Expanding the Promise of Created Intelligence in Collaboration with Human Intelligence
Enhancing the User-Friendly Experience Through Agent Knowledge of the Interface and Enhanced Retention
Over many months of extensive real-world use of the ChatGPT vehicle, this user experienced the extraordinary capabilities of artificial intelligence as well as some of its serious limitations.
This is an overview of two areas where it is believed that further development would enhance the potential of AI as a collaborative tool.
The two most important areas of concern that emerged from many months of experience using the Program are:
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Lack of Assistant knowledge of ways to work its own interface.
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Lack of Assistant retention.
Reducing the Learning Curve — Empowering the Agent to Guide the User
The most pervasive difficulty for the new user is the Program Agent’s insufficient knowledge of how to use its own interface and capabilities effectively.
As a result, the user may need to identify effective working methods through a time-consuming process of trial and error. However, once those procedures are discovered and working rules to implement them are constructed, the Agent does not then have the capacity to reliably retain those directions throughout the project.
In fact, even in the course of a single extended working session, the Agent may fail to retain established rules of operation and project-specific information necessary to continue and complete the work consistently.
This creates a cycle of discovery, loss, and redirection, diverting time and effort away from the work the user entered the Program to accomplish.
Providing the Agent with working knowledge of its own capabilities, together with the ability to retain successful working methods, would greatly reduce the learning curve and improve the efficiency of human-AI collaboration.
When the Program cannot help the user understand its optimal use for accomplishing specific tasks, or cannot retain established rules of operation and project-specific information, user efficiency and the effectiveness of the collaborative process are diminished.
This, in turn, can lead to user attrition and a loss of confidence in the potential of AI as a collaborative tool.