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--- public:t-709-aies-2025:aies-2025:principle_ai_ethics [2025/09/22 12:31] – leonard
+++ public:t-709-aies-2025:aies-2025:principle_ai_ethics [2025/09/22 12:41] (current) – leonard
@@ Line 112: / Line 112: @@
 |  Responsibility  | Still hard to make out who is responsible for the decisions made. |
 |  Privacy  | Anonymizing training data (challenging for large datasets). |
+==== Example ====
+=== ChatGPT ===
+  * Generative Pre-trained Transformer (GPT) is one of the largest LMMs.
+  * GPT-4 had 45 TB, GPT-5 even as much as 280 TB of (unfiltered) training data.
+  * GPT-4 roughly 1.7 trillion parameters. GPT-5 is estimated to have up to 5-10 trillion parameters (could be less than GPT-4, however, due to a possibly multi-model architecture. This is all unclear.).
+  * Up to 400,000 tokens context window.
+**Ethical issues**:
+  * Transparency: Very limited and it is unclear how some responses are generated.
+  * Justice and fairness: Use of ChatGPT may violate copyrights, etc.
+  * Safety: Generating harmful content, misinformation or being misused for unethical purposes.
+  * Responsibility: Who is responsible?
+  * Privacy: Massive amounts of data. Some training data can be extracted. See for example [[https://not-just-memorization.github.io/extracting-training-data-from-chatgpt.html| Extracting Training Data from ChatGPT]]