At the Xconomy Robomadness event in Boston this past week, I heard former Evernote CEO Phil Libin speak on a panel about business use cases of A.I. I've talked to many VCs about conversational interfaces and I think that at the moment, Phil has thought more about them than any other VC I've met. During the panel, Phil use a term that I hadn't heard before, but really liked - "cognitive ergonomics." A quick search turned up quite a few articles but, it is clear people haven't thought about this concept in terms of Natural Language Experiences (NLX). I'd like to take this post to outline a few key ideas about that.
A phrase from the Wikipedia definition sums it up nicely. "Cognitive ergonomics studies cognition in work and operational settings, in order to optimize human well-being and system performance." From a NLX perspective, this means a "bot" has to be able to communicate in a way that minimizes the cognitive load on the user. Since design is generally all about tradeoffs, I have been asking myself "what is the tradeoff when you minimize cognitive load?" I think it is time.
As the CEO of a company that is building an intelligent assistant, I spend a lot of time in team discussions about how Talla should communicate. What I'd like to do is share a few cognitive ergonomic ideas we are talking about. Feedback is of course welcome if you have input on these ideas.
1. Cognitive Efficiency - This is a measure of how much cognitive effort is saved through the interface. For example, compare 3 alternatives to getting calendar information for something 2 weeks away. In the first, a user has to exit a messaging platform, open a calendar, scroll to the right day, and find the event on the calendar. In the second example, a user can ask Talla, right from a messaging platform, a question about the day, or the event, thus saving several steps. In the third example, Talla can anticipate that the user may need that information based on ambient information, and volunteer it without the user asking. These are three steps of increasing cognitive efficiency.
2. Cognitive Return on Investment - This has to do with the ratio between Cognitive Efficiency of a new task, and the investment required to teach Talla that task. Tasks that are easy to teach but super powerful have a higher ROI that tasks that are either difficult to teach, or, easy to teach but limited value.
3. Cognitive Fatigue - Some people are just draining to interact with. Others are very encouraging and engaging. Bots could have the same types of impacts and so should attempt to minimize cognitive fatigue. Good bot interactions should have the same impact as having a helpful conversation with a human - not too much info beyond what you need, concise and direct, and helpful.
4. Cognitive Fit - Just like everyone has a favorite style of chair, everyone has a favorite style of conversation. Bots should match their language style to the kind you like by learning your interactions.
Those are some initial ideas on what cognitive ergonomics for conversational interfaces may look like, but I'd love to hear your ideas. Please email me with your thoughts, and if it makes sense in the future I'll do a follow up post with a deeper list of ideas.