There it is, the very first episode of Efficiently Effective. Let’s dive right into the hot topic of chatbots and conversational UI.
Besides the episode itself, you’ll find information in the experts, a glossary of some of the common terms used in this episode and the link to the podcast on robots taking over jobs from humans. Enjoy!
Our experts in this episode are:
- Sjoera Roggeman – iCapps
Sjoera is a linguist working as a UX professional, and she is pretty excited about the developments towards conversational UI and chatbots. She tells us how natural language processing (half of the magic of conversational UI) works.
- Filip Maertens – FactionXYZ
Filip supplies the other part of the magic: the platforms that are capable of guiding a user through the right flow and machine learning. His company specialises in applied AI.
- Paul Davies – UX Probe
With UX Probe, Paul develops software to test the UX of apps, websites and … chatbots! Because UX is everywhere, right? He explains what metrics matter.
- Alexis Safarakas – Springbok Agency
Springbok Agency has created a few chatbots for their clients. Digital strategist Alexis shares his experiences with that.
Link: How safe is your job? – Freakonomics Radio
About 27 minutes in, I mention an episode of the Freakonomics podcast on robots taking over jobs. It’s a great and very nuanced disquisition of the impact of technology changing our the way we live, consume and work. You can listen to this podcast here.
- AI or Artificial Intelligence: This encompasses the broad field of machines exhibiting intelligent behaviour. Think of a computer being able to recognise and interpret something, and being able to match one piece of data with another, kind of like we do.
- Conversational UI (User Interface): As user interfaces are the links between humans and machines, we use the term ‘conversational UI’ to indicate that the interface has some sort of dialogue in a more literal sense of the word.
- Chatbot: A type of conversational UI. It simulates a conversation that should resemble a human-to-human conversation to guide a user from their intent (what they want to do) to their goal.
- Machine Learning: Literally a machine learning from its experiences and using these memories to get better. It remembers what worked and what didn’t and uses this data in all of its future processes. This way it never makes the same mistake twice and appears to be getting smarter the longer its operational.
- NLP or Natural Language Processing: The way we (humans) process language is very complex. NLP is a five steps simulation of this process, translating our language into data that the computer can work with.