Chatbots and the Corporate Dream
Feb. 02, 2024.
4 min. read. Interactions
Explore the looming future where 90% of customer service jobs could be taken over by bots, transforming interactions with corporations. Is the convenience worth the sacrifice of human nuance?
Hello! How can I help you today?
Visit almost any modern company website – retail, health, service, or other – and you will see this pop up. An invitation to their world. You click, type in your question, and three possible things happen:
- Thank you for your question! A customer service representative will respond with 24 hours
- Did you mean – How to install your new Christmas lights?
Or possibly, nowadays:
- Hi James! I’m Xmasbot. Installing Christmas lights is really easy….
It’s this third option which is so tantalising a prospect for corpos. Customer service is expensive. Execs the world over are rubbing their hands in glee at the prospect of ripping out the expensive bureaucracy of customer-facing support and replacing it entirely with LLM-generated responses. It is predicted that 90% of all customer service jobs will be done by bots eventually. For pleasure-buying, it makes sense, but for services – the future is more scary.
It’s true that the current system of customer support has created frustration for millions, especially when it comes to essential services. Essential services barricade themselves behind bureaucratic labyrinths. It’s almost like they don’t want to really help and, the sad fact is, for some services – like internet, gas, electric, tax – they don’t. Your presence is nothing but a fiscal drag on their bottom line. Pay your bill and beat it.
Customer service roles like this operate formulaically, with off-shore workers fielding calls and responding to a template. A situation which has frustrated customers for decades, when the person they are speaking to hasn’t the faintest idea how the company they work for works – and may even be moonlighting for multiple companies operating out of one giant call centre – and are unable to offer anything more than what you read on the FAQs.
For decades, companies have desperately tried to encourage customers to use online portals. ‘Can’t find what you need online? Give us a call…’. Then you’re waiting for hours in a queue, only to talk to someone who reads the FAQs at you, and blithely reads out some asinine apology based on the severity of your complaints.
In this climate, the idea of talking to a chatbot instead may actually appeal. A well-integrated, sophisticated, amiable chatbot with the power to execute simple commands (refunds etc.) would be a boon. No more waiting around to get through. Response and action on your complaint or needs would be instant, and customer interaction might be superior too.
It’s becoming ever more likely that this will be one of the first widespread everyday applications of generative AI: the area where the strengths of LLMs converge with a business need. Just as companies once tried to move customer service to option-selecting software that scans your responses, now they might move to LLMs. To do this, LLMs would need to be hooked up to the appropriate data, and know when to give specific information. It’s not plug and play, but it’ll soon be close enough that the majority of your interactions with companies will be mediated through ChatGPT or equivalent.
And this is the dark side of AI progress, the increasingly darker mirror wall erected between us and the systems that rule our lives. The ever greater alienation between ourselves and the rest of the world. The fact that, as is already the case with some large service companies, it will be the computer that says no. Gas metre charging you incorrectly? Well, I’m sorry, but GasGPT doesn’t think so – and there is nothing you can do to change its mind, ever.
There is no place for nuance in a world where our interactions are defined through LLMs who are only using the past to decide the present – a place where no one is really listening. Your complaints are just being chewed through the machine, and spat out at the least possible cost to the bottom line.
Of course, this is what is happening already, but through GPT models, the brute, abstracted efficiency moves it from today’s Kafkan dystopia of weaponised incompetence to something altogether more chilling: a world where your interactions with the machine decide your fate, bargaining with a techno-agent who feels only the numbers it achieves.