Teaching computers to converse

When Amazon Echo was first launched in 2014, it was primarily pitched as a smart speaker allowing you to control your music with voice. The next big phase in conversational revolution began in 2016 with the advent of chatbots [1]. Facebook announced a developer friendly platform to build chatbots on messenger. Soon there were tons of toolkits to create bots in minutes. Chatbots are essentially natural language text interfaces constructed using rules and are navigated by pre-defined flows [2].

Bots became a hype owing to app fatigue. Companies saw bots as a new way to generate traffic, usage and engagement on their application without having to install any app. However, the bot technology only worked for conversations with predefined flows like ordering flowers or creating a restaurant reservation. The language of interaction is not so “natural” after all – try asking the bot a complex question with differently timed starts and stops, tones, pauses or implied meanings. As a result, chatbots didn’t deliver on the expectations and became useless pretty soon.

Real conversations require a level of comprehension and cognition that goes far beyond the’ predefined flows. They are conceptually as well as emotionally complex. It is not just about an input-output mapping. There are many parameters like what we say, how we say, where we say, when we say and why we say, that together provide the context of the conversation [3]. In the true aspirational AI world, computers would be able to capture these nuances. Secondly, human conversations often have imperfections like slangs, multi-language sentences, abbreviations, accented pronunciation, etc. which the computer needs to parse and hopefully generate the response in the same “language”. Thirdly, a conversation is not an isolated exchange of messages. It often builds upon previous exchanges, not necessarily all consecutive. A true conversational AI system would be able to identify the related messages from the history and built upon that context to make the exchange more relevant and useful to the user. Moreover, human conversations are tasteful due to unique personality traits, quirks, emotions, surprises etc. and computers would need to incorporate these to make interaction fun and enjoyable. Only then would the smart assistants become truly smart and truly personal!

Many companies like Amazon, IBM [4], Google, Facebook, Intel [5] are investing in this area as it is clear that this is the next big revolution in human computer interaction which feels much more natural than clicks, hovers or typing, and is easily accessible to everyone due to absence of any learning curve.

1. https://venturebeat.com/2016/08/15/a-short-history-of-chatbots-and-artificial-intelligence/
2. https://www.forbes.com/sites/forbestechcouncil/2017/12/04/the-rise-of-conversational-ai/#1e34d65b3b91
3. https://developer.amazon.com/alexa-skills-kit/conversational-ai
4. https://www.ibm.com/watson/advantage-reports/future-of-artificial-intelligence/ai-conversation.html
5. https://www.intel.co.uk/content/www/uk/en/it-managers/conversational-ai.html