The Rise of Artificial Intelligence in Chatbots
The Rise of Artificial Intelligence in Chatbots
AI is a world-changing, massively important technology for all kinds of uses. From fighting crime to helping save the planet, it is the great big hope for so many industries. As such, lots of tech brands want to highlight their AI prowess. Yet, not all AIs are created equal, so we take a look at the varieties of AI in use, and where it will drive the key chatbot and other markets next.
Artificial intelligence is rapidly moving from the tech pages to the front pages, as industries, governments and markets look for the next powerful solution from the IT industry. While it might make for “robots took my job” stories in the tabloids, the reality is that AI can help all sorts of companies build chatbots, services and solutions to impact our daily lives and make businesses more efficient.
Most AI-based tools need a little hype as the technology is rarely obvious, or in the end user’s or customers’ face. A good chatbot is indistinguishable from a chat session with a customer support agent, a self-driving car with the driver awake at the wheel looks just like any other vehicle and plenty of dumb robots perform just the same as those with AI smarts built in.
All of which makes selling AI a fun and challenging part of marketing for the vendors and an area of growing concern for buyers. They might be asking, is the AI on offer really smart? Is it a fixed AI or will it get smarter and will it remain available or the same over the lifetime of the actual product? Then there are the consumer concerns about AI, with the recent example of San Francisco banning facial recognition technology, demonstrating how carefully AI needs to be used and marketed.
Whatever the news and hype, many more businesses are investing in chatbots to handle their customer service, but wonder just how to build AI chatbots. Well, with SnatchBot, they can be acquired as-a-service and built using simple design tools requiring no advanced coding skills.
What is AI? And Where Is It In A Chatbot?
Chatbots, due to their rapid proliferation, have acted as a leading trend for the AI-hype. Even though many early bots were nothing more than a script with simple response-based, or option-based interactions to help with customer services.
But, in a few short years, AI in various forms has come to dominate the chatbot landscape. That’s as the likes of Facebook make bots easy to create and launch on Messenger, where over 300,000 bots are ready to serve. Also, the big tech names like Google, SalesForce Apple and Microsoft also add bot and AI features to their enterprise services and a growing number of specialist bot vendors compete with dedicated products and ai chatbot platforms.
All of this activity creates a confusing landscape where it can be hard for the buyer to understand what AI is part of the product, and what role it plays.
AI comes in many forms, in most cases when it comes to chatbots used in the form of Natural Language Processing (NLP) and natural language understanding to better comprehend what someone is asking. That helps move the conversation on from simple Yes/No, A/B/C and similar structures to something that actually involves chat.
While Artificial intelligence in chatbots needs to be smart, they don’t need to be the deepest of AIs or have the luxury of rushing off to the cloud to do deep research on customers’ input. Instead, they need to be fast and light, ready to respond at human conversation speed.
SnatchBot’s Bright AI
In the case of SnatchBot, the chatbot’s AI kicks in behind the scenes, whether the user is interacting with it via social media, a mobile app or website. The content of a chat is directed to SnatchBot’s cloud-based AI for processing.
As such, IT buyers and customers don’t really see the AI in action or notice it, unless it happens to answer a complex question or gets the meaning of a tricky or colloquial phrase. Or, if it can’t answer a question due to insufficient information or poor training.
The AI for SnatchBot uses natural language processing (NLP), trained via a Bernoulli Naive Bayes algorithm. These help bots learn the best answers, and the BNB provides a “yes” or “no” answer for particular words, phrases or responses based on the training. BNB provides enough data for a chatbot, and is faster in operation than the more complex statistical and computational analysis tools.
When chatting to the bot, the AI technology helps break down each sentence so that the NLP can understand what the user means. To do so, it breaks down each sentence into its essential components. From that it can find key words or phrases of importance, to understand a question or comment.
When examining the text the bot breaks things down into entities (things, like nouns in English) and intent (actions, like verbs). The entity might be a time, location or thing, common in chatbots when ordering or making a booking. Intent focuses on key actions like “booking,” “delivery” or “buy.”
As part of the training, the chatbot creator can define as many key words as they need to help the bot understand what is important. Having identified the entities and intents, the chatbot can respond and move to the next step, or seek clarification.
When the bot makes a mistake, SnatchBot uses supervised machine learning so the creator can help the bot understand its mistake and demonstrate a correct response.
Another tangent that chatbots are taking is the move to voice response. This is practical when the user doesn’t have hands free to type on a phone screen or traditional keyboard. And, with the rise of Amazon Alexa and other smart devices, it gives the chatbot a new platform to work on.
Most bots have an automatic text-to-speech and speech-to-text feature to help both sides of the conversation understand each other. With the AI in some systems helping perform highly accurate translation and giving the audio element a realistic speaking voice.
At this point, it is worth noting that bots need to tell people they are digital beings, and brands that don’t risk all sorts of negative feedback if they pretend their bots are actual staff. For now, most people know or can tell they are talking to a bot. But, when they get a bit smarter or talk just like us, the temptation to pass them off as real will be tempting.
Going beyond human-to-chatbot interactions, the final level of chatbot evolution sees chatbots talking to other bots. This could be a bank bot talking to an insurer bot as part of a package deal or automated stock checking between Internet of Things devices. Bots will talk to each other slightly different than humans as they will need to understand the capabilities of the other party.
How does an AI chatbot work?
Bots can be trained both automatically and through human beta-testing to perform well before they are let loose on the public. That is, the owner feeds in suitable data, perhaps transcripts of previous customer service interactions or other sources of data, which the NLP engine uses to add weight to key terms and phrases, and learns how best to respond to them.
Some chatbots use self-learning, where they guess at what is the best solution during the training. Others use managed learning, where they suggest the best solutions to a question or responses to a phrase, and the human overseer will tell it which is the best. As bots advance the need for human interaction will be less,
The Future for Chatbots
In just a few short years, companies, brands and services adopting chatbots having moved on from scripted models of limited utility to multifunctional and more responsive bots. They can deal with airline or cinema bookings, health issues, handle government or banking inquiries and much more.
Creators of business bots need to be aware of the risk of bias in bots. This can be through poor design, training or data. This can see bots failing to understand colloquial terms, not give relevant information and suffer from deeper problems. Proper training and testing, and checking results with a wide enough user base or community can help avoid these issues.
Despite the few hiccups, already AI chatbots for customer service are rapidly changing that market’s landscape, fast becoming the quickest way customers can solve problems without being left hanging about for a support agent. And, as bots get smarter, the AI chatbots for a growing number of business use cases (link from chatbots for business post), from human resources to internal engagement are fast becoming an everyday feature.
Far and wide, we are seeing growing use in a number of sectors from AI chatbot healthcare (link from healthcare post) to local government solutions, and with travel and transport being keen adopters.
If that’s enough incentive to get your business a chatbot before your rivals leave you behind, remember to invest in an AI technology suitable for the company’s needs. Most businesses don’t need a bot as part of some massively deep and complex AI solution, and neither do many companies need a whole fleet of other AI services.
The reality is, business-class AI has come a long way in a few short years, and powerful chatbot solutions are available as a service to sit alongside your accounting suite, office tools and email. While the AI side may sound scary and challenging, the tools to help build an AI chatbot are far from complex and require no special skills.
That means any business, without the backing of a big IT department, can build a bespoke and useful chatbot to engage customers, turning support and sales into a 24/7 function, without the need for a sizeable support or outsourced hotline team.
As far as your customers are concerned they are already finding chatbots working for a growing number of businesses from take-out pizza to doctor surgeries and banks. Once most people have got over the novelty of that first chatbot interaction, they will treat it just like any other innovation like the smartphone or touchscreen banking or travel booking kiosk.
Whatever your business, the key to AI is to not treat it like a magic bullet, but as just another part of the many digital services on offer. Also, don’t let vendors sell it to you as a magical solution, even a simple bot needs a little effort and use of common sense to be productive. With that in mind, any business can work with AI to create useful chatbots that can benefit the customer and business, and will be essential to engage, drive sales, provide support and solve problems going forward.