15 ways conversation designers could use ChatGPT
Kane Simms
Conversational AI and CX Transformation ?? Strategic Consultancy ??? Podcast ?? Thought-leadership ?? Events
People from all industries and professions have gotten a hold of ChatGPT and have begun to understand the potential power of NLP technologies. In the field of conversational AI, for obvious reasons, there’s been a LOT of talk about whether a future version of ChatGPT would negate the need for conversation designers.
The reactions from the conversational AI community could broadly be placed into two camps:
There’s no need for either yet. You can keep your underwear on. And it’s right that we should be divided right now, because we really don’t know where this thing will go, how (if) it’ll be used in production enterprise use cases and how it will realistically affect what we do.
But we can speculate, based on what’s in front of us, the ways in which we could use ChatGPT to improve the practice of conversation design and development.
So how might you use it? How can we avoid mindless bots who say the absolutely wrong thing at the wrong time, purely because they weren't designed properly?
Perhaps we're about to have another "I got scammed - great!" moment when someone applies this new technology without really considering how it will work in the wild lands of the real world.
We need to keep our heads (and underwear) on, and think realistically about how we can use this.
Here's 15 ways ChatGPT (and LLMs) could help you build better bots
Something to note before we get into this list. This list was written 3 days after ChatGPT launched. It's taken us a little while to get this post out. At the time of writing, the below were simply ideas. Since then, the great team at Voiceflow has actually implemented a number of these things already in its recently announced AI Assist! Kudos to them.
2. Simulate a conversation between various parties. How might famous personas speak about specific subjects? This could be used as a reference in persona design.
3. Enhance a fictional persona. With a short prompt, ChatGPT can add a lot of wonderfully on-topic detail.
4. Intent training. Ask it to list the different ways a user can say ‘I don’t know’ and you’ll get plenty of training data. Voiceflow has actually recently implemented this.
Beware of the risks though. There are some caveats here because someone might say “I’ve lost my bank card”, which may trigger a ‘freeze’ card’ followed by an ‘order replacement card’ intent. Simply asking ChatGPT to generate ways to say “Can you freeze my bank card” will miss those other alternative ways of triggering the intent. Therefore, we’ll still need real customer data to balance this.
5. Entity generation. 'Give me 50 words that mean the same as house’ or ‘list 50 different pizza toppings’. Another Voiceflow recently implemented.
6. Training and quality assurance. How about having it generate test cases? Ask it for test questions that aren’t in your training data to test your language model.
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7. Prompt writing. How best to ask x question? Check out this example of someone who used it to generate prompts to feed into MidJourney and create AI art.
8. Prompt variations. Random prompts that mean the same thing but keep the conversation dynamic, or are specialised for specific customers. Another that Voiceflow has recently implemented.
9. Localisation. Create multi-language conversational designs before sending them to the loc department. chatGPT covers more languages than English. chatGPT’s first attempt should be conversational in any language (at least, it should be better than simply Google translating the source version), so your loc team’s starting point should be a higher quality localisation which will save them time
10. Beating writer’s block.?ChatGPT is an idea generator. If you simply want to try out an idea rapidly (‘what if we rap this sales copy?’), then ChatGPT will let you try that idea very quickly so you can decide if it’s a winner or a binner.
In the future, there's potential for this thing to be able to do:
Of course, the practical limitations to this today is that LLMs including ChatGPT still have the potential to turn racist and say something that’s abusive or generally not in line with how you’d like to speak with your customers, in spite of more recent restrictions put in place.
But let’s remember - ChatGPT is not available for production use (yet). In order for LLMs to achieve mass adoption they need to become embedded into existing tools before they will be used for any of the above. There’s too much friction today. They need to be part of your workflow and easily accessible and usable, which is why it's encouraging to see the progress Voiceflow has made in recent weeks.
Where could this lead?
As this ‘mind blowing panel of talented professionals’ says, the future of conversational AI is going to be one where we give specialised services to each and every customer.
ChatGPT allow for that to happen, and when it is production-ready, it should allow teams building conversational AI to spend more time researching user needs and improving the conversational experience to give users what they need.
Each and every one of those customers is unique, and each of them has specific needs when they contact you. ChatGPT may well allow us to dynamically generate the best way to communicate with them depending on their circumstances (while keeping in mind the bot’s designed persona and the brand too).
You could say the tide of our entire industry will rise, and every practitioner will be able to make better experiences for every customer. ChatGPT and other LLMs won’t solve all issues, and they won’t replace conversation designers, but they should allow everyone to do better work.
All of this nudges our industry forwards. Conversation designers may become more curator than creator, leading a small army of bots to ensure that customers get the best service possible, because ChatGPT shows that computers can convincingly create human language.
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This article was written by Kane Simms and Benjamin McCulloch .
About Kane Simms
Kane Simms is the front door to the world of AI-powered customer experience, helping business leaders and teams understand why voice, conversational AI and NLP technologies are revolutionising customer experience and business transformation.
He's a Harvard Business Review-published thought-leader, a top?'voice AI influencer'?(Voicebot and SoundHound), who helps executives formulate the future of customer experience strategies, and guides teams in designing, building and implementing revolutionary products and services built on emerging AI and NLP technologies.
AI Product Manager | Generative AI | NLP | Chatbots and AI-powered solutions
1 年Great thoughts and stuff to experiment! Thank you Kane
Senior Product Manager @ Critical TechWorks | a BMW Group & Critical Software joint-venture
1 年Daniel Cardoso
Digital Product Owner
1 年This is amazing and so helpful! Thank you for sharing.
Managing Digital Change across Leading Organisations
1 年Really like this Kane Simms thank you - Using ChatGPT to prompt suggestions like these is a great use case and when developing conversational ai the more ways of asking the same intent that you can define before launch the more effective the bot will be. Will definitely be using this. Thanks again.
Co-Founder & CEO at Juji (juji.io)
1 年Kane Simms thanks for sharing! Love #6 the most.