Algorithmic Accountability

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Algorithmic accountability asks who is responsible when automated systems affect people, what evidence is needed to evaluate decisions, and how people can challenge or remedy harms. Approaches include audits and impact assessments, explanations and causal attribution, documentation and provenance, legal oversight and public-interest litigation, and mechanisms for contestation and redress. Researchers examine settings such as public services, hiring, advertising, and multi-agent AI, where responsibility may be spread across developers, vendors, deployers, and institutions. A central tension is that transparency and formal compliance can reveal system details without making decisions genuinely reviewable or providing effective remedies.

Latest papers

33 papers3 papers in the last four weeks, down 25% on the four weeks before. 0.0% of all new papers.

From Explaining to Enabling: Actionable Transparency in Algorithmic Insurance Pricing
Oct 25, 2026Agathe Fernandes Machado, Fei HuangAlgorithmic Recourse Algorithmic Accountability
Département de Mathématiques, Université du Québec à Montréal, Montréal (UQAM), Québec, Canada · School of Risk and Actuarial Studies, UNSW Business School, UNSW, Sydney, New South Wales, Australia
Causal Humility: Governing the Authority of Fairness Claims Under Causal Uncertainty
Oct 19, 2026Khadija Zanna, Rodrigo Ferreira, Frederick L. Oswald +1Algorithmic Fairness Algorithmic Accountability
Rice University, Houston, Texas, USA · University of California, Irvine, Irvine, California, USA
Becoming Suspicious Across Borders: Algorithmic Extraterritoriality and AI-Driven Financial Surveillance
Oct 2, 2026Georgios Pavlidis, Savvas Chatzichristofis, Eleni GavriilAlgorithmic Accountability
Neapolis University Pafos, Cyprus
It Is Not My Code Anymore
Sep 8, 2026Augusto CamargoAlgorithmic Accountability Code Generation Evaluation
Institute of Mathematics, Statistics and Computer Science (IME) University of São Paulo, São Paulo, Brazil
Bonded Recourse for Smart-Contract Settlement of Compensable Agent Side Effects
Sep 1, 2026Laurent Bindschaedler, Quentin Botha, Christoph SiebenbrunnerAlgorithmic Accountability AI Agent Governance
Max Planck Institute for Software Systems · Research Institute for Cryptoeconomics, Vienna University of Economics and Business
Causal Evidentiary Governance for High-Risk Machine Learning Systems
Sep 1, 2026Samah Kareem, Barış ÇeliktaşAlgorithmic Auditing Algorithmic Accountability
Department of Computer Engineering, Isik University, Istanbul, Türkiye. · Department of Computer Engineering, I¸sık University, Istanbul, Türkiye.
When the Algorithm Becomes the Brand Crisis: A Sociotechnical Theory of Distributed Responsibility and Accountable Transparency
Sep 1, 2026Mohammad Saleh Torkestani, Taha MansouriAlgorithmic Accountability Responsible AI
University of Exeter, UK · University of Salford, UK
Peer Oversight in Collective Decision Making
Aug 28, 2026Sarah Mohsen, Pavel NaumovShared Decision-Making Multi-Agent Systems
School of Electronics and Computer Science University of Southampton, United Kingdom
LAAF: A Layered Accountability Architecture Framework for LLM Applications
Aug 27, 2026Prachi Chaturvedi, Shahnawaz Ahmad, Ehsan Nowroozi +5AI Accountability Algorithmic Accountability
School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India · Centre for Sustainable Cyber Security (CS2), University of Greenwich, United Kingdom · School of Electrical Engineering, Computing & Mathematical Sciences, Curtin University, Australia +1
HANSARD: A Reference Architecture for Forensic Readiness, Runtime Witnessing, and Graded Attribution in Autonomous Multi-Agent AI Systems
Aug 23, 2026Christos Sardianos, Iliana Pla, Vasilis Efthymiou +4AI Agent Monitoring Algorithmic Accountability
Department of Informatics and Telematics, Harokopio University of Athens, Athens, Greece · Department of Informatics, Faculty of Science, Democritus University of Thrace, Kavala, Greece · Department of Electrical and Computer Engineering, University of Western Macedonia, Kozani, Greece +1
Auditing Recorded Predictive Lead Service-Line Classifications Against Physical Verification: A Statewide Study of New York
Aug 20, 2026Muhammad Sarmad SohailClassification Algorithmic Auditing
Independent researcher
Scaling, Lock-In, and Proxy Compliance: A Political Economy of Responsible AI
Jul 30, 2026Florian A. D. Burnat, Brittany I. DavidsonAlgorithmic Auditing Algorithmic Accountability
University of Bath, Bath, UK.
Global Index on Responsible AI: 2026 Report
Jul 16, 2026Rachel Adams, Fola Adeleke, Ayantola Alayande +4Algorithmic Accountability AI Governance
Byzantine Accountability Without Consensus: Strong Eventual Consistency for Non-Associative, Stochastic, Robust Aggregation
Jul 11, 2026Ryan GillespieByzantine-Robust Federated Learning Algorithmic Accountability
Independent researcher
Machine-Coached Policy Revision in Adaptive Agent-Based Regulatory Simulation: A Controller-Level Contestability Layer
Jun 15, 2026Roberto GarroneExplainable Artificial Intelligence Algorithmic Accountability
Open University of Cyprus
Selective Control under Noisy Perception: Governance Failures Hidden by Aggregate Metrics in Modular Networks
Jun 12, 2026Igor ItkinAlgorithmic Accountability Content Moderation
Independent Researcher, Tel Aviv, Israel
"Is This Not Enough?": Asymmetries in Institutional Accountability and Collective Sensemaking in the Case of Canada's Algorithmic Visa Triage System
Jun 11, 2026Dipto Das, Matthew Tamura, Syed Ishtiaque Ahmed +1AI-Assisted Decision Making Algorithmic Auditing
Department of Computer Science University of Toronto Toronto, Ontario, Canada · Faculty of Information University of Toronto Toronto, Ontario, Canada
Responsible Agentic AI Requires Explicit Provenance
May 16, 2026Jinwei Hu, Xinmiao Huang, Qisong He +3Data Provenance Algorithmic Accountability
School of Computer Science and Informatics, University of Liverpool, UK · Department of Computer Science, Mohamed bin Zayed University of Artificial Intelligence, UAE
Some[Body] Must Receive That Pain for Agent Accountability
May 16, 2026Botao Amber Hu, Helena RongAI Accountability Algorithmic Accountability
University of Oxford · Oxford, UK · New York University Shanghai +1
Explainable AI Isn't Enough! Rethinking Algorithmic Contestability
May 15, 2026Timo Freiesleben, Kristof Meding, Gunnar KönigExplainable Artificial Intelligence Algorithmic Accountability
LMU Munich, Germany · Munich Center for Machine Learning (MCML) · Munich Center for Mathematical Philosophy (MCMP) +3
Counterfactual Reasoning for Causal Responsibility Attribution in Probabilistic Multi-Agent Systems
May 13, 2026Chunyan Mu, Muhammad NajibAlgorithmic Accountability Causal Attribution
University of Aberdeen · Heriot-Watt University
From Code-Centric to Intent-Centric Software Engineering: A Reflexive Thematic Analysis of Generative AI, Agentic Systems, and Engineering Accountability
May 10, 2026Elyson De La CruzSoftware Engineering Agents Algorithmic Accountability
University of the Cumberlands, United States
How Supply Chain Dependencies Complicate Bias Measurement and Accountability Attribution in AI Hiring Applications
Apr 24, 2026Gauri Sharma, Maryam MolamohammadiAlgorithmic Auditing Algorithmic Accountability
Mila Quebec AI Institute · Montreal, Quebec, Canada
Reckoning with the Political Economy of AI: Avoiding Decoys in Pursuit of Accountability
Apr 17, 2026Janet Vertesi, danah boyd, Alex Taylor +1AI Accountability Algorithmic Accountability
Princeton University, Princeton, NJ USA · Cornell University, Ithaca, NY, USA · University of Edinburgh, Edinburgh, UK +1
Bureaucratic Silences: What the Canadian AI Register Reveals, Omits, and Obscures
Apr 16, 2026Dipto Das, Christelle Tessono, Syed Ishtiaque Ahmed +1Algorithmic Accountability AI Governance
Department of Computer Science · University of Toronto · Toronto, Ontario, Canada +1
The Accountability Horizon: An Impossibility Theorem for Governing Human-Agent Collectives
Apr 9, 2026Haileleol Tibebu, Hewan ShemtagaAI Agent Governance Algorithmic Accountability
University of Illinois at Urbana-Champaign, Champaign, IL, USA · Responsible Intelligence Institute, Addis Ababa, Ethiopia
Algorithmic Administration and the EU AI Act: Legal Principles for Public Sector Use of AI
Mar 24, 2026Georgios Pavlidis, Ioannis KastanasAI Governance AI-Assisted Decision Making
Jean Monnet Center of Excellence AI-2-TRACE-CRIME, Neapolis University Pafos · Associate Professor of International and EU Economic Law, UNESCO Chair & Jean Monnet Chair, School of Law, Neapolis University Pafos, Cyprus · Lecturer of Public Law, Team Member of the Jean Monnet Center of Excellence AI-2-TRACE-CRIME, Neapolis University Pafos, Cyprus
Position: Multi-Agent Algorithmic Care Systems Demand Contestability for Trustworthy AI
Mar 21, 2026Truong Thanh Hung Nguyen, Hélène Fournier, Piper Jackson +4Multi-Agent Systems Algorithmic Accountability
Analytics Everywhere Lab, University of New Brunswick, Canada · National Research Council Canada, Canada · Thompson Rivers University, Canada +2
The DSA's Blind Spot: Algorithmic Audit of Advertising and Minor Profiling on TikTok
Mar 5, 2026Sara Solarova, Matej Mosnar, Matus Tibensky +6Online Advertising Algorithmic Accountability
Kempelen Institute of Intelligent Technologies, Bratislava, Slovakia · Comenius University Bratislava, Bratislava, Slovakia
Representation Fidelity:Auditing Algorithmic Decisions About Humans Using Self-Descriptions
Mar 5, 2026Theresa Elstner, Martin PotthastAlgorithmic Auditing Algorithmic Accountability
Kassel University, Germany

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From Explaining to Enabling: Actionable Transparency in Algorithmic Insurance Pricing

Agathe Fernandes Machado, Fei Huang

Département de Mathématiques, Université du Québec à Montréal, Montréal (UQAM), Québec, Canada · School of Risk and Actuarial Studies, UNSW Business School, UNSW, Sydney, New South Wales, Australia

Algorithmic Recourse Algorithmic Accountability Counterfactual Explanations

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Machine learning (ML) systems increasingly make consequential decisions about individuals, including credit, hiring, and insurance. Research on ML-driven insurance pricing has asked how the pricing mechanism itself can be made accountable. Yet it remains unclear how an individual policyholder's algorithmically determined premium should be explained to them. We argue that a useful explanation must be valid, actionable, and reliable. A valid recommendation lowers the premium according to the model. An actionable recommendation changes only characteristics the policyholder can control. A reliable recommendation has an actual outcome that is likely to meet the target, even in sparsely observed regions of the feature space where the model is uncertain. We formalize these three requirements as axioms and develop a method that turns an algorithmic premium into recommendations that meet them. The method meets the third requirement with a Conformal Prediction constraint, which screens out recommendations that the model is too uncertain about and thereby bounds the rate of unreliable recommendations. We apply four Counterfactual Explanation techniques to 57,832 real Florida flood-insurance claims and 98,058 synthetic driver-telematics policies. We adapt these techniques for insurance applications, so that their recommendations change only controllable characteristics and resemble policyholders observed in the data. In our illustrations, the constrained recommendations for high-risk policyholders are both more reliable and associated with larger predicted risk reductions than the unconstrained ones. These results suggest that insurers can give policyholders explanations that are both actionable and trustworthy. The work contributes to research on algorithmic accountability and offers implications for insurers and regulators.