News Overview
- A real estate agent, Stephanie Soper, is supplementing her income by training AI models for companies like Scale AI.
- She earns between $50 to $200 per week training AI through various tasks, working around her schedule.
- This is part of a growing trend of individuals using AI training as a flexible side hustle.
🔗 Original article link: Real estate agent earning up to $200 a week training AI models describes the best and worst parts of the side hustle
In-Depth Analysis
- AI Training Tasks: Soper’s tasks include labeling images, writing text, and providing feedback to improve the accuracy of AI algorithms. This involves identifying objects in images, describing scenarios, and correcting AI-generated content.
- Flexibility and Accessibility: The key appeal lies in the flexibility. Soper can work whenever she has downtime, fitting it into her existing schedule. The tasks are generally simple and require minimal technical skills, making it accessible to a wide range of people.
- Platforms: The article mentions Scale AI as one platform offering AI training opportunities. Other platforms like Amazon Mechanical Turk, Appen, and Lionbridge also provide similar opportunities.
- Earnings: The earnings vary depending on the task and the platform. Soper’s earnings range from $50 to $200 per week. This highlights the potential for supplemental income rather than a full-time replacement.
- Pros and Cons: Soper mentions the convenience and flexibility as major advantages. However, she also points out that some tasks can be monotonous and that pay rates can fluctuate.
Commentary
The rise of AI training as a side hustle reflects the increasing demand for human-in-the-loop AI development. While the income isn’t substantial enough to replace a full-time job for most, the flexibility and accessibility make it an attractive option for individuals looking to supplement their income. The market for these tasks is likely to grow alongside the continued development and deployment of AI systems. However, concerns around fair wages and the potential for repetitive, low-skill work should be addressed to ensure a sustainable and ethical future for this emerging gig economy sector. The reliance on platforms also introduces a degree of volatility and dependency on the task supply from those platforms.