An editor is using a generative AI application to summarize a document, however, the responses received from the application are not as expected. what should the editor do in this case?
If an editor is not receiving the expected responses from a generative AI application while summarizing a document, they may consider taking the following steps
Refine Input Instructions:
- Provide clearer and more specific instructions to the AI regarding the desired summary format, length, or key points.
- Experiment with different prompts to guide the AI towards the desired outcome.
Iterative Testing:
- Conduct iterative testing by making small adjustments to the input and reviewing the output. This process helps to understand how the AI responds to variations in input.
Check for Ambiguities:
- Ensure that the document or prompt given to the AI is clear and free from ambiguities. Ambiguous or unclear instructions may lead to unexpected responses.
Review Training Data:
- Understand the type of data the AI model has been trained on. If the training data is not aligned with the specific requirements of the document, the model may struggle to provide accurate summaries.
Post-Editing:
- After receiving the AI-generated summary, the editor can manually edit and refine the content to align it with the desired outcome. This hybrid approach combines AI assistance with human editing expertise.
Explore Alternative Models:
- Experiment with different generative AI models or applications. Different models may have varying strengths and weaknesses, and trying alternatives might yield more satisfactory results.
Provide Feedback:
- If the generative AI application allows, provide feedback on the generated summaries. This feedback can contribute to the improvement of the model over time.
Consult AI Guidelines:
- Refer to any guidelines or documentation provided by the AI application's developers. Understanding the limitations and best practices can help optimize the use of the tool.
Consider Expert Assistance:
- Consult with experts or professionals in the field of generative AI to gain insights into potential strategies for improving the quality of generated summaries.
