Date Published: July 13, 2023 - Last Updated 71 Days, 8 Hours, 32 Minutes ago
A version of this article originally appeared in no jitter, a partner publication.
With the networking industry’s long-held fascination with shiny new objects, it is not surprising that contact centers have latched onto fledgling artificial intelligence (AI) technology with both hands. I have every reason to believe that AI will yield significant benefits in many areas, but at this stage, I can’t see any reason to believe that communicating effectively with human beings is not going to make that list of accomplishments anytime soon.
ChatGPT: A Machine to Produce Glib BS
The particular part of AI that the contact center industry has clutched to its breast is generative AI, specifically the generative pre-trained transformer (GPT) family of language models that use a probability distribution of word sequences to predict what word should come next. That’s the basis of how tools like ChatGPT work.
To be able to predict what word should come next in any context, these systems have to ingest enormous amounts of written material. To be clear, this is a “probability computation,” and has little to do with understanding what they’re talking about or the factual content of the words that are getting delivered. ChatGPT is just telling you which word will likely come next.
Once you understand what ChatGPT is trying to accomplish, its widely reported aberrant behavior becomes a predictable outcome.
Companies have a problem with customer service that confounds traditional solutions. Businesses have had enormous success in producing tremendous volumes of great physical products at price points that millions of people can afford. This cornucopia is the result of giant leaps in design and manufacturing technologies, all of which could be easily quantified by energetic MBAs.
However, this great engine of continuous improvement grinds to a halt when it comes to customer service. In manufacturing we can bend metal into any shape, integrate multiple functions onto a single chip and work with suppliers to build sophisticated subcomponents to reduce our manufacturing costs. Customer service involves communicating with people, understanding their issues, (despite language and vocabulary challenges) and then determining the best way to assist them.
Now, there is a rather obvious solution to this problem: you offer enough salary that you can hire smart people with above average communication skills, and then spend more money to train them in your products, how people use them, typical problems they encounter, and how to navigate your organization’s systems and resources to make those customers happy. Then we can use all the swell contact center monitoring tools we have to ensure the process is working. I have run into a few contact centers that have made such an investment, though those are typically businesses that are in the “service business.”
However, for most organizations it appears the obvious solution is off the table, so contact center managers embark on the romantic quest to use machines to solve the problem. Those attempts have included ideas like sending customers back to the company website (whose deficiencies were what got you to pick up the phone in the first place), interactive voice response (IVR) system (where most respondents are picking the “Other” option), or worse yet, conversational bots whose primary objective seems to be getting you to say words your mom told you not to say.
Maybe We Try Going Half-Way?
Like just about everyone in the tech industry, I love enormous leaps forward. Unfortunately, they don’t happen very often, and almost never without multiple missteps along the way. Maybe it’s time to stop trying to do the impossible and start with smaller steps to start moving the needle in the right direction.
For my money, the current generation of conversational bots fail at understanding how humans communicate. However, people very much like things to work. Maybe we should take a slow track on improving the machines and start focusing on improving people’s ability to work with the crummy systems we have. Specifically, we should develop a standard vocabulary for talking to our bots more effectively and start teaching people how to use it.
Businesses have enormous reach with mass media advertising, and we can use this vehicle to show customers how to interact with these systems using as few words as possible.
For anyone who might think this is impossible, just think of all of the myriad computer skills we have imparted to the general population who now routinely point-and-click, swipe right, pinch-and-spread to enlarge an image, and so on. Those people who agree with the premise that bots suck would gladly participate in any activity that might give them a chance at getting a problem resolved through the contact center.