# The Development of an OpenAI-Based Solution for Decision-Making
## 2 Materials and Methods
### Real-Time AI Decision Support
#### 2.7.3 Clarification of Blockchain Implementation: Why PoA over PoS?
Similarly, users can create or join organizations, assign tasks, and manage group decisions. This feature helps with collaborative decision-making. The backend also helps to manage OpenAI API calls, blockchain interactions, and the users of the application. It is developed by using Node.js and Python (Flask/Django) and it ensures that there is secure API communication along with effective task management. The backend also uses the Microsoft SQL Server where the decision and user data are stored. Key backend processes include the decision-making process, task management, and organization creation. The backend is also structured in a way that it can securely handle the requests from the users, store their data, and improve communication with blockchain and OpenAI systems. The backend helps to create and assign the tasks in the organizations, thus helping to properly authenticate the users before task delegation. Similarly, backend processes for user profile management include validating image uploads, updating the profiles, and handling the data in a secure manner. Furthermore, to have robust security, the platform has layers of validation and encryption so that only authentic users can use the system. The frontend and backend interactions are protected by HTTPS, and the user passwords are encrypted through bcrypt library. In order to ensure that only authenticated users can use the system, token-based authentication is implemented; thus, access to sensitive features is protected. Error handling features are built into the system to provide users with clear feedback and guidance; for example, there is a system to address any incorrect code entries during registration or voting errors. Data To Store in Blockchain: To store decision records (Table 3) on the blockchain, we hash the data and store the hash (not the raw data) on the chain. This ensures data integrity while minimizing blockchain costs. \begin{table}
\begin{tabular}{l l l} \hline \hline \multicolumn{1}{c}{**Field**} & \multicolumn{1}{c}{**Type**} & \multicolumn{1}{c}{**Description**} \\ \hline id & int & \begin{tabular}{l} Unique identifier for the decision \\ (auto-incremented). \\ \end{tabular} \\ \hline ownerID & int & ID of the user/owner who created the decision. \\ \hline Type & \begin{tabular}{l} varchar(50) \\ \end{tabular} & Type of decision (e.g., “approval”, “rejection”, “review”). \\ \hline Slug & \begin{tabular}{l} varchar(255) \\ \end{tabular} & \begin{tabular}{l} URL-friendly unique identifier for the decision (e.g., approval-2023). \\ \end{tabular} \\ \hline Status & \
\begin{tabular}{l} varchar(50) \\ \end{tabular} & Current status (default: initiation). Possible values: completed, pending, canceled. \\ \hline Text &
\begin{tabular}{l} varchar(2048) \\ \end{tabular} & Detailed description or notes about the decision. \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Decision records. Using the aforementioned methods, the application was used in an organization called DADWORD IT, which is a mid-sized organization with 12 dedicated employees. As part of adapting to the evolving work environment, the company sought to establish an effective Work-From-Home (WFH) policy that accommodates the needs and preferences of its team members. To facilitate them, the current app was utilized to ensure a collaborative and transparent decision-making process.