two questions come up: is this method understandable and useful in practice for ICT4D practitioners and developers, and is this method instrumental for development of sustainable services for digital inclusion? To answer this, three ICT4D student projects were carried out, that aim to improve digital inclusion in communities in Sarawak, Malaysia. Results show that the e3-value method is easy to learn and use in practice. It is instrumental (i) for visual conceptualization, facilitating discussion and co-construction of different business scenarios; (ii) it allows to assess potential profitability in the value web; (iii) for optimization of the system design (iv) to analyse strengths and weaknesses in the value network in terms of digital inclusion.
{"title":"Digital inclusion requires a business model too: Sustainability analysis of value webs in rural Sarawak","authors":"A. Bon, J. Gordijn, W. Cheah","doi":"10.1145/3394332.3402832","DOIUrl":"https://doi.org/10.1145/3394332.3402832","url":null,"abstract":"In this paper we discuss how to improve business sustainability of services for digital inclusion through value modeling and analysis using the e3-value method. Two questions come up: is this method understandable and useful in practice for ICT4D practitioners and developers, and is this method instrumental for development of sustainable services for digital inclusion? To answer this, three ICT4D student projects were carried out, that aim to improve digital inclusion in communities in Sarawak, Malaysia. Results show that the e3-value method is easy to learn and use in practice. It is instrumental (i) for visual conceptualization, facilitating discussion and co-construction of different business scenarios; (ii) it allows to assess potential profitability in the value web; (iii) for optimization of the system design (iv) to analyse strengths and weaknesses in the value network in terms of digital inclusion.","PeriodicalId":435721,"journal":{"name":"Companion Publication of the 12th ACM Conference on Web Science","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122832697","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}
To build a human-centric Web, we need a solid understanding of human connections online and of mechanisms for fostering such connections. People both perceive and respond to digital technologies and form connections with one another in diverse ways. Whether the goal is to improve engagement or to foster community, modelling user groups to personalise or tailor experiences can be key. Tailoring and connection-building are particularly crucial in spaces such as healthcare and education, where evidence clearly shows that perceived social support can facilitate learning and enhance outcomes. PC’20 is a half-day workshop including two invited speakers, two discussion papers, and a broader discussion session. The first keynote is from Su White, an Associate Professor at the University of Southampton. She will speak about the facilitation of education online. The second keynote is from Michael Fergusson, CEO of Ayogo Health Inc. He will speak about “The Architecture of Choice: Using Psychosocial Variables to Dynamically Tailor Interventions.” A session will highlight two discussion papers. Firstly, Jennifer Golbeck from the University of Maryland will present her work “Improving Emotional Well-Being on Social Media with Collaborative Filtering”. Secondly, Roushdat Elaheebocus, Poovanen Seenan, Sheekah Beharry and Girishsing Caussyram from the University of Mauritius will present their work “BehaviourCoach: A Customisable and Socially-Enhanced Exergaming Application Development Framework”. Finally, a broader discussion session will consider: tools, techniques and case studies in tailoring and community-building; how these relate to one another; and next steps for Web Science researchers. The workshop builds on health and education communities established through previous Web Science conference workshops. By using these two domains to ground discussion of user modelling and community, we intend to reinvigorate these communities. A summary of the workshop will be created and shared online within two weeks of the event. We thank the members of our program committee: Stéphane Bazan (TomKeen) and Charlie Hargood (University of Bournemouth).
{"title":"Personalisation and Community 2020: User Modelling and Social Connections in Web Science, Healthcare and Education: Chairs’ Welcome and Workshop Summary","authors":"C. Hooper, M. Bernstein, M. Weal","doi":"10.1145/3394332.3402895","DOIUrl":"https://doi.org/10.1145/3394332.3402895","url":null,"abstract":"To build a human-centric Web, we need a solid understanding of human connections online and of mechanisms for fostering such connections. People both perceive and respond to digital technologies and form connections with one another in diverse ways. Whether the goal is to improve engagement or to foster community, modelling user groups to personalise or tailor experiences can be key. Tailoring and connection-building are particularly crucial in spaces such as healthcare and education, where evidence clearly shows that perceived social support can facilitate learning and enhance outcomes. PC’20 is a half-day workshop including two invited speakers, two discussion papers, and a broader discussion session. The first keynote is from Su White, an Associate Professor at the University of Southampton. She will speak about the facilitation of education online. The second keynote is from Michael Fergusson, CEO of Ayogo Health Inc. He will speak about “The Architecture of Choice: Using Psychosocial Variables to Dynamically Tailor Interventions.” A session will highlight two discussion papers. Firstly, Jennifer Golbeck from the University of Maryland will present her work “Improving Emotional Well-Being on Social Media with Collaborative Filtering”. Secondly, Roushdat Elaheebocus, Poovanen Seenan, Sheekah Beharry and Girishsing Caussyram from the University of Mauritius will present their work “BehaviourCoach: A Customisable and Socially-Enhanced Exergaming Application Development Framework”. Finally, a broader discussion session will consider: tools, techniques and case studies in tailoring and community-building; how these relate to one another; and next steps for Web Science researchers. The workshop builds on health and education communities established through previous Web Science conference workshops. By using these two domains to ground discussion of user modelling and community, we intend to reinvigorate these communities. A summary of the workshop will be created and shared online within two weeks of the event. We thank the members of our program committee: Stéphane Bazan (TomKeen) and Charlie Hargood (University of Bournemouth).","PeriodicalId":435721,"journal":{"name":"Companion Publication of the 12th ACM Conference on Web Science","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115583093","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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