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Aims & Scope

Overview

The AUIB Journal for AI and Sustainable Development (JAIS) is a peer-reviewed, open-access journal dedicated to advancing rigorous, interdisciplinary scholarship on the intersection of artificial intelligence and sustainable development. JAIS examines how AI technologies are conceived, designed, deployed, governed, and experienced across societal contexts, and how they may support or undermine the goals of long-term equitable and sustainable development.

JAIS is committed to producing knowledge relevant to diverse global audiences, with particular attention to Iraq, the MENA region, and Africa, while engaging with global challenges and opportunities.

Thematic Scope

The journal welcomes original research, critical analyses, and conceptual contributions across the following themes:

  • Digital inclusion and equitable access: Research on the affordability, accessibility, and societal impact of digital technologies, with particular attention to vulnerable and marginalised populations and the conditions for inclusive development.
  • Fairness, transparency, and accountability in AI: Critical examination of algorithmic decision-making, explainability, bias, and auditability, especially as these bear on public policy, governance, and sustainable development outcomes.
  • Institutional capacity and AI-enabled governance: Empirical and analytical work on how automation, decision-support systems, and digital tools affect public institutions, professional roles, and governance quality, with attention to ethical standards and institutional resilience.
  • AI for the SDGs, sectoral and comparative analyses: Case-based, empirical, and comparative studies of AI and digital interventions in health, education, environment, social protection, urban development, finance, and public administration, assessed against the 2030 Agenda for Sustainable Development.
  • Governance and regulation of emerging technologies: Research on risk assessment, regulatory frameworks, oversight mechanisms, human rights alignment, data protection, and the constitutional and legal dimensions of AI deployment for sustainable ends.
  • Participatory and co-design approaches: Work that centres communities, civil society, and multi-stakeholder collaboration in the design and evaluation of technology-enabled solutions for sustainable development.
  • Digital literacy, education, and capacity development: Studies of skills development, training models, and institutional learning that support responsible technology engagement and innovation across SDG-related sectors.
  • Ethical, social, and economic implications of digital transformation: Analyses of bias, inequality, labour transformation, power asymmetries, environmental impact, social cohesion, and public trust as they relate to AI and sustainable development.

Types of Manuscripts Considered

To support this diverse thematic scope, JAIS welcomes submissions in the following formats:

  • Original Research Articles: Comprehensive empirical, methodological, or theoretical studies presenting novel findings.
  • Review Articles: In-depth, critical syntheses of existing literature on topics relevant to AI and sustainable development.
  • Policy & Practice Perspectives: Critical analyses or conceptual contributions focusing on governance, regulatory frameworks, and real-world implementation.
  • Case Studies: Detailed, context-specific investigations of AI deployment and its socioeconomic impacts.

Disciplinary Coverage

JAIS is genuinely interdisciplinary. The journal engages research from computer science, data science, public administration, political science, sociology, science and technology studies, ethics, law, economics, health sciences, and education. Within AI research, it is particularly interested in machine learning, natural language processing, explainable AI, human–AI interaction, algorithmic decision-making, and AI governance, situated within broader sustainability frameworks rather than treated as ends in themselves.

Research Methods and Formats

JAIS welcomes contributions using quantitative, qualitative, mixed-methods, and design-based approaches. Scholarly formats include empirical studies, conceptual frameworks, pilot studies, policy analyses, and interdisciplinary collaborations that connect theory, practice, and policy. Submissions arising from publicly funded research or intended to reach broader professional or public audiences are particularly encouraged.

In strict alignment with open science and FAIR data principles, the journal mandates methodological transparency and reproducibility. While we recognize that not all data sets can be shared openly due to privacy or ethical constraints, all submissions must include a formal Data Availability Statement detailing where and how the data supporting the findings can be accessed or explicitly stating the ethical/legal reasons why the data cannot be shared.

What JAIS Does Not Cover

JAIS does not publish purely technical AI research that lacks a substantive engagement with sustainability, governance, or societal implications. Incremental engineering contributions, benchmark studies without applied developmental context, or submissions that treat AI as a neutral tool without critical reflection on its social embeddedness will not normally fall within scope.

A Note on Language and AI-Assisted Editing

JAIS publishes manuscripts in English. Authors are responsible for ensuring that their submissions are written clearly, concisely, and accurately before submission. Peer reviewers are not expected to correct grammatical errors, and significant language deficiencies may result in desk rejection or publication delays.

If you require assistance with academic English, we strongly encourage utilizing one of the following options prior to submission:

  • Professional Services: Utilize a professional academic language editing service.
  • AI-Assisted Polishing: Authors may responsibly use Generative AI tools (e.g., ChatGPT, Grammarly) strictly as an editing tool to improve the readability, grammar, and formatting of their human-generated text. Note: If GenAI is used for language editing, authors must verify the output to ensure it preserves their original scientific meaning, and they remain entirely accountable for the final content. AI cannot be used to generate core scientific insights or be listed as an author.