C for Chatbots - Growing Seamless Conversations between Machines & Humans!

As part of the Cognitive Enterprise and also as part of the Watson Education, it is quite interesting to know something beyond the usual ‘SIRI’ what most of us know.  

What made me get interested in Chatbots and also start my own use-cases ( Yes, I have been a Business Analyst too!)  is the urge to create the EmpathyBots that I want to create for ‘Diversity & Inclusion’ initiatives,  I can choose no better topic than Chatbots today.

What is a Chatbot?

Chatbot is a  computer program designed to simulate conversation with human users, especially over the Internet.

A few years ago when chatbots were just gaining popularity, there was a lot of talk around what a chatbot actually was. With the advent of natural language processing and various machine learning techniques, some of the more advanced conversational applications wanted to separate themselves from their competition. Many began calling themselves “virtual assistants.” This implied that they were somehow bigger or more powerful than existing chatbots, or perhaps were more conversational or could cover a wider range of topics.

The market did not care how powerful the bot was or about the underlying technology, so long as it solved the right problems. So in a way, many of these different terms for bots became more or less synonymous with each other. It didn’t matter what you called it – you were getting something you could hold a conversation with. We’re now at a point where we know that regardless of what you call the bot, there are usage patterns and differentiation that make chatbots distinct.

Chatbots let you streamline how you engage with customers, partners, and employees. Use Watson to build robust, enterprise-grade chatbots to transform your customer service department and more.

Conversational Solutions for your business and social life

Whether you're looking to build a basic bot from scratch or looking for more robust integrations, Watson lets you build powerful chatbots that can understand your customers, provide answers and even execute business processes. According to the research study by Mindbowser in association with Chatbots Journal. IBM Watson is the first choice as a bot-building platform for 61% of businesses.

When you’ve done your research and are at the point of beginning to build your bot, think carefully about what problems you’re trying to solve and what functionalities you will want to incorporate. Knowing what you want your application to solve for and assist with will decide the type of chatbot, virtual assistant or agent you ought to build. This will impact both your development plan and, as importantly, your end-user experience. The following are the three main types of chatbots I have come across, with background on their particular uses and variations.

Three Main Types of Chatbots

1. Support chatbots

Support chatbots are built to master a single domain, like knowledge about a company. Support chatbots need to have personality, multi-turn capability, and context awareness. They should be able to walk a user through any major business processes, and answer a wide range of FAQ-type questions. You will want to have a short-tail and long-tail combo solution when building this type of chatbot. At IBM Watson, we would use the Watson Conversation service for the short-tail, common questions and processes, and Watson Discovery service for the long-tail, but there are many potential solutions for this. Speech is an optional feature, and not a necessity, since users typically have sat down at a desktop and are ready to figure out their solution. The chatbot developer will want to spend the most time making sure it is as easy as possible to navigate the bot, and ensuring it can execute the actions that your users actually care about (for example, just because you want to sell more credit cards doesn’t mean your customers want to open more credit card accounts).

2. Skills chatbots

Skills chatbots are typically more single-turn-type bots that do not require a lot of contextual awareness. They have set commands that are intended to make life easier: “Turn on my living room lights,” for example. Speech functionality is recommended for this type of chatbot so the user does not need to turn on a device or click any buttons. They should be able to follow commands quickly, so that your users can multitask while engaging with the bot. These chatbots do not need to worry too much about contextual awareness, unless you want to design a particularly advanced one, as people will quickly learn what to say, and say it appropriately. It’s a nice bonus if you can give a command, and your bot knows – to return to our example – that you are in the kitchen and acts to turn on the correct lights.

However, this is not a necessary function, as users will quickly learn to give the appropriately specific command. When building a skills bot, it is important to focus on integration, especially when controlling a home or personalized objects. Keep integration simple so your users can interact with the bot without worrying about how to use .

3. Assistant chatbots

Assistant chatbots are more or less a middle ground between the two bots above. They work best when they know a little bit about a variety of topics. Many people envision these bots will someday become navigators of all other bots that are out there now. Want to pay a bill? Ask your assistant bot to talk to the support bot for your bank. Assistant chatbots need to be conversational and respond to just about anything, while being as entertaining as possible. Siri is a good, current example – while she only does so much, people continually ask her for things simply because even when she cannot perform the command, the response she gives tends to be amusing. When building an assistant chatbot, it is important to make it as obvious as possible how the bot is trained. The range of questions a user might ask is large, so making sure you have adequate coverage is going to be the most difficult factor. In many cases, when people do not know what they should ask, they will not ask anything at all. And if you miss the few topics they initially are willing to try, they will not come back for more.

Even though these are the most common types, many bots in production fall somewhere in between two. Some are even a combination of all three. No matter what type of bot you decide to build, it is important to give your bot some life and personality, make it useful, and make sure it’s easy to use. People interact with bots because they want to get something done in a more natural way than was previously possible. Whether it’s something simple like turning on a light, or something complex like applying for a mortgage, every pattern has specific features that make it stand out, so be sure your bot shines brightly in what it’s designed to do. The possibilities are endless.

Powering Social Good for Everyone with Chatbots!

Below given  bots that are powering social good for everyone, not just businesses.

These include bots that help people solve legal issues, get therapy, quit smoking and learn to meditate.
 

Chatbots are great for customer service, ordering tickets, or just giving you weather updates, but others have nobler goals for their bots. Here are few bots, developed using a variety of technologies and APIs, and delivered via different interfaces, that are helping improve the world for everyone.

1. DoNotPay: Get free legal help in under 30 seconds

DoNotPay started out as a cheeky service to help drivers get out of parking tickets. Stanford student Joshua Browder became more interested in bots after the online tool automatically challenged over 160,000 of them. People began contacting him asking for help with other legal issues relating to evictions, bankruptcies, and repossessions, so he decided to expand the capabilities of the bot to help homeless people.

Rather than making users fill out a lengthy form, Browder used a natural language interface to gather the data needed to fill out the form. He then used IBM Watson’s Conversation service which helped him improve accuracy by 30%. Browder was only 19 years old when he created this app and Watson’s cognitive APIs helped him build stronger AI into his app in a matter of just weeks. He has since turned his attention to other areas of law, including resolving landlord and travel disputes.

Browder mined 15 years of affordable housing application data, obtained via a Freedom of Information Act (FOIA) request. Then he programmed DoNotPay to ask users personal questions relating to their stated problem. For example, it may ask a resident facing eviction “do you have a right to live here?”. It might ask a person seeking housing “are you legally homeless,” while providing them with a legal definition. It then takes this information and creates an application based on previous success rates, using one of seven default claim letters. His goal with the service is to offer a replacement for what he sees as a subset of predatory lawyers that charge heavy fees to do little more than file paperwork.

Since his success with DoNotPay, Browder, dubbed the ‘Robin Hood of the Internet’ by the BBC, has expanded it to give free legal aid to refugees seeking asylum in the US, Canada and UK.

2. Woebot: Your 24×7 Chatbot Therapist

Created by a team of Stanford psychologists and AI experts, Woebot uses short chat conversations, sentiment and tone analysis and word games to help people who are looking for inexpensive therapy. Wombat Labs Inc. just launched the commercial version of the chatbot this June. The first 14 sessions with the bot therapist are free after which they offer tiered pricing of $6 – $12 per week depending on what plan you sign up for.

Wombat’s creators gave the bot a fun, casual and friendly personality. For example their website says Woebot is “…ready to listen, 24/7. No couches, no meds, no childhood stuff. Just strategies to improve your mood. And the occasional dorky joke.“

Wombat uses a combination of natural language processing, therapeutic expertise, personalized content, and sense of humor to “create the experience of a therapeutic conversation for all of the people that use him.”

The company describes their service as below:

“Woebot is an automated conversational agent (chatbot) who helps you monitor mood and learn about yourself. Drawing from a therapeutic framework known as Cognitive Behaviour Therapy, Woebot asks people how they’re feeling and what is going on in their lives in the format of brief daily conversations. Woebot also talks to you about mental health and wellness and sends you videos and other useful tools depending on your mood and needs at that moment. You can think of Woebot as a choose-your-own-adventure self-help book that is capable of storing all of your entries, and gets more specific to your needs over time.”

You can sign up for Woebot directly on their website at woebot.io

3. U-Report: Your voice matters

Across the world, young people are concerned about a variety of issues, ranging from climate change to the economy. Unicef created its own bot, U-Report, to give them a voice. The bot, available via Twitter and Facebook Messenger, polls its followers (called ‘U-Reporters’) on a range of topics. The idea is to gather opinion and experiences from these young participants, who now number over three million, and use them to help influence public policy. 

U-Report regularly sends out polls on a variety of issues, and assesses the results based on demographic data provided by U-Reporters when they sign up.

The pollster bot has achieved some notable results. In Liberia, it asked 13,000 young people if teachers at their schools were exchanging grades for sex. 86% said yes, uncovering an endemic problem and prompting Liberia’s Minister of Education to work with UNICEF on stamping it out.

4. Quitxt: Helping users quit smoking

It is 2017, and despite smoking bans and punitive taxes, people still continue to light up. Could a chatbot help people to quit smoking? Dr. Amelie G. Ramirez of the University of Texas Health Science Center at San Antonio’s Institute for Health Promotion Research hopes so. She created Quitxt, an SMS-based quitbot designed to help addicted puffers deal with their cravings.

Targeting young adults aged 18-29, the bot consistently encourages smokers to give up and not look back. Smokers can set their quit date and embark on an 8-10 week program, receiving between three and seven text messages per day for the first two weeks, gradually reducing over time. In addition to encouraging words, the bot also provides tips for managing stress and building a support network. Participants can expect links to mobile webpages designed to help people give up smoking.

5. MeditateBot: Creating a daily meditation habit

While some bots exist to help you stop a habit, others want to help you start one. Entrepreneur Eric Rems created MeditateBot as a Facebook Messenger tool to help him remember to meditate. Meditation is a proven health technique, and helps practitioners to remain mindful throughout the day, reducing stress and conflict.

Developed over a weekend, the chatbot teaches the benefits of meditation and advises on different kinds. It also enables people to schedule daily meditation reminders. When creating the bot, Rems focused on keeping the barrier to entry low by not imposing too many requirements on users early on. He avoided collecting too much information from them, so that they could begin using the bot easily without filling out forms that would create a hurdle for them to begin using the bot.

He enabled them to choose when they meditate, and let them choose how long. He also limited the available options. “I’ve seen too many apps that have an endless amounts of options, this makes it hard to select the “right” one — which causes frustration,” he said.

Over 500,000 users have been busy chilling out and improving their mental health using the chatbot, so he must be doing something right.

The possibilities are endless. What type of Chatbot can you build?

References:

https://www.ibm.com/blogs/watson/2017/12/3-types-of-business-chatbots-you-can-build/

https://botpress.io/learn/what-why

Source :  Article: Christie Schneider 

 

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