Bots are all the rage currently. By the looks of it they are at the peak of the hype cycle. We will see their deep fall into the trough of disillusionment soon. After all the well-known examples based on the Facebook messenger are somewhat underwhelming, to formulate it carefully. There is not much artificial intelligence visible – nor needed – to provide services like these. They also come with a poor user interface. And this combination of hyped examples, mixing up chatbots and AI, has the potential to kill customer experience. They certainly kill the user experience.
Unless, this is, that these machines already reached a level of intelligence that they are magic to my simple mind…
Which I doubt.
To be sure, there are AIs around that amaze us: IBM’s Watson, Apples Siri, Microsoft’s Cortana, Google’s Now, … even Microsoft’s infamous Tay which got a pretty bad reputation in no time, to name but a few. Recently a whole class of graduate students didn’t realize that their teaching assistant Jill Watson, an AI based upon IBMs Watson, was actually an AI and not a person.
And I sincerely believe that in not so far future we will see AI in many places that is indistinguishable from a human. As Salesforce’s Marc Benioff recently said we will have AI do things that we cannot even imagine right now. The potential is virtually endless (pun intended).
But what we see right now being built standalone or embedded into messaging apps has nothing to do with AI and it often has a poor user interface. This needs to get fixed, or else the potential of falling back to an 90’s customer experience becomes very real.
I get the potential benefit of connecting to businesses via one single app. And I do think that it is the right way forward! After all this is the very principle that is behind my Epikonic platform with its app front end.
But the way the Facebook Messenger looks right now benefits exactly Facebook, which doubtless has a fairly elaborate AI behind the scenes.
The Way Ahead
But enough of the rant. I do not want to be destructive but show a possible way ahead. Because I think that even the simple bots that we see right now have their value, while the end game is in interacting with full-fledged AIs that we perceive as humans, very patient humans.
According to Wikipedia a chatbot or chatterbot is “a computer program which conducts a conversation via auditory or textual methods. Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, thereby passing the Turing test. Chatterbots are typically used in dialog systems for various practical purposes including customer service or information acquisition. Some chatterbots use sophisticated natural language processing systems, but many simpler systems scan for keywords within the input, then pull a reply with the most matching keywords, or the most similar wording pattern from a database.”
This definition is generic enough that even a simple flower ordering app on the FB Messenger that leads a customer through a predetermined process can get sold as a bot. And this is part of the problem.
In order to make bots more useful and therefore accepted we need to work on a few frontiers. And I am sure that this will happen as part of bots moving through the trough of disillusionment. Part of this process will also change our perception of what a bot is. We stop talking of bots (who is talking of social CRM anymore?) and/or will redefine where the value add for customers and businesses is, by answering two basic questions:
- How does does a bot help my customers to better accomplish their “jobs to be done”? Be they ordering of flowers or organizing a family vacation next spring, or whatever else. This is the harder question to answer.
- How does it help the companies using bots improving their business? This one is related to the first question but also touches efficiency, not only effectiveness.
Supporting this these are the main three things that I think research and industry need to work on are:
- An improved definition of what a bot is, in contrast to a simple application that can achieve the same. There is no need for a “bot” that allows me to set reminders for myself or get travel tips or to subscribe to a newsletter. There is also no need for bots that fail at basic natural language detection. Scanning for keywords as it is still very common simply doesn’t cut the mustard. And the real value lies in a meaningful interaction that successfully imitates an interaction between humans. This definition also needs to involve a distinction between a user interface and the the underlying logic. I would argue that many so called bots are actually just another user interface that is plugged on top of existing applications
- Standardization; so far it looks like the APIs for every platform are different. I do not think that all APIs will ever look the same but some basic services need to get standardized, also to make it easier for developers to deploy across different platforms.
- The ‘killer bot’; at the moment we have bots that basically do the same as apps/applications. And then these ‘old style’ apps are often richer in functionality and more convenient to use. A useful bot needs to deliver a use that is hard to deliver for a conventional app. Some (rudimentary) candidates that I see are in the area of financial services, like Digit or Penny. But I can imagine many more uses in complex areas like healthcare or day-to-day self-organization. Key are rich, useful functionality in combination with a simple user interface and integration to other used applications. Text, admittedly is an interface that we are comfortable with, but that doesn’t make it a good one. How many people are struggling with typing?
Maybe it is worthwhile ceasing to speak of bots altogether when we just mean a user interface? Just thinking …