<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Transparency on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/transparency/</link><description>Recent content in Transparency on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Wed, 11 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/transparency/index.xml" rel="self" type="application/rss+xml"/><item><title>Chapter 12: Ethical Implications, Privacy, and Responsible AI in Face Biometrics</title><link>https://ai-blog.noorshomelab.dev/uniface-biometrics-guide-2026/ethics-privacy-responsible-ai/</link><pubDate>Wed, 11 Mar 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/uniface-biometrics-guide-2026/ethics-privacy-responsible-ai/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;Welcome to Chapter 12! As we&amp;rsquo;ve explored the incredible capabilities of the UniFace toolkit for advanced face biometrics, it&amp;rsquo;s crucial to acknowledge that with great power comes great responsibility. Face biometrics, while offering immense potential for convenience and security, also sits at the intersection of deeply personal data and powerful AI. This makes understanding its ethical implications, privacy challenges, and the principles of responsible AI not just important, but absolutely essential for any developer.&lt;/p&gt;</description></item><item><title>AI Ethics: Thinking About What&amp;#39;s Right</title><link>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/thinking-about-ai-ethics/</link><pubDate>Sun, 18 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/thinking-about-ai-ethics/</guid><description>&lt;h2 id="welcome-to-chapter-15-ai-ethics-thinking-about-whats-right"&gt;Welcome to Chapter 15: AI Ethics: Thinking About What&amp;rsquo;s Right!&lt;/h2&gt;
&lt;p&gt;Hello, future AI explorer! You&amp;rsquo;ve come so far, learning about what Artificial Intelligence (AI) and Machine Learning (ML) are, how they learn from data, and how they make predictions. That&amp;rsquo;s fantastic progress!&lt;/p&gt;
&lt;p&gt;Today, we&amp;rsquo;re going to shift gears a little. Instead of focusing on &lt;em&gt;how&lt;/em&gt; AI works, we&amp;rsquo;re going to think about &lt;em&gt;should&lt;/em&gt; AI work in certain ways. This might sound a bit abstract, but it&amp;rsquo;s incredibly important. Just like a powerful tool can be used for amazing things, it can also cause problems if we&amp;rsquo;re not careful. AI is one of the most powerful tools humanity has ever created, and with great power comes great responsibility!&lt;/p&gt;</description></item><item><title>Chapter 17: Ethical Considerations and Responsible AI in Post-Training</title><link>https://ai-blog.noorshomelab.dev/tunix-mastery-2026/17-ethical-ai/</link><pubDate>Fri, 30 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/tunix-mastery-2026/17-ethical-ai/</guid><description>&lt;h2 id="chapter-17-ethical-considerations-and-responsible-ai-in-post-training"&gt;Chapter 17: Ethical Considerations and Responsible AI in Post-Training&lt;/h2&gt;
&lt;p&gt;Welcome to Chapter 17! So far, we&amp;rsquo;ve explored the immense power of Tunix for fine-tuning Large Language Models (LLMs), optimizing their performance, and tailoring them for specific tasks. As we wield such powerful tools, it&amp;rsquo;s crucial to pause and consider the broader impact of the AI systems we build. This chapter shifts our focus from pure technical implementation to the vital domain of ethical considerations and responsible AI in the post-training lifecycle.&lt;/p&gt;</description></item></channel></rss>