Risks and Strategies to Use Generative AI in Software Development
"Generative AI is a powerful tool that can revolutionize software development, but it's important to be aware of the risks involved before you use it," says Muddu Sudhakar, Co-founder & CEO of Aisera.
Here are some of the risks of using generative AI in software development:
Lack of transparency: Generative AI models are often opaque, meaning it can be difficult to understand how they work and why they generate the output they do. This can make it difficult to debug problems and ensure that the code generated is safe and secure.
Accuracy: Generative AI models are still under development, and they can sometimes make mistakes. This can lead to bugs in the code they generate, which can cause problems for users.
Bias: Generative AI models can be biased, meaning they may generate code that reflects the biases of the data they were trained on. This can lead to problems if the code is used in a sensitive application, such as one that handles financial transactions or personal data.
Intellectual property (IP) and copyright: Generative AI models can generate code that infringes on the IP or copyright of others. This can lead to legal problems for the company that uses the code.
Despite these risks, generative AI can be a powerful tool for software development if it is used carefully. Here are some strategies for mitigating the risks of generative AI:
Use a reputable generative AI model: There are a number of reputable generative AI models available, such as OpenAI's GPT-3 and Google's LaMDA. These models have been trained on large amounts of data and are less likely to make mistakes.
Test the code generated by generative AI: It is important to test the code generated by generative AI thoroughly before it is used in production. This will help to identify any bugs or security vulnerabilities.
Use generative AI for specific tasks: Generative AI is not a silver bullet for software development. It is best used for specific tasks, such as generating code for repetitive or low-level tasks.
Monitor the use of generative AI: It is important to monitor the use of generative AI in your organization to ensure that it is being used safely and responsibly. This includes tracking the code generated by generative AI and investigating any potential problems.
By following these strategies, you can mitigate the risks of generative AI and use it to your advantage in software development.