OpenAI released to the publicChatGPTAs we near the end of the year, adoption has surged like never before. As of February 2023, Reuters reported that ChatGPT had approximately 100 million active users. Fast forward to September, and the ChatGPT website has attracted nearly 1.5 billion visitors, demonstrating the platform’s immense popularity and important role in today’s digital landscape.PBT GroupCTO Willem Conradie reflected on this journey, noting ChatGPT’s significant usage and adoption across industries.
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The rise of ChatGPT has highlighted a range of important issues, ranging from output bias, question misunderstanding, inconsistent answers, lack of empathy to safety issues. In response to these issues, the concept of responsible AI has gradually become dominant, emphasizing that it is important to have fair, inclusive, safe, transparent, accountable and ethical intentions when applying artificial intelligence. Responsible AI is particularly important when dealing with false information, as ChatGPT may provide inaccurate or outdated information.
Of course, ChatGPT’s versatility is not limited to public use; it is also a powerful tool in enterprise environments, enhancing a variety of business processes such as customer service inquiries, email drafting, personal assistant tasks, keyword searches, and presentation production.optimalPerformance, it is crucial for ChatGPT to provide accurate responses. This requires training on data that is not only relevant to the company but also accurate and timely.
“Imagine ChatGPT being used to automate the processing of customer queries to improve the customer experience by providing personalized responses,” Conradie noted. “If the underlying data quality is compromised, ChatGPT could provide inaccurate responses, from mistaking the customer’s name to providing incorrect self-service guidance on the company’s mobile app. These inaccuracies could lead to customer frustration, ultimately harming the customer experience and defeating the intended positive outcome.”
Addressing these data quality issues is critical. Ensuring that relevance isFirstThe first step is to ensure that the data used for model training is consistent with the business context in which ChatGPT operates. Timeliness is another key factor, as outdated data can lead to inaccurate responses. The data must also be complete, ensuring that the dataset does not contain missing values, duplicates, or irrelevant entries, as these can also lead to inaccurate responses and behaviors.
In addition, it is crucial to incorporate user feedback into the model retraining cycle to continuously improve the model through reinforcement learning. This helps ChatGPT as wellConversational AI ModelThe whole learns from their interactions, adapting and improving the quality of its responses over time.
Conradie concluded: “The data quality management practices highlighted in this article, while not exhaustive, serve as a practical starting point. These apply not only to ChatGPT, but also to conversational AI and other AI applications such as generative AI. All of this highlights the importance of data quality in the field of AI technology.”