Conversational AI is at play in so many aspects of our digital interactions. But getting the best outcomes from AI requires conversational AI literacy. Such literacy is not about niche technical skills but about general conversational skills, specifically how to prompt well.
Conversational AI fluency: the skill of prompting
Good prompting is the foundation of conversational AI fluency. We can all agree that reading and writing are important life skills. But equally important, at a time where AI is becoming ubiquitous, is conversational AI literacy as a basic life skill.
Getting the best and most out of conversational AI is only achieved when users can clearly articulate what they want, within a defined context, precisely and with the additional step of reviewing and refining the first draft output working towards an outcome.
Good prompting is about:
- Clarity
- Context
- Conciseness
- Critical analysis
Conversational AI literacy as a skill
How well we communicate with conversational AI is equal to how valuable a tool it will be. Those who do learn how to use it will understand that the quality of input determines the quality of output. It is not the tool that will fail, it is a failure in using it in a way to get the best outcomes.
For example, when using GPS, we can input something vague such as, “somewhere pretty”. And you’ll get a generic response. Or we can be precise with our input and include area, distance, preferences, constraints and get a direct route to a more exact location. The same goes for conversational AI in that vague input will give vague output.
Conversational AI as a skill requires knowing:
- How to define the context
- How to ask AI productive questions
- How to specify the output
- How to review and refine output
- When to rely on AI and when not to
Conversational AI literacy is now a basic requirement as important as good writing and reading. Those who learn how to execute the above well will have an advantage.
Why skills development is important
Conversational AI is not just about retrieving documents from systems and acting as a search engine. It goes a step beyond by integrating information, providing options, model reasoning, and drafting outputs.
This capability is heightened when there is a preciseness of direction with input. Conversational AI is not just another tool in the AI arsenal. It is a tool that requires a new literacy and fluency in the language of conversational AI and how to think.
It is important to remember that the intersection where conversational AI meets humans is at the level of language – natural language. This means the interaction is an ongoing exchange, replacing the traditional interfaces between humans and machines that was about clicks, fields and workflows. With conversational AI it is about dialogue that shapes what will follow in the world of knowledge work.
Expertise
The technology user is as important as the technology itself when it comes to the value the technology provides. The power and possibilities of conversational AI are well documented. However, it relies on the quality of the instructions (the prompt), and of the questions asked and constraints articulated, for conversational AI to deliver on its promises.
People who can clearly articulate goals, context and critical review and refine output will extract the most value from conversational AI.
Conversational AI doesn’t replace expertise, it requires expertise. And being fluent in conversational AI is a skill that enables productive dialogue with a machine, and that will result in the best outcomes that deliver the most value.
