Navigating Language Services: A Cautionary Note on ChatGPT Reliability
Although my current title says Founder and President of Karaman Language Solutions, I am still a Linguist at heart. While I work on the business the linguist in me can’t help but get involved in the business. In one of those moments, I got the opportunity to test ChatGPT’s reliability and accuracy as a transcription proofreader.
In the dynamic field of language services, a discerning evaluation of reliability and accuracy is paramount. While ChatGPT showcases intriguing technology, it is pivotal to acknowledge its present limitations in delivering robust language services.
The Case: I wanted to see if ChatGPT could eliminate the need for a human proofreader and cut down proofreading time, therefore increasing profitability and efficiency for a transcription assignment.
In order to test ChatGPT’s transcription proofreading skills, I took the raw transcription generated by another AI software and posted it to ChatGPT with a series of instructions.
I gave ChatGPT clear and brief instructions about spelling, capitalization, and punctuation. I also asked it to remove timestamps and make the text ready for subtitling with additional commands.
What happened?
ChatGPT failed miserably. Since the raw transcription text was too long, I had to break it down into chunks manageable by ChatGPT. For the first few entries, ChatGPT maintained strict adherence to my previously set rules and created the desired outcome in seconds. However, as I kept posting more chunks of text, it started to put out subpar results.
The subpar results included ChatGPT grossly deviating from the set of rules I had set for proofreading. ChatGPT took the liberty to paraphrase some sentences, omit words, and shorten some sentences arbitrarily. It also followed some rules while ignoring others.
The Challenge: ChatGPT, at its current state, based on these series of experiments may not be the optimal solution for critical language services, given its inherent challenges in grasping nuanced language interpretation and contextual understanding. Especially for transcription services, every utterance matters in communication and the transcriber or the proofreader should never have the authority to make any additions or omissions while working on the text. However, ChatGPT was inconsistent and unreliable in its output. If ChatGPT was my employee, s/he would have been fired on the spot.
The Technological Landscape: This observation underscores the ongoing debate about the efficacy of fully relying on artificial intelligence for intricate language tasks, especially in scenarios where cultural context and subtle nuances are imperative. Can we wholly entrust intricate language tasks to artificial intelligence? Particularly, when the terrain demands an acute understanding of cultural context and the subtle hues of human expression.
A Call for Evaluation: In this era of technological evolution, it's essential for professionals in the language services domain to critically evaluate the reliability of tools and solutions, considering the specific demands of each project.
Takeaway: ChatGPT, currently grapples with limitations in delivering the robustness required for critical language services. Always exercise discernment in technological choices. As language professionals, our commitment is to remain vigilant in understanding the evolving landscape and ensuring reliability in every language service rendered.
3 Recommendations:
Integration with Existing Systems: ChatGPT must undergo integration with current systems and processes. Currently, it does not render accurate or reliable outcomes. Trained language professionals have to be a part of the translation or transcription process to ensure quality.
Training and Retraining of the Model: Achieving accurate translations with ChatGPT necessitates specific language and subject area training. This undertaking demands the allocation of time and resources, with the model potentially requiring periodic retraining to adapt to new data and language patterns.
Maintenance and Updating of the Model: As a complex system, ChatGPT requires continuous maintenance and updates to ensure ongoing accuracy and relevance. Consistent efforts are essential to keep the model up-to-date.