Anasse Bari, Ph.D.

🚀 New Release! AI-Based Strategies to Enhance the Visibility and Impact of Scientific Outputs – Part 1 by Nader Ale Ebrahim (2025) Learn how to use AI tools to boost your research visibility, increase citations, and build your academic brand. 📊 Smart strategies. 🔍 Better discoverability. 🎯 Greater impact. 📥 Access the full presentation on Figshare: https://lnkd.in/d58XJUj7 #AI #ResearchVisibility #AcademicImpact #OpenScience #NaderAleEbrahim

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New book chapter is out: "The Coloniality of Artificiality". Co-authored with El Mehdi Bellaarabi, this chapter introduces and defines a new critical framework for understanding AI's power dynamics. We argue that the 'coloniality of artificiality' “captures the ways in which artificial intelligence (AI) systems reinforce, sustain, and expand hierarchies through a seemingly logical, rational, and systematic gathering, reasoning, filtering, and representing of data, and knowledge”. The chapter further contends that AI's 'essence' is its intelligence, but its 'existence' is shaped by external worldviews. We may be overfocusing on AI as a standalone 'existence' while its reality may be fundamentally an extension of its developers and users. This leads us to question whether AI can be truly critical (depending on how we define ‘criticality’ ourselves), proposing that its capacity is contingent on the specific situated context of each interaction, not just its programming. Consequently, its potential for critical interculturality depends not on prompts or code alone, but on a situated interweaving of context, knowledge, and language. This is a key contribution to the forthcoming book, 'Who's Afraid of AI? Fear and Hope in Intercultural Perspectives’, out October 31st. https://lnkd.in/ggbNzu89

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New Release: Generators, Bots, and Tutors: Creative Approaches to Human‑AI Synergy in Classroom Instruction Co-edited by Bosede Edwards, PhD , Hassan Abuhassna , Damola Olugbade, Ph.D. @Olugbade, Olayinka A. Ojo, and @Wan A. J. Wan Yahaya, this 2025 IGI Global volume explores how AI-powered agents—generators, conversational bots, and intelligent tutors—are reshaping education . Highlights include: Designing human–AI collaborative learning environments Using generative AI and bots to boost engagement and personalize learning Examining virtual tutors and emotional connections in the classroom If you're interested in ed‑tech, adaptive learning, or integrating AI in education—this is for you. Dive in here: https://lnkd.in/gW_tiu45

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AI Transforms Grant Writing: Lessons from the 6/6/25 Grant Professionals NYC Meeting Grants Professionals of NYC (GPNYC) convened seasoned AI users and newcomers to share real-world insights on integrating artificial intelligence into grant writing practice. The takeaways were surprisingly practical. What Actually Works: Give AI context and background—it's the difference between generic copy and targeted, compelling narratives that speak directly to funders' priorities. Treat AI as a collaborative partner, not a magic button. The best results come from multiple rounds of refinement and strategic questioning. Never input confidential data or sensitive organizational information. Privacy protections vary widely across platforms. The Bottom Line: AI substantially reduces time spent on first drafts, allowing grant writers to focus more energy on research, strategy, and relationship building. Unexpected Benefit: Even experienced writers were impressed enough by Claude's writing quality to incorporate its suggestions into their own work. Participants said Claude exceeded their expectations—by a wide margin. Join Us in September: We're hosting a follow-up session on writing effective prompts to maximize AI's impact. Friday, September 26, 2-4 PM. Save the date! *This post was co-written with Claude.ai. #gpnyc #grants #grantprofessionals #ai #grantai

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Global Governance and Muslim Organizations Edited By Leslie A. Pal & M. Evren Tok Springer, 2018 Our Chapter Can the Sharī’ah Be Compatible with Global Governance? Islamic Financial Institutions as a Laboratory for Conceptual Analysis By Mesut Idriz & Joseph J. Kaminski Abstract This chapter introduces the notion of Sharı’ah as a multilevel and multifaceted concept. It reviews both classical and contemporary scholarship to show that Sharı’ah law in regard to financial institutions has its own special characteristics, but not ones that make it incompatible with the global regulation of financial institutions. It offers a discussion of global governance and good governance from this perspective and then closes with an analysis of the case of Islamic financial institutions and their supervisory boards as an example of the intersection of good global governing practices and Sharı’ah. The chapter does not claim that these institutions as they currently stand are paragons of good global governance in action; rather it seeks to argue that these institutions can be engaged with and can serve as examples of good global governance in action so long as they continue to be developed and evaluated by scholars across disciplines. https://lnkd.in/dvhsaxUc

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🎓 Ontology, Epistemology, and Research Paradigms — Explained Simply (with Examples) By Prof. Islam Elgammal As a university professor, I often see early-career researchers struggle with these three terms. They sound abstract, but once grounded in examples, they become practical tools rather than philosophical hurdles. Let’s break them down 👇 🔹 Ontology – What is reality? Ontology is about the nature of reality. In simple terms: 👉 What exists? What is real? Examples: Do customer satisfaction levels exist as objective facts that can be measured? Or are they subjective experiences, different for each individual? In research practice: A survey measuring satisfaction scores assumes a more objective reality. Interviews exploring personal experiences assume multiple realities. 🔹 Epistemology – How do we know what we know? Epistemology concerns how knowledge is created and validated. In simple terms: 👉 How can we know about reality? Examples: Can we know reality through numbers, measurement, and statistics? Or through meanings, interpretations, and dialogue? In research practice: Statistical testing reflects a belief that knowledge is gained through measurement. Qualitative interviews reflect a belief that knowledge is co-constructed between researcher and participant. 🔹 Research Paradigm – How do we research? A research paradigm brings ontology + epistemology together and guides the entire study. In simple terms: 👉 Given what we believe about reality and knowledge, how should we do research? Examples: Positivist paradigm: objective reality + measurable knowledge → surveys, experiments Interpretivist paradigm: multiple realities + constructed knowledge → interviews, observations Pragmatic paradigm: “what works for the question” → mixed methods 🧠 Why these matter? Many published papers use these concepts without naming them—but understanding them helps you: ✔ justify your methodology ✔ design coherent studies ✔ respond confidently to reviewers 📌 Remember: Ontology and epistemology shape your research paradigm, and your paradigm shapes every methodological decision you make. If you’re supervising students or writing a methodology chapter, clarity here saves time, confusion, and weak justifications. 💬 How do you usually explain these concepts to your students or research teams?

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This essay made me think that we're witnessing a shift: as we move from deterministic systems to agentic, probabilistic ones (think LLMs + AI), communication within systems transitions from rigid architectural constraints to intentional agreements — in other words, shared semantics. In this new paradigm, actors operating in low-variety, low-complexity workflows (say, a coffee shop) have little incentive to define or manage ontologies — they want invisible systems that “get the job done” seamlessly. On the other hand, in complex environments (multi-product, multi-stakeholder), you must make meaning explicit — and that’s where shared ontologies become the new platforms. Either way, we’re leaving behind an era where architecture imposed constraints, and entering one where LLMs not only enable but in some sense demand that those creating value define the semantics, the ontologies, and, fundamentally, understand what they’re doing, how, and soon even why they’re doing it. seminal thinking here by Pete Koomen https://lnkd.in/dtbEQNkJ

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Professor Nagla Rizk ’83, ’87, founding director of AUC’s Access to Knowledge for Development Center, has been named by Leading Ladies Africa as one of 19 African Women Leading the Global AI Transformation. Her impactful work spans data governance, gender inclusion and the gig economy, shaping a more equitable digital future. Read more: https://lnkd.in/e3vCJSVW

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🎓 New insights on AI tools for qualitative research: Testing Google's NotebookLM with historical methodology As qualitative researchers, we're constantly seeking tools that can help us manage vast amounts of textual and media data without compromising scholarly rigour. My recent experiment with Google's NotebookLM using our co-authored article on historical imagination (with Elena Giovannoni and Emmanuella Plakoyiannaki) and the Bauhaus reveals important insights about AI tools in academic research. Using my recent co-authored article on historical imagination and the Bauhaus as a test case, I evaluated NotebookLM's capacity as a data extraction tool for historians and social scientists. The platform offers compelling features: controlled data input, clear source attribution, and innovative outputs including mind maps, timelines, and AI-generated podcast discussions. However, the results highlight a fundamental challenge with AI applications in qualitative research—the "false negative" problem. While the AI hosts became thoroughly obsessed with Bauhaus design history, they completely missed the article's core methodological contributions: 💡 Historical Imagination Framework: Our article refines Collingwood's concept through three distinct operations: - interpolation (logically connecting evidence to fill gaps) - interpretation (assessing plausibility within existing contexts) - understanding (the cognitive-affective bridge between past and present that enables empathetic comprehension of historical actors' experiences) 👯 Ego- and Alter-Documents: Building on Tinning & Lubinski's (2022) article, we distinguish between ego-documents (sources revealing personal experience) and alter-documents (sources describing "the Other"). Alter-documents are particularly valuable as they reveal both the observer's perspective and provide insights into how innovation and ideas were received in their historical context. 📜 Standards for Historical Narrative Construction: We establish four criteria for rigorous historical narratives: (1) continuity, and coherence; (2) localisation in time and space; (3) consistency with existing historical accounts; and (4) grounding in evidence. These standards ensure historical imagination remains anchored to empirical data. Interestingly, while NotebookLM's AI hosts became obsessed with Bauhaus design details, they initially missed these core methodological contributions entirely—only engaging with them when directly prompted. This highlights both the potential and limitations of AI tools in extracting nuanced theoretical frameworks from academic work. Our article is out advance online and #OpenAccess in Management & Organizational History https://lnkd.in/eZfN3ZB8 #AcademicResearch #QualitativeResearch #DigitalHumanities #HistoricalMethods #AIinAcademia #orghist British Academy of Management

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AI for MOF/materials discovery has advanced rapidly using computational datasets. But we wondered: What if we could leverage the entire body of knowledge in AI systems—experimental & computational data, expert insights, and the full literature? 🤔 🚀 Thomas Pruyn and Amro A. introduce MOF-ChemUnity — a new way for both humans and machines to read, navigate, and reason over scientific literature. 🔍 Powered by #LLM agents: • MOF name disambiguation & crystal matching • Extraction of synthesis routes, properties & applications • Structuring knowledge into a unified, machine-actionable graph MOF-ChemUnity unifies knowledge from over 10,000 scientific articles for over 15,000 MOF crystal structures in a graph containing over 40,000 nodes and 3,200,000 relationships. Literature is no longer just papers—it’s a structured, searchable knowledge base. 📖 We showcase a couple of exciting use cases for this dataset in our paper. Just to highlight one: 🤖 A literature-informed AI assistant that retrieves, infers and recommends MOFs with 2× higher trust and accuracy (as rated by experts) over standard LLMs (i.e., GPT-4(w/o web search)). Links to #AI4ChemS article #4: 🗞️ Preprint: https://lnkd.in/gV8rc-TE 💻 Code: https://lnkd.in/g6iEz7GD Huge congrats to Thomas Pruyn, Amro A., Sartaaj Khan and Robert Black for all their incredible work to get this done! Grateful to National Research Council Canada / Conseil national de recherches Canada, Acceleration Consortium, Data Sciences Institute, University of Toronto, and Natural Sciences and Engineering Research Council of Canada (NSERC) for supporting our research. Work done at Chem Eng at UofT, University of Toronto Engineering, University of Toronto, and Vector Institute #AI4Science #MOFs #LLM #KnowledgeGraph #MaterialsInformatics #MachineLearning #AI4Materials #AI4Sustainability

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My recent paper on al-Ghazālī's appropriation and critique of Ibn Sīnā's view of metaphysical causality is out: Ibn Sīnā and al-Ghazālī on Causality as Necessary Connection, and Occasionalism: Theology and Science: Vol 0, No 0 - Get Access https://lnkd.in/e9Fd3yMN Abstract: This paper examines the relationship between necessity and causality in the philosophies of Ibn Sīnā and al-Ghazālī, with a focus on occasionalism. My analysis uncovers that al-Ghazālī, while critiquing Ibn Sīnā's concept of causal necessity, implicitly grasps a distinction between de reand de dicto necessity. I argue that al-Ghazālī’s acceptance of de dicto necessity, allows him to articulate a more robust principle of causality, termed here the “meta-principle of causality.” This principle forms the basis of a three-step framework supporting occasionalism, offering new insights into the doctrine.

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New Publication Alert: I am pleased to share our latest paper published in European Management Review: “Building clusters without trust: Government as a relational architect in industrial cluster formation.” with Professor Omar AL-Tabbaa (lead author), Dr. Fahime Sadat Saadatyar, Dr. Maksym Koghut, and Dr. Zahra Vazife. Read our paper: https://lnkd.in/egKx84sR What is this paper about? In many developing economies, clusters don’t grow naturally. Instead, they are created through government policies aiming to boost local industries. The challenge is: How can firms collaborate if there is no existing trust or shared way of working? Our study explored two government-created clusters in Iran and found that governments can act as “relational architects” by designing the right structures (who is involved, how they connect) and building shared understanding (why they are working together) to eventually grow trust over time. What are the theoretical contributions? - Challenges the widely held belief that trust is a precondition for collaboration by showing that trust can emerge as an outcome of structured government interventions. - Extends social capital theory by illustrating how structural capital (the network of connections) and cognitive capital (shared language and goals) can lay the groundwork for relational capital (trust and mutual norms) to grow. - Positions governments as dynamic “relational architects” who shape not just physical infrastructure or policy incentives but also the social relationships that make clusters work. - Emphasises the temporal and process-oriented nature of cluster development – showing that trust-building is not a one-off intervention but an evolving process. Managerial insights If you are managing a business in a cluster: - Don’t assume that collaboration will happen just because firms are nearby – invest in building relationships and trust intentionally. - Create opportunities for small wins – such as joint training or pilot projects – to show the value of working together. - Recognise the importance of having credible brokers or coordinators who can connect firms, resolve misunderstandings, and maintain momentum. - Be aware that forced collaborations rarely succeed unless partners see mutual benefit and have space to build shared understanding. Policy implications: - Design policies that are flexible and adaptive to local cultures and business norms rather than copying models from other regions. - Measure success not just by outputs (number of firms involved) but by trust-building indicators, such as frequency of collaboration, information sharing, and joint problem solving. - Appoint and support intermediaries who can act as trusted brokers, as they are crucial in turning policy into meaningful relationships and outcomes. #clusters #trust #socialcapital #policy #management #economicdevelopment #publication #research #collaboration

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