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Professor Taha Yasseri

Workday Chair of Technology and Society (Sociology)
      
Profile Photo

Professor Taha Yasseri

Workday Chair of Technology and Society (Sociology)

 TAHA.YASSERI@tcd.ie

 


Prof Taha Yasseri is Workday Chair and Professor Of Technology and Society at Trinity College Dublin and Technological University Dublin, where he directs the Joint Centre for Sociology of Humans and Machines (SOHAM). He is also an adjunct Full Professor at the School of Mathematics and Statistics at University College Dublin. He formerly was a Professor at the School of Sociology and a Geary Fellow at the Geary Institute for Public Policy at University College Dublin, Ireland. Formerly, he was a Senior Research Fellow in Computational Social Science at the University of Oxford, a Turing Fellow at the Alan Turing Institute for Data Science and Artificial Intelligence, and a Research Fellow in Humanities and Social Sciences at Wolfson College. Taha Yasseri has a PhD in Complex Systems Physics from the University of Göttingen, Germany. He has interests in analysis of large-scale transactional data and conducting behavioural experiments to understand human dynamics, machines" social behaviour, government-society interactions, online political behaviour, mass collaboration and collective intelligence, information and opinion dynamics, hate speech and content moderation, collective behaviour, and online dating.
Project Title
 AI-Enhanced Collective Intelligence
From
Sep 2022
To
Aug 2026
Summary
ANNETTE examines the opportunities for enhancing collective intelligence through deployment of artificial intelligence (AI) as a "team manager" and as a "team-mate" in crowd-based collaborative projects. Collective Intelligence refers to the emergent outcome of the collective efforts of many individuals and is superior to the individual intelligence of those who contributed to it. Internet-based technologies have boosted collective intelligence to an unprecedented level. Large scale collaborations among many individuals across geographical boundaries in Wikipedia or Citizen Science platforms are only a few realized possibilities. However, there are unresolved challenges in collective intelligence knowledge and practice, particularly when it comes to collaboration in a political context such as content moderation tasks on social media to battle misinformation and hate speech. The first issue I tackle is the paradox of "conflict and collaboration": the more diverse the pool of contributors to collective intelligence is, the more intelligent the group becomes, however, political diversity often leads to conflict. How to build teams that are diverse yet avoid opinion clashes and minimize conflict? I will propose and test a multidimensional matching system using AI "as a manager" to achieve this goal. A tightly related problem in deploying AI alongside humans in large-scale collaborative projects is "volunteer demotivation" resulting in a paradoxical decline in performance. To address this, I will study the use of AI "as a teammate", and seek team parameters and designs that maximize the retention and performance of hybrid AI-human teams. I will use behavioural experiments and agent-based simulation, combined with machine learning to examine how collective intelligence can be enhanced by AI, particularly in two cases of collaborative content moderation on social media platforms and volunteer-based citizen science projects. ANNETTE will advance the state-of-the-art in crowd-based teamwork and group organization through bridging to the fastdeveloping field of AI technologies.
Funding Agency
IRC
Programme
Laureate Award (Consolidator)

M Zhu, Taha Yasseri, J Kertész, Individual differences in knowledge network navigation, Scientific Reports, 14, (1), 2024, Journal Article, PUBLISHED  DOI
Hao Cui, Taha Yasseri, AI-enhanced Collective Intelligence, 2024, Journal Article, PUBLISHED  DOI
Milena Tsvetkova, Taha Yasseri, Niccolo Pescetelli, Tobias Werner, Human-machine social systems, 2024, Journal Article, PUBLISHED  DOI
Jason W Burton, Ezequiel Lopez-Lopez, Shahar Hechtlinger, Zoe Rahwan, Samuel Aeschbach, Michiel A Bakker, Joshua A Becker, Aleks Berditchevskaia, Julian Berger, Levin Brinkmann, Lucie Flek, Stefan M Herzog, Saffron Huang, Sayash Kapoor, Arvind Narayanan, Anne-Marie Nussberger, Taha Yasseri, Pietro Nickl, Abdullah Almaatouq, Ulrike Hahn, Ralf H J M Kurvers, Susan Leavy, Iyad Rahwan, Divya Siddarth, Alice Siu, Anita W Woolley, Dirk U Wulff, Ralph Hertwig, How large language models can reshape collective intelligence., Nature Human Behaviour, 2024, Journal Article, PUBLISHED  DOI
H Worrall-Carter, Taha Yasseri, From Black squares to White guilt: The influence of Black Lives Matter on non-Indigenous views of the Voice to Parliament referendum in Australia, Journal of Sociology, 2024, Journal Article, PUBLISHED  DOI
Milan Jovi", Lovro Šubelj, Tea Golob, Matej Makarovi", Taha Yasseri, Danijela Boberi" Krsti"ev, Srdjan Škrbi", Zoran Levnaji", Terrorist attacks sharpen the binary perception of "Us" vs. "Them"., Scientific Reports, 13, (1), 2023, p12451 , Journal Article, PUBLISHED  DOI
A Breu, Taha Yasseri, What drives passion? An empirical examination on the impact of personality trait interactions and job environments on work passion, Current Psychology, 42, (17), 2023, p14350--14367 , Journal Article, PUBLISHED  DOI
Taha Yasseri, From Print to Pixels: The Changing Landscape of the Public Sphere in the Digital Age, 2023, Journal Article, PUBLISHED
Melody Sepahpour-Fard, Michael Quayle, Maria Schuld, Taha Yasseri, Using word embeddings to analyse audience effects and individual differences in parenting Subreddits, 2023, Journal Article, PUBLISHED
Melody Sepahpour-Fard, Michael Quayle, Maria Schuld, Taha Yasseri, Using word embeddings to analyse audience effects and individual differences in parenting Subreddits, 2023, Journal Article, PUBLISHED  DOI
  

Page 1 of 10
Kelly, B.D., Political asylums, History Today, 66, (2), 2016, - 66, Miscellaneous, PUBLISHED

  


Award Date
Laureate Award 1 Sep 2022
Prof Yasseri has interest in analysis of large-scale transactional data and conducting behavioural experiments to understand human dynamics, mass collaboration and collective intelligence, conflict and collaboration, machines social behaviour, government-society interactions, online political behaviour, information and opinion dynamics, hate speech and content moderation, collective behaviour, and online dating.