How to submit.

Chaired by Samuel Fosso Wamba · Information Systems & Data Science, TBS Education

The spread of AI, data-driven decision-making, and platform business models is reshaping the digital economy — and putting digital sovereignty at the center of how organizations coordinate. Sovereignty here is the capacity of states, organizations, and societies to retain control over their data, infrastructures, technologies, and ecosystems even as they depend on cloud, AI, and global platforms. This session asks how that struggle between openness and control plays out where work is mediated by an algorithmic third party — and treats sovereignty as an organizational and coordination problem, not only a regulatory one.

We welcome theoretical, empirical, and practitioner contributions. Submit through the form below and flag "Digital Sovereignty" in the optional special-session field; pick whichever track fits best. Like everything at the conference, accepted work is reviewed in the open. Themes include:

• Foundations — defining and operationalizing digital sovereignty; its tensions with digital globalization; theoretical lenses (dynamic capabilities, institutional and platform theory).
• Technologies & infrastructures — AI sovereignty and algorithmic control; data governance and cross-border flows; cloud dependency and multi-cloud strategy; open-source vs. proprietary ecosystems.
• Organizations, platforms & supply chains — platform power, lock-in, and dependency; sovereign capabilities of SMEs; algorithmic management and supply-chain resilience; strategic responses to platform dominance.
• Global & regional perspectives — European, North American, Chinese, African, and Global South approaches to digital control and governance; comparative cross-country analyses.
• Futures & societal implications — governance models for sovereign digital ecosystems; ethics of AI and data sovereignty; digital inclusion, inequality, and sustainability.

Contributions from diverse geographical and intellectual backgrounds are strongly encouraged.

Chaired by Roger Hunt · Bentley University · conference convener

Algorithmacy isn't only a conference theme — it's an open, living research program, and this session is the front door to it. Everything runs in public: the algorithmacy research repository holds the code, probes, logged experiments, and papers, and every submission to the conference is itself a public pull request against that repository. This session invites work that uses, extends, or challenges that open apparatus — and shows newcomers exactly how to contribute to it.

We especially welcome contributions that put the open process to work: replications and re-analyses of logged experiments, new probes or instruments, method papers, negative and null results, and field accounts of algorithmically-mediated coordination. Submit through the form below and flag "Algorithmacy Research" in the optional special-session field; pick whichever track fits best.

Chaired by Dr. Uohna Thiessen · AI/ML Strategist & Educator — Break Through Tech AI, Cornell Tech

Algorithmacy assumes a worker can actually read the algorithmic third party they coordinate through — but most people can't. This session treats algorithmic literacy, the everyday fluency in data and AI, as the missing coordination competency. When a chatbot mediates a customer conversation, a model routes a task, or a recommendation shapes a decision, the humans on both sides need enough fluency to trust, question, and steer the mediator between them. Drawing on work in democratizing AI, radically accessible data-science education, and responsible AI, it asks how literacy becomes the infrastructure that makes algorithmically mediated coordination work — and who gets left out when it is missing.

We welcome theoretical, empirical, pedagogical, and practitioner contributions. Submit through the form below and flag "Algorithmic Literacy" in the optional special-session field; pick whichever track fits best. Like everything at the conference, accepted work is reviewed in the open. Themes include:

• Literacy as competency — the minimum viable AI and data fluency a non-specialist needs to coordinate through an algorithm; what "good enough" looks like, and how it differs from expert data science.
• Conversational mediation — chatbots and conversational AI as the third party in customer engagement, marketing, and hyper-personalization; trust, handoff, and accountability between human and bot.
• Democratization & access — "data belongs to those who generate it"; closing literacy gaps and breaking barriers for underrepresented communities in algorithmically mediated work.
• Responsible & legible AI — making models contestable and steerable by the people they coordinate rather than opaque to them; literacy as a precondition for governance and worker voice.
• Pedagogy & practice — radically accessible ways to teach data science and machine learning, from team-based industry-project programs to teaching statistics through dance; building coordination-ready practitioners.

Practitioner reports, classroom and field studies, and cross-disciplinary contributions are strongly encouraged.