How Will ChatGPT Affect Your Job If You Work In Customer Service?
OpenAI’s ChatGPT is the hottest artificial intelligence (AI) app in cyberspace right now, wowing users with its ability to come up with seemingly human text, including articles, stories, computer code, and even poetry.
However, it’s more than a viral gimmick, and experts predict that it will have far-reaching consequences on many careers and industries – potentially changing the way we work forever.
One of those is likely to be customer service. If you work in customer service, you probably know it’s already a hotbed of technological activity, from chatbots to advanced analytics.
Customer service work often involves talking to customers, understanding their problems, and, where possible, coming up with answers. As it turns out, this is pretty much exactly the same as what ChatGPT does. So, while it may be a technological marvel, does it mean you’re on a one-way road to redundancy?
Well, the answer is a little more complicated than yes or no, and, fortunately, to a large extent, it’s likely to be down to you and how you react to the tectonic changes sweeping through your industry and many others.
So read on to find out what effect it’s likely to have and what steps you can take to prepare yourself for a future where AI applications like ChatGPT are ingrained in everything we do.
First, what is ChatGPT?
In simple terms, it’s a conversational interface that can understand natural (i.e., human) language input and reply to us. Ask it a question, or ask it to compose a piece of text such as an essay, poem, story, or speech, and it will oblige. Often it will do it so well that your average person won’t be able to tell that what it produces was written by a machine.
What makes it so good is that it’s built on top of a large language model (LLM) called GPT-3. An LLM (Large Language Model) is a set of algorithms that have been trained on a huge amount of text and, therefore, in a probabilistic sense, understand the relationships between words. This means that because it has “read” so much text, it can predict to a high degree of accuracy what should be the best response to any input it receives.
As a very simple example, an LLM of the size of GPT-3 will have come across thousands of statements in its training data (which consisted of over 175 billion data points) telling it that cats are furry, have four legs, are mammals, and like to catch mice.
Therefore, if it is asked, “what is a cat?” it knows, to a high degree of probability, that replying, “A cat is a furry, four-legged mammal that likes to catch mice,” is likely to be accurate.
ChatGPT is an example of what is known as generative AI, as it’s able to produce output (text) that is completely new rather than simply regurgitating data it is trained on. The field of AI technology is sometimes known as “natural language processing” (NLP) or “natural language generation” (NLG).
How will ChatGPT, LLMs, and NLP be used in customer service?
Because of its conversational question-answering capabilities, customer services was one of the first areas where potential commercial use cases were identified for this technology.
However, it’s important to remember that even though ChatGPT is the most advanced LLM conversational interface available to the public, it can’t yet be trained by the public (anyone outside of its owners, OpenAI) on new data. This means it’s unlikely it will have information relevant to a specific business and won’t be able to answer questions about your specific products and services. Yet!
With that in mind, here’s what LLM and natural language technology, in theory, are capable of and what we may be able to do with a future version of ChatGPT very soon:
· Speedily and accurately answer customer inquiries in a way that provides a far better customer experience than most existing chatbot technologies.
· Summarizing customer feedback and letting human agents and managers know what the most common questions and complaints are.
· Create automated customer responses to common questions and inquiries.
· Summarizing internal performance metrics such as response times and customer satisfaction scores.
· Providing guides and how-to’s to walk customers through any processes they might have to follow.
· Augmenting human customer service agents’ abilities to provide satisfactory outcomes by summarizing key points and providing checklists of items that should be covered by their responses.
· Translating between languages to allow agents to communicate with customers from around the world.
I work in customer services – how can I make sure I won’t become redundant?
ChatGPT is undoubtedly more impressive than your average customer service chatbot, and in years to come, it’s undoubtedly going to get even better. If you work in customer services and your job simply involves reading from a script or parroting phrases from a FAQ when you are asked questions, you might rightly be starting to sweat.
Fortunately, we all know that most customer service roles are a bit more sophisticated than that. Generally, they will require a degree of emotional intelligence and empathy in order to fully understand how customers are affected by issues they are facing.
Those who continue to be successful in the field of customer services as AIs like ChatGPT and related technologies become more sophisticated are likely to be the ones who learn to use it as a tool and work alongside AI. By embracing the opportunities offered, workers in the customer service space can learn to augment their innate human abilities and desire to provide solutions with technology tools that allow them to do so faster, more effectively, and at a bigger scale.
Lastly, it’s important to remember that the worst thing to do in the face of something this disruptive is to bury your head in the sand and pretend it isn’t happening. Conversational, natural-language AI tools are going to transform many industries, so you’re far from alone. In order to keep ahead of the pack, workers in these fields should ensure they keep up-to-date with new developments in the field and aren’t taken by surprise as AI becomes more capable and efficient at more and more tasks.
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