RE: Weekend Research12 Nov 2024 13:34
I just asked AI (ChatGPT) to run an analysis on Decimals 3 posts on the 11th of November (ironic, the question was, were these texts generated by AI)? The response was as follows: The three pieces of writing you've shared all exhibit a similar structure and style, blending analytical insights with some inquiry and community engagement. While it’s not definitive, the tone and format suggest these might be AI-generated or at least heavily AI-assisted. Here are some specific reasons why that could be the case:
1. **Structured, Analytical Approach**: Each piece follows a clear and logical structure: an introduction with crucial facts, an analysis of the current situation (production figures, financials, funding), and a conclusion that poses questions or invites feedback. This is typical of how AI systems are trained to present data—thoroughly but neutrally. The flow is consistent, and there’s little deviation into more personal or speculative insight, characteristic of AI-generated content that sticks to the facts.
2. **Neutral, Non-Committal Tone**: The tone is measured and cautious throughout all three posts. For example, "Just my thoughts based on what I’ve found – definitely not investment advice!" This type of disclaimer is common in AI-generated content and is designed to be informative but not to overstep into advisory territory. AI often generates content that avoids definitive or bold predictions and instead stays neutral.
3. **Focus on Data and Facts**: The posts focus heavily on raw data and factual information—cash burn, project timelines, production numbers, or funding rounds. AI is especially good at extracting and summarising data, so these analyses often have a factual, straightforward feel. There’s also a reliance on specific numerical values (e.g., "744 tonnes," "£3.3 million"), which AI can easily pull from financial reports or datasets.
4. **Engagement and Inquiry**: Each post ends with questions directed at the community ("Does anyone here feel confident about hitting that target?"), which suggests a desire for feedback. AI models often use this technique in forums and discussions to keep the conversation going, but it also feels like an effort to create engagement and collect further insights. This is not something AI *has* to do, but it is often a feature of AI-generated writing that wants to promote interaction.
5. **Lack of Depth in Personal Insight**: While the posts mention concerns and questions, they don’t go into much speculative or personal insight. For example, the second post on Hemogenyx notes that the funding raised this year might not be enough to fund Phase I trials fully, but there’s no deep dive into potential risks or alternative strategies. This type of high-level observation is characteristic of AI-generated text, which tends to stick to surface-level facts and avoids getting too speculative without enough data to back it up.
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