ArticleNature2021
Measuring algorithmically infused societies.
Article in Nature, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 132 citations in OpenAlex.
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- Beyond the brain: a computational MRI-derived neurophysiological framework for robotic conscious capacity.Neuroscience and biobehavioral reviews · 2025Review
- A dynamical measure of algorithmically infused visibility.Royal Society open science · 2025Article
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- Social Drivers and Algorithmic Mechanisms on Digital Media.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024Review
- Challenges in Understanding Human-Algorithm Entanglement During Online Information Consumption.Perspectives on psychological science : a journal of the Association for Psychological Science · 2024Article
- Crowdsourced audit of Twitter's recommender systems.Scientific reports · 2023Article
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- Using the Veil of Ignorance to align AI systems with principles of justice.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
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- Digital data donations: A quest for best practices.Patterns (New York, N.Y.) · 2022Article
- The future of human behaviour research.Nature human behaviour · 2022Article
- Open Debates Conducive for Vaccination Rate Flatlines: A Scoping Review and Convergent Cross Mapping.Frontiers in public health · 2022Article
- Inoculating against the spread of Islamophobic and radical-Islamist disinformation.Cognitive research: principles and implications · 2021Article
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Authors and funding
6 authors at 3 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It has been the historic responsibility of the social sciences to investigate human societies. Fulfilling this responsibility requires social theories, measurement models and social data. Most existing theories and measurement models in the social sciences were not developed with the deep societal reach of algorithms in mind. The emergence of 'algorithmically infused societies'-societies whose very fabric is co-shaped by algorithmic and human behaviour-raises three key challenges: the insufficient quality of measurements, the complex consequences of (mis)measurements, and the limits of existing social theories. Here we argue that tackling these challenges requires new social theories that account for the impact of algorithmic systems on social realities. To develop such theories, we need new methodologies for integrating data and measurements into theory construction. Given the scale at which measurements can be applied, we believe measurement models should be trustworthy, auditable and just. To achieve this, the development of measurements should be transparent and participatory, and include mechanisms to ensure measurement quality and identify possible harms. We argue that computational social scientists should rethink what aspects of algorithmically infused societies should be measured, how they should be measured, and the consequences of doing so.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.