CLOSED: Call for Papers: Special Issue on Trustworthy AI and Data Lineage

IEEE Internet Computing seeks submissions for this upcoming special issue.
Share this on:
Submissions Due: 05 May 2023

Important Dates

  • Paper submissions due: 5th May 2023
  • Publication: November/December 2023

Do you trust AI? Do you care about sources of data? If so, consider submitting a paper to this Special Issue.

Topics of interest include, but are not limited to, the following:

  • AI Trustworthiness properties, lifecycle, assurance
  • AI Safety and Robustness
  • End to End Responsible and Explainable AI Systems
  • Measurement, Analysis, Design for trust in AI models, datasets and pipelines (e.g. fair, robust, explainable) 
  • Data lineage challenges and applications: meta data tracking, sharing, exchange, and usage
  • Data centric and Model centric trustworthy AI techniques
  • Privacy preserving and secure AI
  • Data Lineage privacy and security
  • Analyzing tradeoffs in dimensions of trustworthy and efficient AI
  • Characterizing AI trustworthiness for different data and model types (NLP, Vision, Time series, RL, Graphs)
  • Decentralized ML data lineage and trust
  • Deployment and use
  • Verifying, validating, projecting
  • Human engagement, in the loop, ease of use
  • Standards, blueprints, best practices, repositories
  • Ethics, diversity, equity, and inclusion
  • Sustainability, scale, responsiveness
  • Governance, regulatory compliance
  • Industry verticals, e.g. manufacturing, healthcare

Submission Guidelines

For author information and guidelines on submission criteria, please visit the Author Information page. Please submit papers through the ScholarOne system, and be sure to select the special-issue name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal.


Contact the guest editors at

  • Elisa Bertino, Purdue University
  • Suparna Bhattacharya, Hewlett Packard Labs
  • Elena Ferrari, University of Insubria
  • Dejan Milojicic, Hewlett Packard Labs