Future of Code with Generative AI: Transparency and Safety in the Era of AI Generated Software
It tackles safety and transparency issues in AI-generated software for software engineering and AI ethics, but is incremental as it reviews and proposes rather than introduces new methods.
This study addresses the need for transparency and safety in AI-generated code by analyzing risks, market opportunities for detection, and proposing solutions to enhance functionality analysis, while investigating long-term implications like AGI development and human-AI interaction.
As artificial intelligence becomes increasingly integrated into software development processes, the prevalence and sophistication of AI-generated code continue to expand rapidly. This study addresses the critical need for transparency and safety in AI generated code by examining the current landscape, identifying potential risks, and exploring future implications. We analyze market opportunities for detecting AI-generated code, discuss the challenges associated with managing increasing complexity, and propose solutions to enhance transparency and functionality analysis. Furthermore, this study investigates the longterm implications of AI generated code, including its potential role in the development of artificial general intelligence and its impact on human AI interaction. In conclusion, we emphasize the importance of proactive measures for ensuring the responsible development and deployment of AI in software engineering.