In this article, the author discusses several key questions and themes related to Generative AI. They express frustration with the lack of documentation and tutorials provided by companies building and releasing Large Language Models (LLMs). The author emphasizes that AI detectors claiming to detect AI writing are ineffective, as they can be easily defeated and have high false positive rates. The use of AI in detecting cheating in education is also addressed, highlighting the challenges faced by teachers and the need for adaptation in assessment methods. The article then explores the best ways to use AI and recommends accessing advanced Large Language Models like OpenAI’s GPT-4 for various tasks. Privacy concerns and copyright issues related to AI are discussed, along with the uncertainty surrounding the future development and capabilities of AI.
| Signal | Change | 10y horizon | Driving force |
|---|---|---|---|
| AI detectors for writing and images | Detection accuracy and reliability | Improved AI detection technology and methods | Desire for fairness and accuracy in detecting AI usage |
| Utility and application of AI | Finding optimal use of AI in work | Increased understanding and expertise in AI utilization | Experience and experimentation with AI tools |
| Data privacy concerns with AI | Addressing data security in AI usage | Improved privacy options and guarantees for AI users | Desire for data protection and ethical AI practices |
| Copyright and AI | Navigating copyright rules for AI-generated content | Clarification and legal safeguards for commercial use of AI outputs | Ensuring legal and ethical use of AI-generated content |
| Advancement of AI models | Progress in AI model performance | Continued improvement and innovation in AI models | Technical, economic, and regulatory factors driving AI development |