call for research papers 2022

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PLOS ONE presents a curated collection of pioneering research in the field of Personalized Medicine. This collection demonstrates the exciting range…

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PLOS Water is inviting submissions of original research articles that address how we ensure food security with limited water resources. This includes…

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In this Call for Papers, PLOS ONE aims to highlight the broad scope of multidisciplinary research in the area of aging. We are calling for submissions…

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Cells use elaborate mechanisms to sense a variety of mechanical and biochemical cues in their environment, to integrate this information, and to…

The efficacy and safety of a drug is highly impacted not only by how it is designed, but also by how and where it is delivered. In recent years there…

Transparency in reporting and methodological rigor have received increasing interest in psychology and cognitive science. They are crucial ingredients…

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Highlight your research and enhance its visibility to your field and community by submitting to one of our Collections. Collections at HSS Comms provide a high-profile venue for topics of substantial interest to the community. Papers included in a Collection are published in the journal and featured on our Collection page.

Divisive politics, polarisation and democratic decline

Interrogating postmodernism

Philosophy [in:of:for:and] digital knowledge infrastructures

• Frodo Podschwadek, PhD.

Transdisciplinary approaches to knowledge production and problem solving to tackle grand societal challenges

Digitalisation in the post-pandemic era: sustainability, inequality and politics

• Qinglong Shao, PhD.

Replication and replicability

Technology and learning

Theorising and implementing smart healthy age-friendly environments

• Agnieszka Cieśla, PhD.
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Behavioural public policy

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The manosphere and networked misogyny

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Call for Papers: IEEE CLOUD 2022

PDF Call for Papers

IEEE CLOUD is a flagship conference focusing on innovative cloud computing across all “as a service” categories, including modeling, developing, publishing, monitoring, managing, delivering Everything-as-a-Service (XaaS) in the context of various types of cloud environments. IEEE CLOUD 2022 invites original papers addressing all aspects of cloud computing technology i.e., infrastructure, applications, management and security solved using technologies of Big Data, Artificial Intelligence, High Performance computing, Distributed computing etc..

Technical topics of interest include but are not limited to the following:

Cloud as a Service

• IaaS, PaaS, and SaaS
• Function as a Service
• Network as a Service
• Storage as a Service
• Everything as a Service

Cloud Infrastructure

• Cloud Computing System and Architectures
• Edge Computing System and Architectures
• Cloud-centric Network Architectures
• Storage and Data Architectures
• Hybrid-clouds and Multi-clouds Integration
• Cloud Computing Virtualization/Containerization

Cloud Applications

• Large Scale Cloud Applications
• Terminal-Edge-Cloud Applications
• 5G/6G Enhanced Edge/Cloud Applications
• Social and Mobile Cloud Applications
• Innovative Cloud Applications
• Microservice-based Cloud Applications
• Containerized Application Virtualisation
• Serverless Cloud Applications

Cloud Management and Operations

• Distributed and Parallel Query Processing
• Resource, Energy, Data Management
• Cloud Metering and Monitoring
• Containers, Serverless Computing
• SDN, NFV, Data Center Network
• Cloud Service Adaptation and Automation
• Cloud Federation, Service Composition
• Sustainable Cloud Computing

Cloud Security and Privacy

• Access Control, Authorization, Authentication
• Assurance, Audit, Certification, Compliance
• Fault Tolerance, High Availability, Reliability
• Cryptographic Algorithms and Protocols
• Privacy-aware data management
• Trusted Cloud Environments
• Application of Distributed Ledger Technologies to Cloud

MANUSCRIPT GUIDELINES AND SUBMISSION INFORMATION

Please download the paper template in WORD, LaTeX or Overleaf.

Language:  English Paper size and format:  US Letter; Two-column format in the IEEE style Page limit:

• Every full paper submission can include up to 10 pages for the main contents (including all text, footnotes, figures, tables and appendices) with additional pages for appropriate references.
• Up to three pages for “Work-in-Progress” paper submission (including main contents and references).
• Please note that the above page limit will be applied without exception. Papers violating the page limit will regretfully be desk rejected.

Abstract Length:  1500 characters for a regular paper, and 500 characters for “work in progress” papers Number of Keywords:  between five to eight keywords for each paper File format:  Limit the size of a single PDF file to be 6MB

Anonymous Submissions: All conferences under IEEE SERVICES implement a double-blind reviewing process. Author names and affiliations should not appear in the paper. The authors should make a reasonable effort not to reveal their identities of institutional affiliations in the text, figures, photos, links, or other data that is contained in the paper. Authors’ prior work should be preferably referred to in the third person; if this is not feasible, the references should be blinded. Submissions that violate these requirements will be rejected without review. The list of authors cannot be changed after the acceptance decision is made unless approved by the Program Chairs.

All submitted manuscripts will be peer-reviewed by at least three members of the program committee. Accepted papers with confirmed registration and committed presentation will appear in the conference proceedings published by the IEEE Computer Society Press. TCSVC will provide a cash prize of USD 400.00 to every Best Paper and Best Student Paper at IEEE SERVICES 2022. Recipients of “Best Paper”, “Best Student Paper”, and special paper awards will be presented with award certificates and cash prizes in the to-be-recorded Awards session of the conference. The authors of selected papers will be encouraged to submit extended and enhanced versions of their papers to the IEEE Transactions on Services Computing (TSC) and other suitable journals.

Submitted papers are REQUIRED to be formatted using the IEEE Proceedings template. Unformatted papers and papers beyond the page limit will not be reviewed.

PAPER SUBMISSION – EASYCHAIR

REVIEW POLICY

IEEE Policy and professional ethics require that referees treat the contents of papers under review as privileged information not to be disclosed to others before publication. It is expected that no one with access to a paper under review will make any inappropriate use of the special knowledge, which that access provides. Contents of abstracts submitted to conference program committees should be regarded as privileged as well, and handled in the same manner. The Conference Publications Chair shall ensure that referees adhere to this practice.

Organizers of IEEE conferences are expected to provide an appropriate forum for the oral presentation and discussion of all accepted papers. An author, in offering a paper for presentation at an IEEE conference, or accepting an invitation to present a paper, is expected to be present at the meeting to deliver the paper. In the event that circumstances unknown at the time of submission of a paper preclude its presentation by an author, the program chair should be informed on time, and appropriate substitute arrangements should be made. In some cases, it may help reduce no-shows for the Conference to require advance registration together with the submission of the final manuscript.

ABOUT THE TECHNICAL COMMITTEE ON SERVICES COMPUTING

Founded in 2003, IEEE Computer Society’s Technical Committee on Services Computing (TCSVC) is a multidisciplinary group whose purpose is to advance and coordinate work in the field of Services Computing carried out throughout the IEEE in scientific, engineering, standard, literary and educational areas. IEEE TCSVC membership details are available at  http://tab.computer.org/tcsvc/

CONTACT INFORMATION

Email CFP inquiries to: [email protected]

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42nd IEEE International Conference on Distributed Computing Systems

Call for Research Papers

The annual IEEE ICDCS conference is a premier international forum for researchers, developers and users to present, discuss and exchange the cutting edge ideas and latest findings on topics related to any aspect of distributed computing systems.

We invite you to submit your original contributions to ICDCS 2022 ( https://icdcs2022.icdcs.org/ ).

Topics of interest include, but are not limited to:

• Cloud Computing and Data Centers
• Distributed Algorithms and Theory
• Distributed Big Data Systems and Analytics
• Distributed Fault Tolerance and Dependability
• Distributed Operating Systems and Middleware
• Edge Computing
• Internet of Things and Cyber-Physical Systems
• Mobile and Wireless Computing
• Security, Privacy, and Trust in Distributed Systems
• Machine Learning on or for Distributed Systems: Applications of machine learning to enhancing and optimizing systems, or using systems techniques to scale and improve machine learning applications.
• Insights from Industrial Experience: Case studies, data analysis, and empirical evaluation of distributed systems deployed in real-world production settings.

Paper Submission

Papers must be original and unpublished, and must not be submitted for publication elsewhere concurrently. All paper submissions should follow  the IEEE 8.5″ x 11″ Two-Column Format . Each submission can have up to 11 pages (including references). Papers exceeding this page limit or with smaller fonts will be rejected without review. The submitted manuscripts should include author names and affiliations.

Electronic submission site： https://easychair.org/conferences/?conf=icdcs2022

If the submission is accepted for publication, up to 2 over length pages may be purchased for the final camera-ready version. Each accepted paper must have at least one author registered and be presented during the conference. No-show paper will be reported to the publisher and deleted from the conference publication. For authors with multiple papers accepted by the conference, a separate author registration is required for each paper.

Important Dates

• IEEE Xplore Digital Library
• IEEE Standards
• IEEE Spectrum Online
• More IEEE Sites

Call for Papers [Main Conference]

Call For Papers [Main Conference]:  PDF Version Is Available  Here .

IEEE INFOCOM 2022 solicits research papers describing significant and innovative research contributions to the field of computer and data communications networks. We invite submissions on a wide range of research topics, spanning both theoretical and systems research. Topics include but are not limited to:

5G and beyond networks Age of Information Big data and machine learning for networks Cellular networks Cloud computing/mobile cloud computing Challenged Environments (underwater, underground) Connected unmanned aerial/terrestrial/underwater systems Cross-layer optimization and control Crowdsourcing CubeSats Cyber-physical systems Datacenter networking Dynamic spectrum sharing Energy efficiency in networks Edge and fog computing/networking Fault tolerance, reliability and survivability Information security and privacy Information-centric networking Interference management and mitigation Internet architecture Internet of Things Localization and location-based services Medium access control MIMO-based networking mmWave, THz, VLC, full duplex communication networks Mobile sensing and applications Mobility management and models Multimedia networking Network economics and pricing Network management Network measurement and analysis Network security and privacy Network virtualization Optical networks Overlay and peer-to-peer networks Quality-of-service and resource management Quantum networking Router and switch design Routing and multicast Scaling laws and fundamental limits Smart grid applications Social computing and networks Software-defined networking Studies on testbeds and large-scale experimental platforms Vehicular networks Web applications and content distribution WLAN, WPAN, RFID, and NFC

IEEE INFOCOM incorporates a rigorous double-blind review process, empowered by a fully automated review assignment system that analyzes the submitted manuscripts and the representative publications of TPC members, and matches the submissions to TPC members’ expertise and interests. The automated review assignment system, termed Erie, is described in the following paper. 

B. Li and Y.T. Hou. “The new automated INFOCOM review assignment system,” IEEE Network, vol.30, no.5, pp.18-24, Sept./Oct. 2016.

http://ieeexplore.ieee.org/document/7579022/

Preprints Policy

The submitted manuscript or its title/abstract should not be posted on a public website, such as arXiv.org, or transmitted via public mailing lists. Authors will need to provide consent that their submissions may be subject to an early rejection if it is found to have more than 30% overlap with a single paper available to the public over the Internet (e.g., arXiv, webpages, etc.).

Anonymous Extended Report Policy

Note that the submitted papers are not allowed to refer to an extended/technical report, even if it is anonymous. Please include what you deem to be the most important technical content within the page limitations of the submission.

Conflict of Interests (COI)

A COI occurs when a person’s objective judgment is — or is perceived by a reasonable observer to be — compromised by an existing relationship, affiliation, or connection to a person whose work they must evaluate.

The following are considered to be specific exemplars of relationships that produce COIs. Individuals in such relationships should not be involved in peer review of, or making editorial decisions about, materials provided by the related parties.

• Notable personal or professional rivalry/animosity (publicly known or not)
• The lifelong relationship between Ph.D. student and Ph.D. supervisor
• Personal or family relationships that would reasonably cause others to doubt impartiality
• Working closely together (e.g., at the same institution, company or organization; or within the same organizational team)
• Recipients of joint funding or significant professional collaboration
• Joint authorship of an archival publication

Accepted and presented papers will be published in the IEEE INFOCOM 2022 Conference Proceedings and submitted to IEEE Xplore®. Full details of submission procedures and requirements for authors of accepted papers are available at http://infocom2022.ieee-infocom.org .

Important Dates:

Abstract Due: Saturday, July 24, 2021 (11:59pm EDT) Full Paper Due: Saturday, July 31, 2021 (11:59pm EDT) Notification of Acceptance: Friday, December 3, 2021

Technical Program Chairs

Yingying (Jennifer) Chen (Rutgers University, USA)

Atilla Eryilmaz (Ohio State University, USA)

Joerg Widmer (IMDEA Networks, Spain)

Technical Program Vice-Chair for Information Systems

Yan Wang (Temple University)

Student Conference Grant Sponsors

• Message from the Chairs
• Organizing Committee
• Research Program Committee
• Demonstration Track Committee
• Industry Track Committee
• Sponsorship Opportunities
• Program Schedule
• Research Paper Track
• Tutorial Track
• PhD Symposium Track
• Industry Track
• TKDE Poster Track
• Student and Dnl Events
• Keynote Session
• PhD Symposium Program
• Workshop Schedules
• Best Papers Award

Important Dates

• Review Process
• Research Papers Track
• Demonstration Track
• Tutorials Track
• Industry and Applications Track
• HardBD & Active ’22
• Call for Research Papers

IEEE ICDE 2022 Call for Research Papers

The 38th IEEE International Conference on Data Engineering (ICDE 2022) will be hosted in Kuala Lumpur, Malaysia during the week of May 9-12, 2022.

Highlights for ICDE 2022

Topics of interest, notes on research papers, reviewing process, inclusion and diversity in writing, conflict of interest.

ICDE 2022 will include a Review Quality phase where all reviews will go through an improvement process focusing on constructive feedback.

Clear accepts and Rejects will be notified early, midway through the review process.

Authors will be invited to provide author feedback both in terms of technical remarks in the reviews and with respect to the quality of the reviews.

Paper format will change to 12 pages + unlimited space for references.

We invite the submission of original research contributions in the following areas:

Benchmarking, Performance Modelling, and Tuning

Crowdsourcing

Data Mining and Knowledge Discovery

Data Models, Semantics, Query languages

Data Stream Systems and Sensor Networks

Data Visualization and Interactive Data Exploration

Database Security, Privacy, and Trust

Database Technology for Machine Learning

Distributed, Parallel and P2P Data Management

Graphs, Networks, and Semi-Structured Data

Information Integration and Data Quality (Data Provenance, Cleaning, Curation; Data Integration, Metadata Management, and Interoperability)

Machine Learning for Database Systems

Modern Hardware and In-Memory Database Systems

Query Processing, Indexing, and Optimization

Spatial Databases and Temporal Databases

Text, Semi-Structured Data, IR, Image, and Multimedia Databases

Uncertain, Probabilistic and Approximate Databases

Very Large Data Science Applications / Pipelines

Workflows, Scientific Data Management

We also welcome any original contributions that may cross the boundaries among areas or point in other novel directions of interest to the database research community.

IEEE ICDE 2022 will have two rounds of research paper submissions with each round involving two rounds of reviewing to allow for revisions. Notifications dates are approximate. All deadlines are 11:59PM PST.

First Round:

Submission due: July 21, 2021 (Wednesday)

Early notification phase: August 25, 2021 (Wednesday) changed to September 1, 2021 (Wednesday)

Rebuttal due: August 30, 2021 (Monday) changed to September 6, 2021 (Monday)

Notification for authors (Accept/Revise/Reject): September 22, 2021 (Wednesday) changed to September 29, 2021 (Wednesday)

Revision due: October 27, 2021 (Wednesday) changed to November 3, 2021 (Wednesday)

Notification to authors (Accept/Reject): November 10, 2021 (Wednesday) changed to November 17, 2021 (Wednesday)

Camera-ready copy due: December 2, 2021 (Thursday) changed to January 7, 2022 (Friday) January 21, 2022 (Friday)

Update on Research Paper Track

We have received 360 submissions in the first round for research papers and we are working on finalizing reviewer assignments now. Stay tune!

Second Round:

Submission due: November 17, 2021 (Wednesday) extended to November 19, 2021 ( Friday ) [Note: CMT was down before the original deadline]

Early notification phase: December 22, 2021 (Wednesday) extended to January 14, 2022 ( Friday )

Rebuttal due: January 7, 2022 (Friday) extended to January 17, 2022 ( Monday )

Notification for Authors (Accept/Revise/Reject): January 26, 2022 (Wednesday) extended to February 2, 2022 ( Wednesday )

Revision Due: March 2, 2022 (Wednesday) extended to March 9, 2022 ( Wednesday )

Notification to authors (Accept/Reject): March 16, 2022 (Wednesday) extended to March 23, 2022 ( Wednesday )

Camera-ready copy due: March 30, 2022 (Wednesday)

Manuscripts must be prepared in accordance with the IEEE format available at https://www.ieee.org/conferences_events/conferences/publishing/templates.html

Research papers must not exceed 12 pages for the main text plus an unlimited number of pages for the bibliography. No appendix is allowed. Only electronic submissions in PDF format will be considered. A paper submitted to IEEE ICDE 2022 cannot be under review for any other conference or journal during the entire time it is considered for ICDE 2022, and it must be substantially different from any previously published work. Submissions will be reviewed in a single-blind manner. All accepted papers will be presented as posters at ICDE 2022, but the PC may decide to select only a subset of the accepted papers for a “conventional” presentation slot during the conference. However, all accepted papers will be treated equally in the conference proceedings, which are the persistent, archival record of the conference. The best papers (as judged by the ICDE 2022 PC) will be selected for extended versions to be published in the IEEE Transactions on Knowledge and Data Engineering (TKDE). IEEE reserves the right to exclude a paper from distribution after the conference (e.g., removal from IEEE Xplore) if none of the authors attends the conference to present their paper. Submissions that are rejected in the first round of IEEE ICDE 2021 research track are not eligible for re-submission to the second round.

Review Quality

Once the reviews are complete, the area chairs will “review the reviews” and work with reviewers to improve the feedback to the authors as much as possible focusing on providing constructive feedback.

Early notifications

Papers that are a clear accept or reject will receive early notification.

Author Feedback

Then the authors will have a few days to read the reviews and submit an optional short rebuttal. The purpose of the rebuttal is to clarify misunderstandings and factual errors through pointers to specific parts in the submitted paper. The authors will also be invited to submit feedback on specifics metrics for the quality of the reviews (this feedback will only be visible to the area chairs and PC chairs).

Papers will be invited to submit a revised version of their paper if the PC believes the papers can reasonably improve within the available time-frame. Authors will have one and a half months to prepare their revision. The revision process is intended to be a constructive partnership between reviewers and authors. To this end, reviewers will be instructed to request revisions only in constructive scenarios with specific requests.

1) Number of reviews: All papers will receive at least three reviews. 2) Number of accepted papers: The number of accepted research papers will not be capped. We will accept all papers meeting the high quality and innovation standards of ICDE.

We value Diversity and Inclusion in our community and professions. Both are important in our writing as well. Be mindful in your writing of not using language or examples that further the marginalization, stereotyping, or erasure of any group of people, especially historically marginalized and/or under-represented groups (URGs) in computing. Also be vigilant and guard against unintentionally exclusionary examples. Reviewers will be empowered to monitor and demand changes if such issues arise. Going further, also consider actively raising the representation of URGs in your writing. Diversity of representation in writing is a simple but visible avenue to celebrate and ultimately help improve our community’s diversity.

During submission of a research paper, the submission site will request information about Conflicts of Interest (COI) of the paper’s authors with program committee (PC) members. It is the full responsibility of all authors of a paper to identify all (and only) PC members with potential COIs as per the definition provided on the submission site. Papers with incorrect or incomplete COI information as of the submission closing time are subject to immediate rejection.

Definition of Conflict of Interest

A paper author has a COI with a PC member when and only when one or more of the following conditions hold:

The PC member is a co-author of the paper.

The PC member has been a co-worker in the same company or university within the past two years.

The PC member has been a collaborator within the past two years.

The PC member is or was the author’s primary thesis advisor, no matter how long ago.

The author is or was the PC member’s primary thesis advisor, no matter how long ago.

The PC member is a relative or close personal friend of the author.

Want to contribute? Let’s Start!

We are excited to see you at ICDE 2022

Event Booking

Call for Papers (Research Papers)

The annual Joint Conference on Digital Libraries (JCDL) is the primary international event for the inter- and multi-disciplinary community of academics and practitioners in digital libraries coming from computer, information and social sciences, and other related disciplines. JCDL encompasses the many meanings of the term digital libraries, including notions of managing, operating, developing, curating, evaluating, or utilizing collections of data/information/knowledge in various domains.

The deadline for submitting Research papers has expired !

The deadline for submitting Late-breaking results, Preliminary work, Datasets, and Demonstrations is March 14, 2022. See the  call for late breaking and demo papers for more details.

JCDL 2022 – Bridging Worlds

In this global pandemic that put many of us into lockdown, quarantine, and separation for a long time, we will do our best to bring together communities and people again. As digital libraries are traditionally strong in connecting the digital and the physical world, we will pick up this heritage and establish a hybrid format that is as open as possible to everyone.

Topics of interest, as they relate to digital libraries, include, but are not limited to:

Research Papers: Variable Page Length

JCDL 2022 will implement a variable paper length policy for research papers. There is no longer a distinction between long and short papers, nor a need of condensing or enlarging medium-length submissions.

The maximum paper length is 10 pages in content plus unrestricted space for references . The minimum paper length is 4 pages in content plus unrestricted space for references . Any page length in between is allowed.

Paper length should be commensurate with contribution size and authors should submit a paper whose length reflects what is needed for the content of the work. The reviewers will assess whether the contribution is appropriate for the given length. Longer papers may be given more presentation time during the conference. We hope this new streamlined process will preserve the variety of paper lengths and foster the exchange of ideas without creating an artificial distinction among them. Reviewers will be explicitly advised to judge the quality of a paper and not its length.

Submission Guidelines

All submissions must be original works, not previously published or under review for publication elsewhere, in English, in PDF format, and in the current ACM two-column conference format. Suitable LaTeX, Word, and Overleaf templates are available from the ACM Website (use “sigconf” proceedings template for LaTeX and the Interim Template for Word, https://www.acm.org/publications/proceedings-template ).

All submissions will be rigorously peer-reviewed in a double-blind reviewing process.

Submissions must be anonymous and all references to authors’ works have to be anonymised.

Submissions are to be made via Easychair:

All accepted papers will be included in the proceedings and will be presented at the conference. At least one author of each accepted paper is required to register for, and present the work at the conference at sight in Cologne. In case of travelling restrictions, authors will be enabled to present the work remotely.

Selected best papers will be invited for a special issue to be published with the International Journal on Digital Libraries (IJDL), Springer.

Dual Submission Policy

Papers submitted to JCDL 2022 should be substantially different from papers that have been previously published, or accepted for publication, or that are under review at other venues. Exceptions to this rule are:

• Submission is permitted for papers presented or to be presented at conferences or workshops without proceedings.
• Submission is permitted for papers that have previously been made available as a technical report (e.g., in institutional archives or preprint archives like arXiv). However, we discourage this since it places anonymity at risk; in particular, please do not publish your paper at arXiv and submit to JCDL at the same time, some days before, or during the reviewing period of JCDL.

If your paper already is available as a technical report:

• You might not want to use the exact same title and abstract for your JCDL submission (in case of acceptance at JCDL, the title of your submission still might be changed “back”).
• Please do not cite your technical report and make some effort to avoid any issues that may harm the double-blindness of your submission. Reviewers will receive guidance that ask them to refrain from trying to break blindness if at all possible too, but be aware that the availability of an available technical report for an JCDL submission can cause issues.

Submission Deadlines

All dates are Anywhere on Earth (AoE) time zone

• 10 January 2022   23 January (extended) – Research paper submissions
• 14 March 2022 – Notification of acceptance for research papers
• 18 April 2022 – Final camera-ready deadline for all submission
• 30 April 2022 – Final camera-ready deadline (extended) for all submission
• 20 – 24 June 2022 – JCDL Conference in Cologne, Germany

Program Chairs

• Annika Hinze, University of Waikato, New Zealand
• Philipp Mayr, GESIS – Leibniz Institute for the Social Sciences, Germany
• Philipp Schaer, TH Köln (University of Applied Sciences), Germany

For any questions about paper submissions you may contact the Program Chairs by email to [email protected].

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• Symposium Issue – Application of Blockchain Technology in PFM – deadline for abstracts April 30, 2024
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Journal of Interactive Marketing

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Cleft Palate Craniofacial Journal

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Progress in Transplantation

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ECNU Review of Education

• Understanding What Mathematics Teachers Notice in Instruction: A Cross-Cultural Dialogue Between East and West  – deadline 15-Nov-2023 for abstract, 31-Mar-2024 for submission

Asian Journal for Mathematics Education

Gifted Child Today

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• Activism, Advocacy, and Allyship  – deadline TBD
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Hispanic Health Care International

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Neurorehabilitation and Neural Repair

Chinese Journal of Transnational Law

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• Unpacking Economic Inequality: A Psychological Perspective  – Proposal deadline: Sep 9, 2024; Manuscript deadline: Jan 10, 2025

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American Behavioral Scientist

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 Call for papers 2023

We, at IJSER, initiate a call for research paper in all areas of science, engineering and technology every month . From original research papers, survey papers, case studies and academic or scholarly articles to extended versions of previously published papers in conferences, scholarly journal or academic peer reviewed international journals, we welcome high quality work that focuses on research, development and application in the aforesaid areas.

(ISSN 2229-5518)

Call for papers 2023 Paper Submission Deadline: September 30, 2023 ( Call for Papers - Volume 14, Issue 9 Edition ) Paper Online Publication : September, 2023 ( Research paper online publication finalized for (registered papers) Volume 14, Issue 9 Edition . ) Open Access Journal Publication

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Following is a long list of areas covered which is in fact much wider in scope than what you see. so, find out the details for the latest call for paper and start the online submission process (the areas are not limited to the following):.

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Director's Messages

Extended—call for papers: design and analytic methods to evaluate multilevel interventions to reduce health disparities.

Updated Aug. 25, 2022 to extend the call for papers until Sept. 30, 2022

The NIH has launched initiatives to end structural racism in biomedical research and eliminate health disparities . For example, several funding opportunities have already been released that focus on developing and testing multilevel interventions to address structural racism and other structural determinants as drivers of health disparities across the United States.

The ODP recently elevated the issue of health disparities from a cross-cutting theme for the Office to a new strategic priority . We introduced ADVANCE: Advancing Prevention Research for Health Equity , a new trans-NIH effort to encourage new prevention interventions and strategies that deliver existing evidence-based interventions and preventive services in populations that experience health disparities. We expect ADVANCE will lead to additional funding opportunities over the next several years.

Open Call for Submissions—Extended to Sept. 30, 2022

The ODP is also working hard to provide investigators with the opportunities and information they need to perform high-quality health equity research. I am proud to announce a call for abstracts for a supplemental issue of the journal Prevention Science , the official publication of the Society for Prevention Research, which will be sponsored by the ODP. The forthcoming issue will be entitled “Design and Analytic Methods to Evaluate Multilevel Interventions to Reduce Health Disparities.”

We invite you to review the detailed Submission & Review Process ,  Manuscript Details , and Frequently Asked Questions  below and submit a two-page manuscript precis to [email protected] . The deadline for submitting a manuscript precis has been extended to Sept. 30, 2022 .

Aims of the Supplemental Issue

Effectively addressing structural racism and other structural determinants to improve health equity requires rigorously tested and evidence-based multilevel interventions. However, studies that evaluate multilevel interventions face specific challenges, which require specialized design and analytical approaches.

Investigators could benefit from guidance on the appropriate design and analytic methods for evaluating these multilevel interventions, but such guidance is currently incomplete and scattered across a wide range of sources and across disciplines that do not often interact.

This supplemental issue will bring together current thinking and new ideas about design and analytic methods that would be appropriate for studies aimed at reducing health disparities, including strategies for balancing methodological rigor with design feasibility, acceptability, and ethical considerations. Of particular interest are design and analytic methods for parallel group- or cluster-randomized trials (GRTs), stepped-wedge GRTs, group-level regression discontinuity trials, and other methods that are appropriate for evaluation of multilevel interventions.

We anticipate the supplemental issue will be published in April 2024. 

Submission & Review Process

Please also refer to the Frequently Asked Questions at the bottom of this page for additional information, which will be updated regularly.

• NOW Sept. 30, 2022 : Deadline for investigators to submit a two-page manuscript precis to [email protected] . The precis should outline the proposed design, analytic, and sample size methods, together with any new research you propose to evaluate those methods.
• Nov. 1, 2022 : Guest editors invite selected authors to submit a full manuscript.
• March 1, 2023 : Deadline for authors to submit initial manuscript drafts to the guest editors (see Manuscript Details below). Guest editors will review drafts for length, APA formatting, and reference style, as well as informally for content and fit with the theme of the supplemental issue. Authors will have time to incorporate feedback prior to formal submission to the journal for peer review.
• May 1, 2023 : Deadline for authors to submit full manuscripts to Prevention Science for peer review through the journal’s online portal . Guest editors assign reviewers and make recommendations to the journal editor, who makes the final decision regarding disposition of the manuscript.

Manuscript Details

Manuscripts should be limited to 30 double-spaced pages and will need to:

• Provide an example multilevel intervention that could be proposed to address structural racism or reduce health disparities.
• Propose a design, analytic plan, and sample size estimation method to evaluate that intervention.
• Present the methods and results of new research used to evaluate the proposed design, analytic plan, and sample size estimation method (where appropriate).
• Discuss the strengths and weaknesses of the proposed approach relative to existing methods.

Additional material can be proposed as Supplemental Information to be published online. Instructions to authors for manuscript submissions are available on the Prevention Science website.

Guest Editors

• David M. Murray, Ph.D. (ODP)
• Patrick Heagerty, Ph.D. (Department of Biostatistics, University of Washington)
• Melody S. Goodman, Ph.D. (Department of Biostatistics, New York University)

Additional Information

Send questions and manuscript precis submissions to Dr. David Murray at [email protected] .  

Frequently Asked Questions

(updated regularly)

1. What are the formatting requirements for the two-page manuscript precis?

• Font size: At least 11 points
• Font style: Arial, Georgia, Helvetica, or Palatino Linotype
• Line spacing: Single spaced
• Margins: 1 inch

2. Do references and figures count toward the two-page limit of the manuscript precis, or can I include them as a separate document?

Both references and figures count toward the two-page limit for the manuscript precis and should not be submitted as a separate document or attachment.

3. Can I submit a manuscript about a proposed study, or does the study need to be active or completed?

Manuscripts should provide an example multilevel intervention that could be proposed to address structural racism and reduce health disparities. This includes a study that has not been conducted but could be in the future.

4. Does the final manuscript submission need to present results of an active multilevel study?

Manuscripts do not need to present results from the study described in their manuscript, but they must provide the other information identified under Manuscript Details :

• Provide an example multilevel intervention that could be proposed to address structural racism and reduce health disparities.
• Note : We recognize that authors may propose a new method for design, analysis, or sample size. If this is the case, authors should provide results from simulation or other studies to demonstrate the validity of their proposed new methods.
• Discuss the strengths and weaknesses of the proposed approach relative to existing methods.  

5. Are the guest editors interested in experimental designs (i.e., randomized trials) only, or can I submit non-experimental designs or natural experiments (e.g., policy changes or community interventions that are not randomized trials)?

Non-randomized designs will be considered, as long as the submission addresses all the requirements stated in the call for papers:

• The two-page manuscript precis (due Sept. 1, 2022) should outline the proposed design, analytic, and sample size methods, together with any new, proposed research to evaluate those methods.
• Each manuscript should provide an example multilevel intervention that could be proposed to address structural racism or other structural determinants and reduce health disparities.
• Each manuscript should discuss the strengths and weaknesses of the proposed approach relative to existing methods.
• Manuscripts that do not address design, analysis, and sample size issues for a multilevel intervention that could be proposed to address structural racism or other structural determinants and reduce health disparities will not be considered responsive.

6. Does the proposed multilevel intervention need to both address structural racism and reduce health disparities?

No. Proposed multilevel interventions are not required to address structural racism and reduce health disparities. The guest editors will consider manuscripts that propose multilevel interventions designed to address structural racism or reduce health disparities. It is acceptable if the intervention is designed to reduce health disparities but does not address structural factors. 

Open Calls for Papers, Proposals, and Applications

Calls for papers .

Wage Dynamics in the 21st Century (call closes May 15, 2024)

Economics of Artificial Intelligence: Political Economy Challenges (call closes June 1, 2024)

Megafirms and the Economy   (call closes June 15, 2024)

Economics of Mobility (call closes July 18, 2024)

Competition in the US Agricultural Sector (call closes September 3, 2024)

Economics of Talent (call closes September 11, 2024)

Digital Platforms: Competition and Regulation (call closes September 12, 2024) 

Energy Markets, Decarbonization, and Trade (call closes October 16, 2024 )

Calls for Proposals

Market Frictions and Financial Risks (Call closes May 21, 2024)

Call for Student Research Workshop Papers

The Student Research Workshop (SRW) provides a venue for student researchers to present their work in computational linguistics and natural language processing. Students receive feedback from the general conference audience as well as from mentors specifically assigned according to the topic of their work.

The workshop’s goal is to aid students at multiple stages of their education, including undergraduate, MSc/MA, junior and senior PhD students, in getting familiar with conducting and presenting their research.

General Invitation for Submission

We invite papers in two different categories:

Thesis Proposals : This category is appropriate for advanced students who have decided on a thesis topic and wish to get feedback on their proposal and broader ideas for their continuing work.

Research Papers : Papers in this category can describe completed work, or work in progress with preliminary results. For these papers, the first author must be a current student. Topics of interest for the SRW are the same as the NAACL 2022 main conference .

Benefits of Participating

All accepted papers will be presented in the main conference poster session, giving students an opportunity to interact with and present their work to a large and diverse audience, including top researchers in the field.

All accepted thesis proposals will be presented during a session at the main conference , giving students an opportunity to receive feedback from assigned mentors and other researchers.

Submissions (in both categories) may either be archival or non-archival , based on the wishes of the authors. All archival papers will be published in the NAACL 2022 SRW Proceedings. All non-archival papers may be submitted to any venue in the future except another SRW.

Each participant is also assigned a mentor - an experienced researcher - who can provide valuable advice on the submission during the pre-submission period and mentoring during the conference.

Pre-Submission Mentorship Program

The SRW offers students the opportunity to get advance feedback before submitting their work for review. The goal of the pre-submission mentorship program is to improve the quality of writing and presentation of the student’s work, not to critique it. Participation is optional but encouraged. We especially encourage participation from undergraduates, Masters students, and others who are new to research. The pre-submission mentorship is not anonymous.

Students wishing to participate must submit their paper by Feb 1 2022 by filling out the following form . Note that even though the mentoring is not done anonymously, the paper needs to be anonymized and follow the formatting requirements.

Participants will receive a mentor who will review and provide feedback to the student within five weeks. This mentor will not be the same person who will review the final submission. The feedback will be in the format of guidance and suggestions to improve the overall writing and communication of the paper; students are not required to make the changes suggested by the pre-submission mentor.

Important Dates

Pre-submission mentoring deadline: February 1, 2022

Paper submission deadline: Mar 25, 2022

Reviews due: April 29, 2022

Notification of acceptance: May 8, 2022

Camera-ready version of papers due: May 20, 2022

NAACL 2022 conference dates: July 10–15, 2022

Note: All deadlines are 11:59PM UTC-12:00 (“anywhere on Earth”).

Submission Requirements

Submissions should follow the NAACL-HLT 2022 style guidelines, which will be posted on the conference website. All papers consist of up to five (5) pages of content, plus unlimited references. References do not count against these limits. Supplementary materials are not allowed. Upon acceptance, papers will be given six (6) content pages in the proceedings. Authors are encouraged to use this additional page to address reviewer’s comments in their final versions.

We strongly recommend the use of the official ARR style templates. The paper templates are available as an Overleaf template and can also be downloaded directly ( LaTeX and Word ). All submissions must be in PDF format. Submissions that do not adhere to the above author guidelines or ACL policies will be rejected without review. Please follow the formatting documentation general to ACL conferences available here . The templates themselves contain only specific notes (e.g., LaTeX notes in the .tex file).

Submission is electronic, using the OpenReview conference management. The submission link will be available at https://naacl2022-srw.github.io .

Travel and Grants

For students wishing to attend NAACL in person, we expect to have grants to offset some portion of the students’ conference registration, travel, and accommodation expenses. Further details will be posted here when available.

Website and Contact Information

For more information, please visit https://naacl2022-srw.github.io/ and follow us on Twitter @naacl_srw . To contact the organizers of the workshop, please email us at [email protected] .

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CALL FOR PAPERS 2022 FOR THE 9TH COMESA ANNUAL RESEARCH FORUM

Trade and competitiveness are integral to spur growth, productivity and job creation. Trade success is fundamental for a country’s economic competitiveness, and competitiveness in turn boosts the success of firms and economies in global trade, in particular to integrate into  Global Value Chains (GVCs). The competitiveness of economies in an integrated world determines how well they convert the potential created by access to global markets into opportunities for their firms, farms and people (World Economic Forum, 2015).

Competitiveness can be defined as the set of factors, policies, institutions, strategies and processes that determine the level of sustainable productivity of an economy, be it the world, a continent (or macro region), nation, region or even a city (World Economic Forum, 2014). Competitiveness centres on productivity which is the efficiency with which an economy uses available inputs to produce outputs. It determines the rate of return on investments, which fundamentally drives economic growth (World Economic Forum, 2015).

The International Trade Centre (ITC) defines competitiveness as the demonstrated ability to design, produce and commercialize an offer that fully, uniquely, and continuously fulfils the needs of targeted market segments, while connecting with and drawing resources from the business environment, and achieving a sustainable return on the resources employed. Several factors at the firm, business ecosystem and national levels influence the capacity of a company to be competitive.

According to ITC’s competitiveness framework, there are three pillars of competitiveness; compete, connect and change. Capacity to compete focuses on factors for a firm to deliver output of appropriate quantity, quality and cost. Capacity to connect describes a company’s ability to exploit information to underpin strategy and operations. Capacity to change refers to factors that support a firm’s capacity to make changes in response to, or in anticipation of, dynamic market forces.

The World Bank’s Global Competitiveness Index 4.0 (GCI 4.0) measures factors and attributes that drive productivity, growth and human development in the era of the Fourth Industrial Revolution. It includes 12 pillars of competitiveness: Institutions; Infrastructure; ICT adoption; Macroeconomic stability; Health; Skills; Product market; Labour market; Financial system; Market size; Business dynamism; and Innovation capability (World Economic Forum, 2019) The pillars are organized in three sub-indexes; basic requirements, efficiency enhancers and innovation and sophistication factors.

The competitiveness index score is measured on a 0-100 scale, where 100 represents the ‘frontier’,  an ideal state where an issue ceases to be a constraint to productivity growth. The average GCI score across the 141 economies studied in 2019 was  60.7,  with a deficit of 40 points implying that on average, most economies continue to be far from the competitiveness “frontier” (World Economic Forum, 2019).

COMESA’s average GCI score was 49.0 in 2019. Six Member States were ranked among the top 100. These are Mauritius with a score of 64.3 and ranked 52, followed by Seychelles (score 59.6, ranked 76), Tunisia (score 56.4, ranked 87), Egypt (Score 54.5, ranked 93), Kenya (score 54.1. ranked 95) and Rwanda (score 52.8, ranked 100).

Resilience is the capacity to withstand disruption. Firms display the ability to absorb shocks with situation-specific responses, based on how robust, related and responsive they are. ­Robust firms have strong management and operational procedures to withstand pressure during a crisis.­ Related firms leverage internal and external connections to access resources and support during a crisis. Responsive firms overcome crises with inventive, well-adapted strategies to absorb shock, transform and cope with the new reality. Resilient firms emerge from a crisis as strong, or stronger, than before (International Trade Center, 2021). According to ITC, a firm’s resilience is likely to be closely linked to its competitiveness.

According to a recent study by Secretariat, COMESA’s export potential stood at US$ 100.1 billion in 2019. However, the potential remains unutilized mainly due to weak productive capacity in information and communication technology, transport, structural change, energy, institutions and human capital; high freight and transport costs mainly due to inadequate export cargo to ensure sufficient return cargo for the vessels; high banking charges; lack of information on production capacities and available goods in the region;  problems in payment settlements;  slow implementation of COMESA FTA agreement; and non-tariff barriers.

COMESA global exports declined by 26.9 percent from US$123.4 billion in 2019 to US$90.3 billion in 2020. Global imports reduced by 28.7 percent from US$223.1 billion in 2019 to US$ 159.1 billion in 2020. The decrease in global trade may be attributed to the effects of covid-19 such as restrictions of international travel, closure of borders and disruptions in global and regional values chains. Intra-COMESA trade was not an exception, exports declined by 11 percent from US$10.9 in 2019 to US$9.7 billion in 2020. This was mainly due to Covid-19 restrictions imposed by governments such as restrictions on movement of people, border closures and shutdowns which affected cross border trade. The following export sectors contributed to the decline; fuels (63%), agricultural raw materials (47%), food (10%) and manufactures (6%). Most Member States recorded decrease in intra-COMESA exports except Burundi, Djibouti, Congo DR, Kenya, Uganda, Zambia and Zimbabwe.

Objective of the call for papers

The objective of this call is to seek empirical and/or policy-oriented research papers to address issues pertinent to regional integration agenda in the context of Enhancing business competitiveness and resilience to boost intra-COMESA trade. Selected papers will be presented at the 9 th COMESA Annual Research Forum to be held in September 2022.

Click on the link below for more details.

Download “CALL FOR PAPERS 2022 FOR THE 9TH COMESA ANNUAL RESEARCH FORUM”

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Process Mining Conference 2022

4th International Conference on Process Mining, October 23-28, 2022

Research Papers

Call for research papers.

The International Conference on Process Mining (ICPM) is the premium forum for researchers, practitioners and developers in process mining. The objective is to explore and exchange knowledge in this field through scientific talks, industry discussions, contests, technical tutorials and panels. The conference covers all aspects of process mining research and practice, including theory, algorithmic challenges, applications and connections with other fields.

The conference is technically co-sponsored by the IEEE Computational Intelligence Society and supported by the IEEE Task Force on Process Mining. (TBC)

Process mining is an innovative research field that focuses on extracting business process insights from transactional data commonly recorded by IT systems, with the ultimate goal of analyzing and improving organizational productivity along performance dimensions such as efficiency, quality, compliance, and risk. By relying on data rather than perceptions gained from interviews and workshops, process mining shifts the way of thinking from “confidence-based” to “evidence-based” business process management. Thus, process mining distinguishes itself within the information systems domain by its fundamental focus on understanding, analyzing, and improving business processes based on process data.

Current process mining challenges include scalability, i.e., dealing with volume, velocity, veracity and variability of input data, especially in real-time/online settings using event streams; approximation, i.e., balancing computation time with accuracy; understandability and explainability, i.e., providing easy-to-understand and explainable analytics; multi-perspective analysis, i.e., considering data, resources and time beyond the process control flow; measurability, e.g., providing a comprehensive framework for measuring differences between observed and modelled process behavior, and ethical and confidential aspects of process mining, i.e., how to ensure that process mining procedures and results do not violate ethical and privacy principles.

Topics for Research Papers

ICPM 2022 encourages papers on new methodologies, techniques and applications for process mining, as well as case studies coming from industrial scenarios. Also, papers describing novel tools, fundamental research and empirical studies on process mining are expected. For the sake of replicability of the presented studies, the addition of supplementary resources is strongly encouraged, such as used datasets, publicly accessible implementations of new techniques, and experimental packages for empirical studies. The use of novel, previously unpublished datasets is most welcome. Research on existing datasets must clearly showcase the novelty or unprecedented results of the applied analysis.

Selected, accepted research papers will be considered for publication in an extended and revised form in a special issue of Information Systems, edited by Elsevier.

The thematic areas in which contributions are sought include, but are not limited to, those listed below.

Process mining techniques

• Automated Discovery of Process Models
• Conformance/compliance Analysis
• Construction of Event Logs
• Event Log Quality Improvement
• Decision Mining for Processes
• Rule/constraint-based Process Mining
• Mining from non-process-aware systems / event streams
• Multi-perspective Process Mining
• Simulation/optimization for Process Mining
• Predictive Process Analytics
• Prescriptive Process Analytics and Recommender Systems
• Responsible Process Mining
• Privacy-preserving Process Mining
• Process Model Repair
• Process Performance Mining
• Variants/deviance Analysis and Root-cause Analysis
• Visual Process Analytics
• Process Monitoring

Process mining fundamental research

• Formal Foundations of Process Mining
• Comparative and Benchmark Studies on Process Mining
• Conceptual Models Related to Process Mining
• Human-centered Studies on Process Mining
• Process Mining Quality Measures
• Process Mining Guidelines

Process mining applications and case studies in

• Artificial Intelligence
• Blockchain Technologies
• Robotic Process Automation (RPA)
• Business Activity Monitoring and Business Intelligence
• (Cyber) Security and Privacy
• Operations Management and Lean Six Sigma
• Process Performance Measurement
• Process Reengineering
• Resource Management
• Risk Management
• Sensors, Internet-of-Things (IoT) and Wearable Devices
• Specific domains (such as accounting, finance, government, healthcare, manufacturing)

Submission Instructions

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Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research

• James Shaw 1 , 13 ,
• Joseph Ali 2 , 3 ,
• Caesar A. Atuire 4 , 5 ,
• Phaik Yeong Cheah 6 ,
• Armando Guio Español 7 ,
• Judy Wawira Gichoya 8 ,
• Adrienne Hunt 9 ,
• Daudi Jjingo 10 ,
• Katherine Littler 9 ,
• Daniela Paolotti 11 &
• Effy Vayena 12  

BMC Medical Ethics volume  25 , Article number:  46 ( 2024 ) Cite this article

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The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, research ethics committee members and other actors to engage with challenges and opportunities specifically related to research ethics. In 2022 the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations, 16 governance presentations, and a series of small group and large group discussions. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. In this paper, we highlight central insights arising from GFBR 2022.

We describe the significance of four thematic insights arising from the forum: (1) Appropriateness of building AI, (2) Transferability of AI systems, (3) Accountability for AI decision-making and outcomes, and (4) Individual consent. We then describe eight recommendations for governance leaders to enhance the ethical governance of AI in global health research, addressing issues such as AI impact assessments, environmental values, and fair partnerships.

Conclusions

The 2022 Global Forum on Bioethics in Research illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

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Introduction

The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice [ 1 , 2 , 3 ]. Beyond the growing number of AI applications being implemented in health care, capabilities of AI models such as Large Language Models (LLMs) expand the potential reach and significance of AI technologies across health-related fields [ 4 , 5 ]. Discussion about effective, ethical governance of AI technologies has spanned a range of governance approaches, including government regulation, organizational decision-making, professional self-regulation, and research ethics review [ 6 , 7 , 8 ]. In this paper, we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health research, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022. Although applications of AI for research, health care, and public health are diverse and advancing rapidly, the insights generated at the forum remain highly relevant from a global health perspective. After summarizing important context for work in this domain, we highlight categories of ethical issues emphasized at the forum for attention from a research ethics perspective internationally. We then outline strategies proposed for research, innovation, and governance to support more ethical AI for global health.

In this paper, we adopt the definition of AI systems provided by the Organization for Economic Cooperation and Development (OECD) as our starting point. Their definition states that an AI system is “a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. AI systems are designed to operate with varying levels of autonomy” [ 9 ]. The conceptualization of an algorithm as helping to constitute an AI system, along with hardware, other elements of software, and a particular context of use, illustrates the wide variety of ways in which AI can be applied. We have found it useful to differentiate applications of AI in research as those classified as “AI systems for discovery” and “AI systems for intervention”. An AI system for discovery is one that is intended to generate new knowledge, for example in drug discovery or public health research in which researchers are seeking potential targets for intervention, innovation, or further research. An AI system for intervention is one that directly contributes to enacting an intervention in a particular context, for example informing decision-making at the point of care or assisting with accuracy in a surgical procedure.

The mandate of the GFBR is to take a broad view of what constitutes research and its regulation in global health, with special attention to bioethics in Low- and Middle- Income Countries. AI as a group of technologies demands such a broad view. AI development for health occurs in a variety of environments, including universities and academic health sciences centers where research ethics review remains an important element of the governance of science and innovation internationally [ 10 , 11 ]. In these settings, research ethics committees (RECs; also known by different names such as Institutional Review Boards or IRBs) make decisions about the ethical appropriateness of projects proposed by researchers and other institutional members, ultimately determining whether a given project is allowed to proceed on ethical grounds [ 12 ].

However, research involving AI for health also takes place in large corporations and smaller scale start-ups, which in some jurisdictions fall outside the scope of research ethics regulation. In the domain of AI, the question of what constitutes research also becomes blurred. For example, is the development of an algorithm itself considered a part of the research process? Or only when that algorithm is tested under the formal constraints of a systematic research methodology? In this paper we take an inclusive view, in which AI development is included in the definition of research activity and within scope for our inquiry, regardless of the setting in which it takes place. This broad perspective characterizes the approach to “research ethics” we take in this paper, extending beyond the work of RECs to include the ethical analysis of the wide range of activities that constitute research as the generation of new knowledge and intervention in the world.

Ethical governance of AI in global health

The ethical governance of AI for global health has been widely discussed in recent years. The World Health Organization (WHO) released its guidelines on ethics and governance of AI for health in 2021, endorsing a set of six ethical principles and exploring the relevance of those principles through a variety of use cases. The WHO guidelines also provided an overview of AI governance, defining governance as covering “a range of steering and rule-making functions of governments and other decision-makers, including international health agencies, for the achievement of national health policy objectives conducive to universal health coverage.” (p. 81) The report usefully provided a series of recommendations related to governance of seven domains pertaining to AI for health: data, benefit sharing, the private sector, the public sector, regulation, policy observatories/model legislation, and global governance. The report acknowledges that much work is yet to be done to advance international cooperation on AI governance, especially related to prioritizing voices from Low- and Middle-Income Countries (LMICs) in global dialogue.

One important point emphasized in the WHO report that reinforces the broader literature on global governance of AI is the distribution of responsibility across a wide range of actors in the AI ecosystem. This is especially important to highlight when focused on research for global health, which is specifically about work that transcends national borders. Alami et al. (2020) discussed the unique risks raised by AI research in global health, ranging from the unavailability of data in many LMICs required to train locally relevant AI models to the capacity of health systems to absorb new AI technologies that demand the use of resources from elsewhere in the system. These observations illustrate the need to identify the unique issues posed by AI research for global health specifically, and the strategies that can be employed by all those implicated in AI governance to promote ethically responsible use of AI in global health research.

RECs and the regulation of research involving AI

RECs represent an important element of the governance of AI for global health research, and thus warrant further commentary as background to our paper. Despite the importance of RECs, foundational questions have been raised about their capabilities to accurately understand and address ethical issues raised by studies involving AI. Rahimzadeh et al. (2023) outlined how RECs in the United States are under-prepared to align with recent federal policy requiring that RECs review data sharing and management plans with attention to the unique ethical issues raised in AI research for health [ 13 ]. Similar research in South Africa identified variability in understanding of existing regulations and ethical issues associated with health-related big data sharing and management among research ethics committee members [ 14 , 15 ]. The effort to address harms accruing to groups or communities as opposed to individuals whose data are included in AI research has also been identified as a unique challenge for RECs [ 16 , 17 ]. Doerr and Meeder (2022) suggested that current regulatory frameworks for research ethics might actually prevent RECs from adequately addressing such issues, as they are deemed out of scope of REC review [ 16 ]. Furthermore, research in the United Kingdom and Canada has suggested that researchers using AI methods for health tend to distinguish between ethical issues and social impact of their research, adopting an overly narrow view of what constitutes ethical issues in their work [ 18 ].

The challenges for RECs in adequately addressing ethical issues in AI research for health care and public health exceed a straightforward survey of ethical considerations. As Ferretti et al. (2021) contend, some capabilities of RECs adequately cover certain issues in AI-based health research, such as the common occurrence of conflicts of interest where researchers who accept funds from commercial technology providers are implicitly incentivized to produce results that align with commercial interests [ 12 ]. However, some features of REC review require reform to adequately meet ethical needs. Ferretti et al. outlined weaknesses of RECs that are longstanding and those that are novel to AI-related projects, proposing a series of directions for development that are regulatory, procedural, and complementary to REC functionality. The work required on a global scale to update the REC function in response to the demands of research involving AI is substantial.

These issues take greater urgency in the context of global health [ 19 ]. Teixeira da Silva (2022) described the global practice of “ethics dumping”, where researchers from high income countries bring ethically contentious practices to RECs in low-income countries as a strategy to gain approval and move projects forward [ 20 ]. Although not yet systematically documented in AI research for health, risk of ethics dumping in AI research is high. Evidence is already emerging of practices of “health data colonialism”, in which AI researchers and developers from large organizations in high-income countries acquire data to build algorithms in LMICs to avoid stricter regulations [ 21 ]. This specific practice is part of a larger collection of practices that characterize health data colonialism, involving the broader exploitation of data and the populations they represent primarily for commercial gain [ 21 , 22 ]. As an additional complication, AI algorithms trained on data from high-income contexts are unlikely to apply in straightforward ways to LMIC settings [ 21 , 23 ]. In the context of global health, there is widespread acknowledgement about the need to not only enhance the knowledge base of REC members about AI-based methods internationally, but to acknowledge the broader shifts required to encourage their capabilities to more fully address these and other ethical issues associated with AI research for health [ 8 ].

Although RECs are an important part of the story of the ethical governance of AI for global health research, they are not the only part. The responsibilities of supra-national entities such as the World Health Organization, national governments, organizational leaders, commercial AI technology providers, health care professionals, and other groups continue to be worked out internationally. In this context of ongoing work, examining issues that demand attention and strategies to address them remains an urgent and valuable task.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, REC members and other actors to engage with challenges and opportunities specifically related to research ethics. Each year the GFBR meeting includes a series of case studies and keynotes presented in plenary format to an audience of approximately 100 people who have applied and been competitively selected to attend, along with small-group breakout discussions to advance thinking on related issues. The specific topic of the forum changes each year, with past topics including ethical issues in research with people living with mental health conditions (2021), genome editing (2019), and biobanking/data sharing (2018). The forum is intended to remain grounded in the practical challenges of engaging in research ethics, with special interest in low resource settings from a global health perspective. A post-meeting fellowship scheme is open to all LMIC participants, providing a unique opportunity to apply for funding to further explore and address the ethical challenges that are identified during the meeting.

In 2022, the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations (both short and long form) reporting on specific initiatives related to research ethics and AI for health, and 16 governance presentations (both short and long form) reporting on actual approaches to governing AI in different country settings. A keynote presentation from Professor Effy Vayena addressed the topic of the broader context for AI ethics in a rapidly evolving field. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. The 2-day forum addressed a wide range of themes. The conference report provides a detailed overview of each of the specific topics addressed while a policy paper outlines the cross-cutting themes (both documents are available at the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ ). As opposed to providing a detailed summary in this paper, we aim to briefly highlight central issues raised, solutions proposed, and the challenges facing the research ethics community in the years to come.

In this way, our primary aim in this paper is to present a synthesis of the challenges and opportunities raised at the GFBR meeting and in the planning process, followed by our reflections as a group of authors on their significance for governance leaders in the coming years. We acknowledge that the views represented at the meeting and in our results are a partial representation of the universe of views on this topic; however, the GFBR leadership invested a great deal of resources in convening a deeply diverse and thoughtful group of researchers and practitioners working on themes of bioethics related to AI for global health including those based in LMICs. We contend that it remains rare to convene such a strong group for an extended time and believe that many of the challenges and opportunities raised demand attention for more ethical futures of AI for health. Nonetheless, our results are primarily descriptive and are thus not explicitly grounded in a normative argument. We make effort in the Discussion section to contextualize our results by describing their significance and connecting them to broader efforts to reform global health research and practice.

Uniquely important ethical issues for AI in global health research

Presentations and group dialogue over the course of the forum raised several issues for consideration, and here we describe four overarching themes for the ethical governance of AI in global health research. Brief descriptions of each issue can be found in Table  1 . Reports referred to throughout the paper are available at the GFBR website provided above.

The first overarching thematic issue relates to the appropriateness of building AI technologies in response to health-related challenges in the first place. Case study presentations referred to initiatives where AI technologies were highly appropriate, such as in ear shape biometric identification to more accurately link electronic health care records to individual patients in Zambia (Alinani Simukanga). Although important ethical issues were raised with respect to privacy, trust, and community engagement in this initiative, the AI-based solution was appropriately matched to the challenge of accurately linking electronic records to specific patient identities. In contrast, forum participants raised questions about the appropriateness of an initiative using AI to improve the quality of handwashing practices in an acute care hospital in India (Niyoshi Shah), which led to gaming the algorithm. Overall, participants acknowledged the dangers of techno-solutionism, in which AI researchers and developers treat AI technologies as the most obvious solutions to problems that in actuality demand much more complex strategies to address [ 24 ]. However, forum participants agreed that RECs in different contexts have differing degrees of power to raise issues of the appropriateness of an AI-based intervention.

The second overarching thematic issue related to whether and how AI-based systems transfer from one national health context to another. One central issue raised by a number of case study presentations related to the challenges of validating an algorithm with data collected in a local environment. For example, one case study presentation described a project that would involve the collection of personally identifiable data for sensitive group identities, such as tribe, clan, or religion, in the jurisdictions involved (South Africa, Nigeria, Tanzania, Uganda and the US; Gakii Masunga). Doing so would enable the team to ensure that those groups were adequately represented in the dataset to ensure the resulting algorithm was not biased against specific community groups when deployed in that context. However, some members of these communities might desire to be represented in the dataset, whereas others might not, illustrating the need to balance autonomy and inclusivity. It was also widely recognized that collecting these data is an immense challenge, particularly when historically oppressive practices have led to a low-trust environment for international organizations and the technologies they produce. It is important to note that in some countries such as South Africa and Rwanda, it is illegal to collect information such as race and tribal identities, re-emphasizing the importance for cultural awareness and avoiding “one size fits all” solutions.

The third overarching thematic issue is related to understanding accountabilities for both the impacts of AI technologies and governance decision-making regarding their use. Where global health research involving AI leads to longer-term harms that might fall outside the usual scope of issues considered by a REC, who is to be held accountable, and how? This question was raised as one that requires much further attention, with law being mixed internationally regarding the mechanisms available to hold researchers, innovators, and their institutions accountable over the longer term. However, it was recognized in breakout group discussion that many jurisdictions are developing strong data protection regimes related specifically to international collaboration for research involving health data. For example, Kenya’s Data Protection Act requires that any internationally funded projects have a local principal investigator who will hold accountability for how data are shared and used [ 25 ]. The issue of research partnerships with commercial entities was raised by many participants in the context of accountability, pointing toward the urgent need for clear principles related to strategies for engagement with commercial technology companies in global health research.

The fourth and final overarching thematic issue raised here is that of consent. The issue of consent was framed by the widely shared recognition that models of individual, explicit consent might not produce a supportive environment for AI innovation that relies on the secondary uses of health-related datasets to build AI algorithms. Given this recognition, approaches such as community oversight of health data uses were suggested as a potential solution. However, the details of implementing such community oversight mechanisms require much further attention, particularly given the unique perspectives on health data in different country settings in global health research. Furthermore, some uses of health data do continue to require consent. One case study of South Africa, Nigeria, Kenya, Ethiopia and Uganda suggested that when health data are shared across borders, individual consent remains necessary when data is transferred from certain countries (Nezerith Cengiz). Broader clarity is necessary to support the ethical governance of health data uses for AI in global health research.

Recommendations for ethical governance of AI in global health research

Dialogue at the forum led to a range of suggestions for promoting ethical conduct of AI research for global health, related to the various roles of actors involved in the governance of AI research broadly defined. The strategies are written for actors we refer to as “governance leaders”, those people distributed throughout the AI for global health research ecosystem who are responsible for ensuring the ethical and socially responsible conduct of global health research involving AI (including researchers themselves). These include RECs, government regulators, health care leaders, health professionals, corporate social accountability officers, and others. Enacting these strategies would bolster the ethical governance of AI for global health more generally, enabling multiple actors to fulfill their roles related to governing research and development activities carried out across multiple organizations, including universities, academic health sciences centers, start-ups, and technology corporations. Specific suggestions are summarized in Table  2 .

First, forum participants suggested that governance leaders including RECs, should remain up to date on recent advances in the regulation of AI for health. Regulation of AI for health advances rapidly and takes on different forms in jurisdictions around the world. RECs play an important role in governance, but only a partial role; it was deemed important for RECs to acknowledge how they fit within a broader governance ecosystem in order to more effectively address the issues within their scope. Not only RECs but organizational leaders responsible for procurement, researchers, and commercial actors should all commit to efforts to remain up to date about the relevant approaches to regulating AI for health care and public health in jurisdictions internationally. In this way, governance can more adequately remain up to date with advances in regulation.

Second, forum participants suggested that governance leaders should focus on ethical governance of health data as a basis for ethical global health AI research. Health data are considered the foundation of AI development, being used to train AI algorithms for various uses [ 26 ]. By focusing on ethical governance of health data generation, sharing, and use, multiple actors will help to build an ethical foundation for AI development among global health researchers.

Third, forum participants believed that governance processes should incorporate AI impact assessments where appropriate. An AI impact assessment is the process of evaluating the potential effects, both positive and negative, of implementing an AI algorithm on individuals, society, and various stakeholders, generally over time frames specified in advance of implementation [ 27 ]. Although not all types of AI research in global health would warrant an AI impact assessment, this is especially relevant for those studies aiming to implement an AI system for intervention into health care or public health. Organizations such as RECs can use AI impact assessments to boost understanding of potential harms at the outset of a research project, encouraging researchers to more deeply consider potential harms in the development of their study.

Fourth, forum participants suggested that governance decisions should incorporate the use of environmental impact assessments, or at least the incorporation of environment values when assessing the potential impact of an AI system. An environmental impact assessment involves evaluating and anticipating the potential environmental effects of a proposed project to inform ethical decision-making that supports sustainability [ 28 ]. Although a relatively new consideration in research ethics conversations [ 29 ], the environmental impact of building technologies is a crucial consideration for the public health commitment to environmental sustainability. Governance leaders can use environmental impact assessments to boost understanding of potential environmental harms linked to AI research projects in global health over both the shorter and longer terms.

Fifth, forum participants suggested that governance leaders should require stronger transparency in the development of AI algorithms in global health research. Transparency was considered essential in the design and development of AI algorithms for global health to ensure ethical and accountable decision-making throughout the process. Furthermore, whether and how researchers have considered the unique contexts into which such algorithms may be deployed can be surfaced through stronger transparency, for example in describing what primary considerations were made at the outset of the project and which stakeholders were consulted along the way. Sharing information about data provenance and methods used in AI development will also enhance the trustworthiness of the AI-based research process.

Sixth, forum participants suggested that governance leaders can encourage or require community engagement at various points throughout an AI project. It was considered that engaging patients and communities is crucial in AI algorithm development to ensure that the technology aligns with community needs and values. However, participants acknowledged that this is not a straightforward process. Effective community engagement requires lengthy commitments to meeting with and hearing from diverse communities in a given setting, and demands a particular set of skills in communication and dialogue that are not possessed by all researchers. Encouraging AI researchers to begin this process early and build long-term partnerships with community members is a promising strategy to deepen community engagement in AI research for global health. One notable recommendation was that research funders have an opportunity to incentivize and enable community engagement with funds dedicated to these activities in AI research in global health.

Seventh, forum participants suggested that governance leaders can encourage researchers to build strong, fair partnerships between institutions and individuals across country settings. In a context of longstanding imbalances in geopolitical and economic power, fair partnerships in global health demand a priori commitments to share benefits related to advances in medical technologies, knowledge, and financial gains. Although enforcement of this point might be beyond the remit of RECs, commentary will encourage researchers to consider stronger, fairer partnerships in global health in the longer term.

Eighth, it became evident that it is necessary to explore new forms of regulatory experimentation given the complexity of regulating a technology of this nature. In addition, the health sector has a series of particularities that make it especially complicated to generate rules that have not been previously tested. Several participants highlighted the desire to promote spaces for experimentation such as regulatory sandboxes or innovation hubs in health. These spaces can have several benefits for addressing issues surrounding the regulation of AI in the health sector, such as: (i) increasing the capacities and knowledge of health authorities about this technology; (ii) identifying the major problems surrounding AI regulation in the health sector; (iii) establishing possibilities for exchange and learning with other authorities; (iv) promoting innovation and entrepreneurship in AI in health; and (vi) identifying the need to regulate AI in this sector and update other existing regulations.

Ninth and finally, forum participants believed that the capabilities of governance leaders need to evolve to better incorporate expertise related to AI in ways that make sense within a given jurisdiction. With respect to RECs, for example, it might not make sense for every REC to recruit a member with expertise in AI methods. Rather, it will make more sense in some jurisdictions to consult with members of the scientific community with expertise in AI when research protocols are submitted that demand such expertise. Furthermore, RECs and other approaches to research governance in jurisdictions around the world will need to evolve in order to adopt the suggestions outlined above, developing processes that apply specifically to the ethical governance of research using AI methods in global health.

Research involving the development and implementation of AI technologies continues to grow in global health, posing important challenges for ethical governance of AI in global health research around the world. In this paper we have summarized insights from the 2022 GFBR, focused specifically on issues in research ethics related to AI for global health research. We summarized four thematic challenges for governance related to AI in global health research and nine suggestions arising from presentations and dialogue at the forum. In this brief discussion section, we present an overarching observation about power imbalances that frames efforts to evolve the role of governance in global health research, and then outline two important opportunity areas as the field develops to meet the challenges of AI in global health research.

Dialogue about power is not unfamiliar in global health, especially given recent contributions exploring what it would mean to de-colonize global health research, funding, and practice [ 30 , 31 ]. Discussions of research ethics applied to AI research in global health contexts are deeply infused with power imbalances. The existing context of global health is one in which high-income countries primarily located in the “Global North” charitably invest in projects taking place primarily in the “Global South” while recouping knowledge, financial, and reputational benefits [ 32 ]. With respect to AI development in particular, recent examples of digital colonialism frame dialogue about global partnerships, raising attention to the role of large commercial entities and global financial capitalism in global health research [ 21 , 22 ]. Furthermore, the power of governance organizations such as RECs to intervene in the process of AI research in global health varies widely around the world, depending on the authorities assigned to them by domestic research governance policies. These observations frame the challenges outlined in our paper, highlighting the difficulties associated with making meaningful change in this field.

Despite these overarching challenges of the global health research context, there are clear strategies for progress in this domain. Firstly, AI innovation is rapidly evolving, which means approaches to the governance of AI for health are rapidly evolving too. Such rapid evolution presents an important opportunity for governance leaders to clarify their vision and influence over AI innovation in global health research, boosting the expertise, structure, and functionality required to meet the demands of research involving AI. Secondly, the research ethics community has strong international ties, linked to a global scholarly community that is committed to sharing insights and best practices around the world. This global community can be leveraged to coordinate efforts to produce advances in the capabilities and authorities of governance leaders to meaningfully govern AI research for global health given the challenges summarized in our paper.

Limitations

Our paper includes two specific limitations that we address explicitly here. First, it is still early in the lifetime of the development of applications of AI for use in global health, and as such, the global community has had limited opportunity to learn from experience. For example, there were many fewer case studies, which detail experiences with the actual implementation of an AI technology, submitted to GFBR 2022 for consideration than was expected. In contrast, there were many more governance reports submitted, which detail the processes and outputs of governance processes that anticipate the development and dissemination of AI technologies. This observation represents both a success and a challenge. It is a success that so many groups are engaging in anticipatory governance of AI technologies, exploring evidence of their likely impacts and governing technologies in novel and well-designed ways. It is a challenge that there is little experience to build upon of the successful implementation of AI technologies in ways that have limited harms while promoting innovation. Further experience with AI technologies in global health will contribute to revising and enhancing the challenges and recommendations we have outlined in our paper.

Second, global trends in the politics and economics of AI technologies are evolving rapidly. Although some nations are advancing detailed policy approaches to regulating AI more generally, including for uses in health care and public health, the impacts of corporate investments in AI and political responses related to governance remain to be seen. The excitement around large language models (LLMs) and large multimodal models (LMMs) has drawn deeper attention to the challenges of regulating AI in any general sense, opening dialogue about health sector-specific regulations. The direction of this global dialogue, strongly linked to high-profile corporate actors and multi-national governance institutions, will strongly influence the development of boundaries around what is possible for the ethical governance of AI for global health. We have written this paper at a point when these developments are proceeding rapidly, and as such, we acknowledge that our recommendations will need updating as the broader field evolves.

Ultimately, coordination and collaboration between many stakeholders in the research ethics ecosystem will be necessary to strengthen the ethical governance of AI in global health research. The 2022 GFBR illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

Data availability

All data and materials analyzed to produce this paper are available on the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ .

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Acknowledgements

We would like to acknowledge the outstanding contributions of the attendees of GFBR 2022 in Cape Town, South Africa. This paper is authored by members of the GFBR 2022 Planning Committee. We would like to acknowledge additional members Tamra Lysaght, National University of Singapore, and Niresh Bhagwandin, South African Medical Research Council, for their input during the planning stages and as reviewers of the applications to attend the Forum.

This work was supported by Wellcome [222525/Z/21/Z], the US National Institutes of Health, the UK Medical Research Council (part of UK Research and Innovation), and the South African Medical Research Council through funding to the Global Forum on Bioethics in Research.

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Caesar A. Atuire

Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK

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JS led the writing, contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. CA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. PYC contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AE contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JWG contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AH contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DJ contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. KL contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DP contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. EV contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper.

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Shaw, J., Ali, J., Atuire, C.A. et al. Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research. BMC Med Ethics 25 , 46 (2024). https://doi.org/10.1186/s12910-024-01044-w

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Overdraft/NSF Revenue in 2023 down more than 50% versus pre-pandemic levels, saving consumers over $6 billion annually

Q4 2023 data suggest most banks are no longer significantly reducing fees; fees still totaled $5.8 billion in 2023

The CFPB continues to closely monitor trends in overdraft/non-sufficient funds (NSF) fee revenue and practices. With 2023 data now available, we can compare overdraft and NSF revenue last year to 2022, when many banks changed their fee policies, and to pre-pandemic levels. Our most recent analysis finds the following:

• Reported annual overdraft/NSF revenue has dropped by $6.1 billion since before the pandemic – a reduction of more than half – saving the average household who overdrafts $185 per year. 1 This reflects a nearly $2 billion annual reduction in NSF fees, and a roughly $4 billion annual reduction in overdraft fees. (This $6.1 billion drop between 2023 and 2019 is larger than the $5.5 billion decline we projected based on Q4 2022 data in our May 2023 analysis .)
• In 2023, overdraft/NSF fees were approximately $1.8 billion lower than in 2022, a 24% decrease.
• However, banks appear to have stopped significantly reducing overdraft fees, as their major policy changes have taken effect and further policy changes have slowed. Following five straight quarterly declines in overdraft/NSF revenue, such revenue remained flat across all quarters of 2023. Even with the substantial reductions in fees versus prior years, consumers paid over $5.8 billion in 2023 in reported overdraft/NSF fees.
• Evidence continues to suggest that financial institutions are generally not increasing other checking account fees to compensate for reduced overdraft/NSF revenue. Across all reporting banks, combined account maintenance and ATM fees remained flat from 2019 to 2023.

Since the CFPB heightened its supervisory attention on overdraft and NSF fees in 2022, financial institutions have agreed to refund over $240 million to consumers—approximately $177 million in unfair unanticipated overdraft fees charged on transactions that were authorized when the consumer had sufficient funds, and approximately $64 million in NSF fees charged on the same transaction that already incurred an NSF fee when it was previously declined. This $240 million reflects $120 million that the CFPB previously announced in October 2023, and an additional more than $120 million that financial institutions have agreed to refund since the period covered by that announcement. 2

This current analysis of bank call report data follows our previous analyses of trends in checking account fee revenue, most recently those published in May 2023 and October 2023 . The October 2023 spotlight reported that the vast majority of NSF fees have been eliminated. Thus, the remaining revenue being reported as combined overdraft/NSF fee revenue can be largely attributed to overdraft revenue alone.

Overdraft/NSF Fee Revenue

Banks with assets over $1 billion have been required to report overdraft/NSF fee revenue in their call report data since 2015. For each of the five years from 2015 to 2019, the overdraft/NSF revenue reported by these banks totaled $11-12 billion annually. 3 Bank overdraft/NSF fee revenue was lower in 2020 and 2021 than before the pandemic, likely primarily due to pandemic-related stimulus checks pushing up average checking account balances. 4 In the second half of 2021, overdraft/NSF fee revenue rebounded somewhat. However, this revenue began decreasing again in early 2022 and continued to decrease until the first quarter of 2023, before remaining at level amounts through 2023. The sustained reductions we see today compared to 2019 are likely due to changes in bank policies that started to go into effect toward the end of 2021 and throughout 2022.

The overall reduction in combined overdraft and NSF fees observed in 2023 primarily reflects a full-year effect of changes to bank policies at larger banks, though several larger and some smaller banks did further reduce overdraft and NSF fee revenue during the year. For the full year 2023, combined reported bank overdraft/NSF fee revenue was $5.83 billion, a decrease of 51%, or $6.13 billion, compared to the $11.96 billion reported in 2019, and 24% less than the $7.61 billion reported in 2022 (Figure 1). For the fourth quarter of 2023 alone, overdraft and NSF revenue was approximately $1.5 billion, compared to roughly $1.6 billion in the fourth quarter of 2022, a reduction of roughly 8 percent (Figure 2). However, quarterly overdraft and NSF revenue for all quarters of 2023 were roughly equivalent, suggesting banks have largely finished implementing policy changes.

FIGURE 1: Annual reported overdraft/NSF revenue 2015 to 2023

Source: Consolidated Reports of Condition and Income (“Call Reports”), Federal Financial Institutions Examination Council

FIGURE 2: Quarterly reported overdraft/NSF revenue 2019 to 2023 5

Despite these declines, reporting banks collected $5.8 billion in overdraft/NSF fees from their customers in 2023. Though many banks have made a range of changes to their policies in recent years, some banks continue to charge overdraft fees as high as $37 each . Overdraft fees can total hundreds of dollars per day, exacerbating financial setbacks. And they can lead to account closures, essentially pricing people out of the banking system .

Table 1 below compares overdraft/NSF revenue in 2023 to 2019 across specific banks and groups of banks. The individual banks listed were the largest overdraft/NSF revenue generators in 2021, with each collecting more than $200 million in these fees. Table 1 also shows trends among four groups of banks that generated $200M or less in overdraft/NSF fee revenue in 2021, consisting mainly of small and midsize banks. 6

Table 1: Change in overdraft/NSF fee revenue for the year 2023 versus 2019 for select individual banks and groups of banks 7

Despite the overall decrease in overdraft/NSF fee revenue, we continue to see significant differences across banks and groups of banks. While this evidence is indirect and does not control for changes in the number, composition, or behavior of accountholders, the variations likely reflect, in significant part, changes in overdraft/NSF programs. 8

All of the large banks listed have seen decreases in overdraft/NSF revenue of over 40% compared to 2019, and the total decrease across all eight banks was 58%. Specifically:

• Bank of America experienced the most significant decline by far (91%), which likely reflects the reduction of its overdraft fee to $10, the elimination of overdraft fees on ATM withdrawals, and the elimination of NSF fees, among other changes.
• TD Bank , Truist, U.S. Bank , and PNC all experienced declines of over 50%. Among other changes, all four banks eliminated NSF fees; TD Bank, U.S. Bank, and PNC established a grace period until the end of the next day before an overdraft fee is charged; TD Bank and U.S. Bank implemented $50 negative balance cushions; and PNC implemented a limit of one overdraft fee per day.
• JPMorgan Chase , Wells Fargo , and Regions experienced relatively smaller declines ranging from 43% to 46%. All three banks eliminated NSF fees and have introduced a grace period until the end of the next day before an overdraft fee is charged. JPMorgan Chase also implemented a $50 negative balance cushion.

As we did in May 2023, we are also analyzing the change in overdraft/NSF revenue at the individual bank level for the banks that reported between $50 million and $200 million in overdraft/NSF revenue in 2021, reflected in Table 2 below.

Table 2: Change in overdraft/NSF fee revenue for the year 2023 versus 2019 for banks that earned between $50 and $200 million in overdraft/NSF fee revenue in 2021

Capital One and Citibank have both eliminated overdraft and NSF fees entirely, reflected in their ~100% drop in associated revenue compared to 2019. USAA experienced a 90% decline in 2023, having eliminated NSF fees, while beginning to charge overdraft fees on checks and automated clearinghouse (ACH) transactions; the bank still does not charge overdraft fees on debit card point-of-sale or ATM transactions. M&T ’s revenues have dropped 73% since 2019, likely reflecting the reduction of its overdraft fee to $15 and a limit of one overdraft fee per day, along with the elimination of NSF fees. BMO Harris , newly added to this analysis this year due to its acquisition of Bank of the West, saw a 65% decline since 2019, likely reflecting the reduction of its overdraft fee to $15 and the elimination of NSF fees. 9 Huntington and KeyBank ’s revenues fell 64% and 56% since 2019, respectively; Huntington reduced its overdraft fee to $15, among other changes, while KeyBank reduced its overdraft fee to $20, among other changes; both banks eliminated NSF fees. Citizens’ fees dropped 54% since 2019; it began offering a grace period until the end of the next day and eliminated NSF fees, among other changes. First National Bank Texas/First Convenience Bank , Arvest , and Woodforest experienced smaller declines since 2019 ranging from 21-23%. Among other changes, First National Bank Texas/First Convenience Bank implemented a grace period until the end of the next business day, while Arvest and Woodforest eliminated NSF fees. Fifth Third experienced the smallest decline since 2019 at 16%.

For the first time, we are also presenting the change in overdraft/NSF revenue at the individual bank level for the banks that reported between $10 million and $50 million in overdraft/NSF revenue in 2021, reflected in Table 3 below. We find that banks in this group reported 33% less overdraft/NSF revenue in 2023 than they did in 2019, a reduction of nearly $400 million. Of the 47 banks in this group, 41 reduced overdraft/NSF fee revenue, and the median bank reduced such fees by 29%. Of banks that increased overdraft/NSF fee revenue, the median increase was 8%.

Table 3: Change in overdraft/NSF fee revenue for the year 2023 versus 2019 for banks that earned between $10 and $50 million in overdraft/NSF fee revenue in 2021

Other listed (maintenance and atm) fee revenue.

We also continue to examine other checking account fee revenue, in part to determine whether these fees may be increasing to replace reduced overdraft/NSF revenue. Call Reports require banks to list consumer deposit account revenue from three sources: 1) combined overdraft and NSF fees, 2) periodic maintenance fees, and 3) ATM fees. We refer to these three types of fees as “listed fees.” In Table 4 (structured similarly to Table 1), we report changes in listed fees other than overdraft/NSF fees – i.e., maintenance and ATM fees. As with prior analyses, we do not identify a clear relationship between declines in overdraft/NSF fee revenue and increases in other listed fee revenue.

Table 4: Change in other listed fee revenue (maintenance fees and ATM fees) for the year 2023 versus 2019 for select individual banks and groups of banks 10

Among the eight larger individual banks, compared to the pre-pandemic 2019 baseline, there was a divergence of experiences in other listed fee revenue. However, there is no clear relationship between decreases in overdraft/NSF fee revenue and increases in other listed fee revenue. Of the four banks with the most significant percentage declines in overdraft/NSF fee revenue, Bank of America’s other listed fee revenue dropped 9%, while TD Bank’s increased 19%, Truist’s fell 10%, and U.S. Bank’s decreased 23%. In terms of dollar amounts, the declines in overdraft/NSF fee revenue across all eight banks in 2023 ($4.6 billion) far exceeded the net increase in other listed fee revenue ($111 million) since 2019.

Banks with $50-$200 million and banks with $10-$50 million in 2021 overdraft/NSF revenue, on average, reported less revenue from other listed fees in 2023 than before the pandemic; in contrast, banks with $2-$10 million and under $2 million in 2021 overdraft/NSF revenue saw increases. Across all reporting banks, other listed fee revenue remained flat from 2019 to 2023, even as overdraft/NSF fee revenue decreased by $6.1 billion. 11

The CFPB’s focus on overdraft and NSF fees continues. The CFPB has proposed a rulemaking intended to ensure that overdraft offered by financial institutions with more than $10 billion in assets either operates as a courtesy or complies with regulations that apply to other consumer credit transactions. The CFPB has also proposed a rulemaking to prohibit NSF fees on transactions that are declined instantaneously or near-instantaneously.

The CFPB will also continue to follow trends in other listed fees.

For our latest review of overdraft/NSF policies, please see the  most recent table tracking overdraft fees and policies across banks and the most recent chart on NSF fee practices. For further discussion of trends in these practices, see our  February 2022 analysis ,  April 2022 analysis ,  July 2022 analysis ,  February 2023 analysis , May 2023 analysis , and  October 2023 analysis .

• Surveys prior to the pandemic found that approximately 25% of households overdrew their checking account, which amounts to roughly 33 million households. $6.1 billion in reduced fees divided by 33 million households equals $185 per household per year. Overdraft and NSF fees are not evenly distributed across households that overdraft, however. CFPB has previously found that nearly 80% of combined overdraft and NSF fees were shouldered by under 9% of accountholders who had more than 10 overdrafts annually. Thus, many households that have typically incurred a high number of overdraft or NSF fees have saved more than the average savings per household.
• The additional more than $120 million reflects approximately $79 million in unfair unanticipated overdraft fees charged on transactions that were authorized when the consumer had sufficient funds, and approximately $42 million in NSF fees charged on the same transaction that already incurred an NSF fee when it was previously declined.
• This revenue excludes overdraft/NSF revenue generated by banks with assets of $1 billion or less, which are not required to report overdraft/NSF fee revenue as a separate line item in their call report data, as well as overdraft/NSF revenue generated by all credit unions. Because some banks do not report in all years, some of the year-to-year variation in overdraft revenue reflects changes in the set of reporting banks.
• JPMC Institute, Household Pulse: The State of Cash Balances through March 2023.
• Some banks report fee revenue values for some quarters and not others. Most commonly, this occurs because banks with assets less than $5 billion are required to break out overdraft/NSF (and other listed fee) revenue only annually, not quarterly. Thus, some banks report all of their annual overdraft/NSF (and other listed fee) revenue in the fourth quarter. To estimate quarterly revenue with the benefit of the full year’s data, we allocate the annual reporters’ revenue to each quarter evenly, by applying one-fourth of it to each quarter.
• We define two groups of small banks, those collecting under $2 million and those collecting $2 million to $10 million in overdraft/NSF fee revenue in 2021, and two groups of midsized banks, those collecting $10 million to $50 million and those collecting $50 million to $200 million in overdraft/NSF fee revenue in 2021. Since our focus is exclusively on fee revenues, we use this categorization as opposed to the more common categorization by asset size. This is because overdraft/NSF revenue and asset size are strongly but not perfectly correlated. This means that some banks that are categorized as midsize banks here based on their overdraft/NSF revenue may not be midsize based on their assets. Conversely, some banks that are categorized as small banks here based on their overdraft/NSF revenue may not be small based on their assets.
• The data construction for Table 1 is the same as in our Dec 2021 report ; please see that report for details. The table restricts data to banks that reported listed fees during 2023.
• It is important to note that there are significant drivers of fee revenues besides bank overdraft program settings. An important one is the number of accounts consumers hold at a bank. While we merger-adjust the data, there can be significant changes in the number of accounts held at a bank even without mergers. We cannot examine this further since Call Reports do not require banks to report the number of consumer checking accounts they hold.
• In order to construct a consistent set of banks over time, all institutions in this report are merged to the entity that was listed as the owner as of December 31, 2023, after mergers and acquisitions. As a result, some historical figures may not correspond to prior reports. See “ Merger Adjusting Bank Data: A Primer ,” FDIC Quarterly 2018 Volume 13, Number 1.
• The data construction for Table 4 is the same as in our Dec 2021 report ; please see that report for details. The table restricts data to banks that reported listed fees during 2023.
• We also note that, as with overdraft/NSF fee revenue, there are a number of factors that could influence other listed fee revenues, making it difficult to isolate the impacts of any policy changes, or lack thereof, without further analysis. For example, the increases in savings, such as those observed during the pandemic, can lead to higher average account balances, which can result in fewer accounts being assessed minimum balance maintenance fees. Other factors, including growth in the number of accounts, would have the opposite effect.