=========== CALL FOR PAPERS ===========
ACM GOODIT 2026
6th ACM International Conference on Information Technology for Social
Good
Pisa, Italy, 2-4 September 2026
https://goodit2026.di.unipi.it
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The ACM 6th International Conference on Information Technology for
Social Good (GoodIT 2026) is a premier international forum for
researchers, practitioners, and educators to present and discuss the
latest innovations, trends, and challenges in leveraging technology,
data, and interdisciplinary approaches for Social Good and the UN
Sustainable Development Goals. The conference welcomes contributions
that explore the intersection of technology with fields such as social
sciences, healthcare, environmental studies, and public
policy—highlighting the broader impact of digital transformation on
society.
Alongside the main track, the conference features the Work-in-Progress
Track and the PhD Track. The Work-in-Progress Track provides an
excellent opportunity for practitioners and researchers from diverse
domains to present early-stage work, share ideas, and receive valuable
feedback, fostering cross-disciplinary discussions and collaborations.
The PhD Track is designed for doctoral students at different stages of
their research, offering a unique space to present and refine their work
with guidance from experienced researchers across various disciplines.
Additionally, the program will be enriched with several Special Tracks,
complementing the existing five conference tracks. These tracks will
further emphasise the interdisciplinary nature of GoodIT 2026,
addressing topics at the convergence of technology, ethics,
sustainability, and societal impact. The forthcoming Call for Papers
will outline these tracks in detail. The list of special tracks will be
available at a later date.
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Conference Track
==================
For our Main Track, Work in Progress Track, and PhD Track, we welcome
submissions on a wide range of topics, including but not limited to:
- Data Science and AI for Social Good:
Social Impact of Machine Learning Applications
Data and Algorithmic Biases and Potential Societal Risks
Large Language Models (LLMs) and GenAI Models' Impact on Society
Fairness, Accountability, and Transparency in Machine Learning
Citizen Science and Civic Intelligence
Data Sensing, Processing and Persistence
- Technology and Applications for Social Good:
AI and Machine Learning for Social and Humanitarian Response
IoT Solutions for Sustainable Development
Decentralised Approaches to IT
Digital Solutions for Cultural Heritage
Game, Entertainment, and Multimedia Applications
IT for Education, Smart Living, Health and Social Care
Social Informatics
- Environmental Sustainability and Technology:
Green Computing and Energy-Efficient Technologies
Climate Change Modelling and Environmental Science
Smart Cities and Sustainable Urban Development
Sustainable Networking and Communication Systems
Technology Addressing the Digital Divide
Sustainable Cities and Transportation
Frugal Solutions for IT
- Ethics, Policy, and Governance in Tech for Social Good:
Regulatory and Policy Frameworks for Ethical Tech
Governance of AI and Autonomous Systems in Social Contexts
Digital Rights and Freedom in the Age of Technology
Data Privacy and Security in Social Applications
Privacy and Trust Issues and Solutions
Smart Governance and E-administration
Socially Responsible IT Solutions
======================
Submission Guidelines
======================
Submitted papers must be original works and must not have been
previously published.
All papers must clearly outline the research question, methodology,
results, and implications for social good.
The papers should follow the new ACM format
(https://authors.acm.org/proceedings/production-information/taps-production-workflow).
* Main Track and Special Tracks Full Paper Submission should be a
maximum of 9 pages. (ACM double column format)
* Work-in-Progress papers should be a maximum of 6 pages. (ACM double
column format)
* Ph.D. track papers should be a maximum of 4 pages. (ACM double column
format)
The indicated paper length includes references, tables, and figures.
Documents with a length disproportionate to their contribution will be
rejected. These submissions will undergo a single-blind peer review
process involving three evaluations each. Accepted papers will be
included in the ACM Digital Library.
Each accepted paper must have at least one of its authors register for
and physically present the work at the conference. Please consider that
this is a condition to ensure the paper is included in the conference
proceedings. There will not be possibilities to present online/remote.
For additional details, please check the “Submission of Papers” web
page.
By submitting your article to an ACM Publication, you are hereby
acknowledging that you and your co-authors are subject to all ACM
Publications Policies, including ACM's new Publications Policy on
Research Involving Human Participants and Subjects. Alleged violations
of this policy or any ACM Publications Policy will be investigated by
ACM and may result in a full retraction of your paper, in addition to
other potential penalties, as per ACM Publications Policy.
Please ensure that you and your co-authors obtain an ORCID ID, so you
can complete the publishing process for your accepted paper. ACM has
been involved in ORCID from the start and we have recently made a
commitment to collect ORCID IDs from all of our published authors. We
are committed to improve author discoverability, ensure proper
attribution and contribute to ongoing community efforts around name
normalisation; your ORCID ID will help in these efforts.
======================
Important update on ACMs new open access publishing model for 2026 ACM
Conferences!
======================
Starting January 1, 2026, ACM will fully transition to Open Access. All
ACM publications, including those from ACM-sponsored conferences, will
be 100% Open Access. Authors will have two primary options for
publishing Open Access articles with ACM: the ACM Open institutional
model or by paying Article Processing Charges (APCs). With over 2,600
institutions already part of ACM Open, the majority of ACM-sponsored
conference papers will not require APCs from authors or conferences
(currently, around 76%).
Authors from institutions not participating in ACM Open will need to pay
an APC to publish their papers, unless they qualify for a financial
waiver. To find out whether an APC applies to your article, please
consult the list of participating institutions in ACM Open and review
the
https://www.acm.org/publications/policies/policy-on-discretionary-open-access-apc-waivers.
Keep in mind that waivers are rare and are granted based on specific
criteria set by ACM.
Understanding that this change could present financial challenges, ACM
has approved a temporary subsidy for 2026 to ease the transition and
allow more time for institutions to join ACM Open. The subsidy will
offer:
$250 APC for ACM/SIG members
$350 for non-members
This represents a 65% discount, funded directly by ACM. Authors are
encouraged to help advocate for their institutions to join ACM Open
during this transition period.
This temporary subsidised pricing will apply to all conferences
scheduled for 2026.
======================
Important Dates
======================
- Proposals for Special Tracks: February 7th, 2026.
- Special Track Proposal acceptance notification: February 14th, 2026.
- Full Paper submission deadline (all): May 17th, 2026.
- Acceptance Notification Deadline (all): June 7th, 2026.
- Camera-Ready Submission (all): June 21st, 2026.
- Conference Dates: 2-4 September 2026, Pisa, Italy.
======================
HOTCRP Submission Link
======================
Please submit your papers through our online submission portal available
at: https://goodit2026.hotcrp.com/
======================
Contact Us
======================
For any inquiries regarding the call for papers, please contact
andrea[dot]michienzi[at]unipi[dot]it
We look forward to your contributions and to seeing you at the ACM
GOODIT 2026 Conference!
ACM GOODIT 2026 Conference Committee
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Andrea Michienzi
PhD, Università di Pisa - Department of Computer Science
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