AI Internal Audit M7 (Arabic): AI Ethics and Bias   46-page PDF document
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AI Internal Audit M7 (Arabic): AI Ethics and Bias – PDF

PDF document Arabic 46 Pages

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Crafted by Amer Morgan, a seasoned Senior Consultant with 30+ years in audit leadership across global entities, including profound engagements with Internal Audit, Risk Management, and Corporate Governance.
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VIDEO DEMO

BENEFITS OF THIS DOWNLOADABLE PDF DOCUMENT

  1. Equips auditors to audit AI for ethics, bias, and fairness using disciplined, evidence-based procedures rather than subjective impressions.
  2. Clarifies multiple fairness definitions (demographic parity, equalized odds, calibration) and helps audit teams evaluate which definition the organization has adopted.
  3. Provides bias testing and fairness assessment templates and real case references from hiring tools, healthcare algorithms, and facial recognition.

AUDIT MANAGEMENT PDF DESCRIPTION

AI Internal Audit Ethics Bias PDF (Arabic): Download AI ethics, bias testing, NIST AI RMF & EU AI Act audit templates and case studies for GCC MENA auditors. AI Internal Audit M7 (Arabic): AI Ethics and Bias is a 46-page PDF document available for immediate download upon purchase.

[Arabic Edition · تدقيق أخلاقيات الذكاء الاصطناعي والتحيز والإنصاف] The AI-Powered Internal Audit Professional Series – Module 7: AI Ethics, Bias, and Fairness Auditing – is part of a comprehensive 15-module program aligned with the NIST AI Risk Management Framework, ISO/IEC 42001, the IIA Global Internal Audit Standards (GIAS 2024), and the EU AI Act. This is the Arabic-language edition of the series, designed for internal auditors, audit managers, IT auditors, GRC professionals, and Chief Audit Executives (CAEs) across the GCC, MENA, and Arabic-speaking markets in Egypt, Iraq, Jordan, Lebanon, Sudan, Libya, Morocco, Tunisia, and Algeria. Content is delivered in Modern Standard Arabic with international standards terminology preserved in English (e.g., NIST AI RMF, ISO 42001, EU AI Act, GIAS 2024) for searchability and conformance traceability.
Disciplined approach to auditing AI for ethics, bias, and fairness – sources of bias, ethical principles (fairness, transparency, accountability, human oversight), fairness metrics, bias testing methodology, and real cases from hiring tools, healthcare, and facial recognition.
What's inside this module: • 45 professionally designed slides in Modern Standard Arabic (MSA / فصحى) • Ready-to-use templates and worksheets including: Bias assessment checklist; fairness metrics guide; ethics audit template; bias testing methodology framework; AI ethics policy template • NIST AI RMF, ISO 42001, and EU AI Act conformance references mapped to relevant requirements • Practical case examples drawn from real audit engagements with cited authoritative sources (Deloitte, IIA, ISACA, NIST) • Knowledge-check questions for self-assessment and team training • Fully editable PowerPoint (PPTX) format – customize with your organization's branding
Who it's for: Internal auditors in GCC/MENA organizations preparing for ISACA AAIA and CIA/CRMA certifications, audit managers building team AI capability in Arabic-speaking teams, IT auditors expanding into AI assurance, GRC professionals expanding into AI risk, training departments delivering bilingual AI audit programs, and CAEs modernizing audit functions for the AI-enabled environment in regional markets.
Why this module matters: Most Arabic AI audit training material is either translated from English without adapting examples and frameworks for Arabic readers, or built on outdated AI references that miss NIST AI RMF, ISO 42001, and the EU AI Act. This module is native to the current AI governance landscape, professionally formatted for right-to-left reading, and built by a CIA/CRMA/CFE practitioner with 30+ years of audit leadership across the GCC, MENA, Europe, and the USA.
About the author: Amer Morgan, CIA, CRMA, CFE, is the founder of Business Excellence and a Senior Consultant who has led internal audit functions across government and private-sector organizations in Qatar, the wider GCC, MENA, Europe, and the USA. He has authored 60+ professional publications in English and Arabic and trained thousands of audit professionals across the region.
Arabic version of the description (paste this into the Flevy field directly below the English text – single field, one copy-paste):
السلسلة الاحترافية للتدقيق الداخلي المدعوم بالذكاء الاصطناعي – الإصدار العربي – الوحدة 7: تدقيق أخلاقيات الذكاء الاصطناعي والتحيز والإنصاف – جزء من برنامج شامل من 15 وحدة متوافق مع إطار إدارة مخاطر الذكاء الاصطناعي من NIST و ISO/IEC 42001 والمعايير العالمية للتدقيق الداخلي (GIAS 2024) وقانون الذكاء الاصطناعي الأوروبي. هذا هو الإصدار العربي من السلسلة، مصمم للمدققين الداخليين ومديري التدقيق ومدققي تقنية المعلومات ومتخصصي الحوكمة والمخاطر والامتثال ورؤساء المراجعة الداخلية (CAEs) في الخليج والشرق الأوسط وشمال أفريقيا والأسواق الناطقة بالعربية.
مقاربة منضبطة لتدقيق الذكاء الاصطناعي للأخلاقيات والتحيز والإنصاف – مصادر التحيز، والمبادئ الأخلاقية (الإنصاف والشفافية والمساءلة والرقابة البشرية)، ومقاييس الإنصاف، ومنهجية اختبار التحيز، وحالات حقيقية من أدوات التوظيف والرعاية الصحية والتعرف على الوجه.
محتوى هذه الوحدة: • 45 شريحة احترافية باللغة العربية الفصحى • نماذج وأوراق عمل جاهزة للاستخدام تشمل: قائمة فحص تقييم التحيز؛ دليل مقاييس الإنصاف؛ نموذج تدقيق الأخلاقيات؛ إطار منهجية اختبار التحيز؛ نموذج سياسة أخلاقيات الذكاء الاصطناعي • مراجع امتثال NIST AI RMF و ISO 42001 وقانون الذكاء الاصطناعي الأوروبي مرتبطة بالمتطلبات ذات الصلة • أمثلة عملية مستمدة من مهام تدقيق حقيقية مع مصادر موثوقة (Deloitte و IIA و ISACA و NIST) • أسئلة تقييم ذاتي للتدريب الفردي والجماعي • عرض تقديمي قابل للتعديل بالكامل (PPTX) – يمكنك تخصيصه بهوية مؤسستك
الفئة المستهدفة: المدققون الداخليون في مؤسسات الخليج والمنطقة العربية المستعدون لشهادات ISACA AAIA و CIA/CRMA، ومديرو التدقيق الذين يبنون قدرات فرقهم العربية في الذكاء الاصطناعي، ومدققو تقنية المعلومات الموسعون إلى تأكيد الذكاء الاصطناعي، ومتخصصو الحوكمة والمخاطر والامتثال الموسعون إلى مخاطر الذكاء الاصطناعي، وأقسام التدريب التي تقدم برامج تدقيق ذكاء اصطناعي ثنائية اللغة، ورؤساء المراجعة الذين يطورون وظائفهم للبيئة المُمكَّنة بالذكاء الاصطناعي.
لماذا هذه الوحدة: معظم محتوى تدريب تدقيق الذكاء الاصطناعي بالعربية إما مترجم من الإنجليزية دون تكييف الأمثلة والأطر للقارئ العربي، أو مبني على مراجع ذكاء اصطناعي متقادمة تفتقد NIST AI RMF و ISO 42001 وقانون الذكاء الاصطناعي الأوروبي. هذه الوحدة أصيلة لمشهد حوكمة الذكاء الاصطناعي الحالي، ومُنسَّقة احترافياً للقراءة من اليمين إلى اليسار، ومبنية بواسطة ممارس حاصل على CIA/CRMA/CFE مع 30+ سنة من قيادة التدقيق في الخليج والمنطقة وأوروبا والولايات المتحدة.
عن المؤلف: عامر مرجان، CIA، CRMA، CFE، مؤسس Business Excellence ومستشار أول قاد وظائف التدقيق الداخلي في مؤسسات حكومية وخاصة في قطر ودول الخليج والمنطقة وأوروبا والولايات المتحدة. ألَّف أكثر من 60 منشوراً مهنياً بالعربية والإنجليزية ودرَّب آلاف المدققين المهنيين في المنطقة.

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Source: Best Practices in Audit Management, Arabic PDF: AI Internal Audit M7 (Arabic): AI Ethics and Bias PDF (PDF) Document, Amer Morgan


$39.00
Crafted by Amer Morgan, a seasoned Senior Consultant with 30+ years in audit leadership across global entities, including profound engagements with Internal Audit, Risk Management, and Corporate Governance.
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Author: Amer Morgan
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Amer Morgan is the founder of Business Excellence, Audit Consultant and Governance Advisor with over 30 years of practice in internal audit, enterprise risk management, and corporate governance across Qatar, Egypt, the UAE, and the USA. He currently leads the internal audit function for a sovereign-wealth-fund-owned food security group in Doha, with responsibility for board-level assurance across ... [read more]

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