Gen AI Code Assistants in Software Development

Generative Artificial Intelligence (Gen AI) is taking the world by storm and revolutionizing global industries. The widespread adoption of OpenAI's ChatGPT has underscored the technology's capabilities, enhancing operational efficiency and elevating employee satisfaction, particularly in software development. Nonetheless, the question remains: is Gen AI truly a rose without thorns?  

Research shows that Gen AI tools can reduce the time required for less complex tasks by up to 50%, enabling employees to focus on more critical chores. However, there are some risks related to confidentiality, intellectual property rights, and data security. To effectively navigate these challenges, it is essential to meticulously select the appropriate tools, guarantee their correct configuration, and provide comprehensive training for the workforce. Combining this knowledge with the requirements of your organization can lead to a thorough and powerful Gen AI strategy. 

Risks associated with Generative AI usage 

The incorporation of Gen AI technologies into software development poses substantial security and data privacy challenges, which can be classified into four core areas: 

1. Output quality concerns: Gen AI tools may inadvertently produce inaccurate or fabricated information, propagate existing biases from their training datasets, or generate recommendations based on obsolete models, thereby rendering the outputs irrelevant.
2. Data security and confidentiality: The level of data protection varies by provider. Depending on the tool's license and configuration, user inputs may be utilized for further model training. There is a non-zero risk that if the tool is not configured correctly, such user inputs could be incorporated into a response to other users' queries.
3. Risk of Intellectual Property Rights Infringement: Code-generation models are trained using a broad set of open-source repositories, encompassing both permissive and non-permissive licenses. Utilizing code under restrictive licenses (e.g., the General Public License) could lead to severe legal consequences and financial liabilities. Generative AI tool providers adopt diverse strategies to protect users from such infringement claims. These include both built-in detection filters and the offering of indemnification, sometimes without a cap on damages liability.
4. Intellectual Property Rights to Gen AI outputs: The question of whether an artificial entity can be recognized as the author of its generated output, and thus possess intellectual property rights over it, remains unsettled. Current legislative frameworks lack clear guidelines on this matter. Consequently, service providers typically only transfer ownership rights or offer their users a non-exclusive, perpetual, and royalty-free license to use the generated content. 

Xebia’s research on code-generating tools 

Xebia researchers have meticulously evaluated the landscape of Generative AI code assistants, conducting a comprehensive review of their documentation, privacy policies, and terms of service, and prepared the whitepaper "State of Generative AI - Code Assistants in Software Development," summarizing our findings.

Our analysis focused on the methodologies employed by various providers in handling sensitive data, with a particular emphasis on ensuring the confidentiality of proprietary information during data transmission and processing. Additionally, we scrutinized the intellectual property rights pertaining to the output generated by these tools. Another critical aspect of our assessment was the extent to which Gen AI assistant providers are prepared to protect their clients from third-party claims, including an evaluation of the legal support provided and the limitations on liability. The tools subjected to a detailed examination are: 

• Amazon CodeWhisperer Professional 
• GitHub Copilot Business 
• Tabnine Pro 
• ChatGPT Team 
  

Free tiers and plans of Generative AI tools have been excluded from further consideration due to their non-compliance with fundamental confidentiality standards. Crucially, these complimentary licenses employ input data to enhance the training of vendors' models, raising significant concerns regarding data privacy and security. 

Dive deeper into the transformative world of Gen AI with our latest whitepaper 

In the whitepaper "State of Generative AI - Code Assistants in Software Development," we unveil Xebia's insights and recommendations for the safe adoption of Generative AI. We highlight the most favored strategies for their deployment, based on which we have enacted our internal guidelines and policies. This whitepaper helps you integrate new tools efficiently and securely into your workflow. It also delineates the benefits and examines the pros and cons of each professional tool evaluated.

Get your copy of the whitepaper now and take the first step towards future-proofing your software development processes.