The question of whether opting out of AI training reduces one's influence on the technology is a complex one. On one hand, individual data is just a small part of a vast dataset, and its removal may not significantly impact the model's behavior. On the other hand, subject matter experts' unique insights and perspectives can be valuable to AI researchers, and their opt-out decision may have a greater impact.

Moreover, the current opt-out processes are often futile, as startups and other companies may still scrape data from various sources, including social media platforms. This means that even if an individual opts out, their data may still be used to train AI models.

Furthermore, the influence of individual data on AI models is not just about the data itself, but also about the context in which it is used. AI models are often fine-tuned and refined through a process of human labeling and feedback, which can further abstract the data and reduce the impact of individual contributions.

However, it is also possible to view individual data as having a similar impact to a vote in an election. Just as every vote matters, every piece of data can contribute to the overall behavior of the AI model. This perspective suggests that opting out of AI training may still have an impact, even if it is a small one.

In conclusion, the impact of opting out of AI training on personal influence is a nuanced and complex issue. While individual data may be a small part of a larger dataset, it can still have an impact, especially for subject matter experts. Ultimately, the decision to opt out of AI training should be based on a careful consideration of the potential benefits and drawbacks.