Skip to content
#federated learning Book Open access

THE EL-RAKHAWI SOVEREIGN PROTOCOL (ERSP) An Open Scientific-Technical Framework for Building Ethically Guaranteed, Ecologically Sustainable, and Human-Centric Digital Systems A Foundational Protocol Specification Unifying Formal Verification, Sovereign Data Architecture, Green Computing, Algorithmic Accountability, and Cognitive Dignity into a Single Open Standard for Global Digital Civilization

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI

Abstract

The El-Rakhawi Sovereign Protocol (ERSP) (DOI: 10.5281/zenodo.23235007) is an open scientific-technical specification designed to build ethically guaranteed, ecologically sustainable, and human-centric digital systems. Analogous to TCP/IP, the ERSP provides a unified five-layer architecture for digital integrity: (1) Sovereignty Layer (data locality, post-quantum encryption, sovereign federated learning); (2) Ethical Verification Layer (normative operationalization, formal policy contracts, mandatory human-in-the-loop gates); (3) Ecological Layer (green computing, energy budgeting, carbon tracking); (4) Accountability Layer (immutable logging, causal explanations, decentralized trust); and (5) Human Dignity Layer (cognitive load minimization, anti-addiction protocols, universal accessibility). At its core is the Protocol Integrity Index (PII), a conceptual heuristic framework operating under the Weakest-Link Axiom to assess systemic compliance. Released freely under the Ferial Zayed Humanitarian License, the ERSP serves as a foundational, royalty-free global standard for regenerative digital civilization.

View source

Similar papers

#machine learning Review Open access Oct 2014

Software development in startup companies: A systematic mapping study

The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al. · 394 citations · ⚡54
#machine learning Review Open access Jun 2014

Why Early-Stage Software Startups Fail: A Behavioral Framework

This state-of-practice investigation was performed using a literature review followed by a multiple-case study approach and presents how inconsistency between managerial strategies and execution can lead to failure by means of a behavioral framework.

Carmine Giardino, Xiaofeng Wang, P. Abrahamsson · 175 citations · ⚡19
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#machine learning Review Open access May 2016

Key Challenges in Software Startups Across Life Cycle Stages

It is found that what perceived as biggest challenges by software startups do vary across different life cycle stages, even though its significance decreases when the learning focuses of the startups move from problem to solution and their products mature.

Xiaofeng Wang, Henry Edison, Sohaib Shahid Bajwa et al. · 62 citations · ⚡6

Related blog posts

MIT News · Artificial Intelligence Oct 7, 2026

Discovering the value of humanistic inquiry

Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.

Microsoft Research Blog Oct 7, 2026

Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses

Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.