4: Ethical Issues with AI (Algorithmic Bias, Privacy, Copyright & Intellectual Property, Deepfakes, AI Safety & Governance) — البرمجة والذكاء الاصطناعي الصف الثاني الثانوي لغات

الدرس ده من وحدة «Principles of Algorithms and Computational Thinking» فى مادة البرمجة والذكاء الاصطناعي لـالصف الثاني الثانوي لغات على منصة دروسات.

الدرس متاح بالاشتراك: ترم كامل أو المادة لوحدها.

ملخص الدرس

This lesson critically examines the ethical, legal, and societal challenges surrounding artificial intelligence. It investigates algorithmic bias and historical data discrimination, personal privacy erosion, copyright controversies in generative models, the malicious weaponization of deepfakes and disinformation, the black-box opacity challenge, and international frameworks for AI safety, governance, and eXplainable AI (XAI).

هتتعلم إيه فى الدرس ده

• Algorithmic bias occurs when AI models amplify historical prejudices present in training datasets.
• Massive data collection for AI training raises acute privacy and consent concerns.
• Generative AI pre-training on copyrighted material sparks severe intellectual property disputes.
• Deepfakes threaten public trust through synthetic video, voice cloning, and disinformation.
• The 'Black Box' problem refers to the lack of interpretability in deep neural decisions.
• eXplainable AI (XAI) seeks to make AI reasoning transparent, auditable, and interpretable.
• Responsible AI frameworks enforce fairness, accountability, privacy, and human oversight.