Note!

• The slides are layed out in 2D space!
• Press left / right to change sections
• Press down to proceed to next slide of current section
• Press up to proceed to previous slide of current section
• Or just press the spacebar to move on to what comes next ;)

Note!

• All images are taken from relevant posts and articles
• You can click on the images to be directed there

Chatting, Texting, Messaging

Chatting more than SMS

Chatting is pretty wide

People communicate more in "text" than in "voice"

*Especially young people!

**Millennials: 20-40 years old at time of writing (2017)

OpenMarket Report 2016

Talking to friends

Talking to friends

Why do people like communicating like this anyway?

• Asynchronous: keeps you connected with friends through ongoing conversations while being at another context, e.g., at work
• Fast: perfect for quick information, e.g., "Send me your address"
• Groups: great for arranging plans for dinner, drinks, hobbies, trips, etc
• Multimedia: pictures, emoticons, stickers, GIFs! 
• Casual: easier when talking to people you know less

Talking to companies

Talking to companies

When a company contacts a customer by texting:

• Less invasive than receiving a phone call: people feel more comfortable in asynchronous and anonymous communication
• Normal: people are used to talk like this everyday 
• Personal: people feel they are treated better! e.g., compared to receiving a more "dry" email

Chatting is big

OK, so it's a wide new medium where companies can talk to their customers!

Where though, on SMS, Messenger, Viber..?

Some platforms are bigger than others

Some platforms are bigger than others (March 2017)

The new marketing dream is to be able to talk to customers on

Facebook Messenger
(push messages)

Facebook provides the tools

• Facebook pages support chatting 

• Users can send "Inbox" messages on Messenger

• Human operators can handle the messages (when they are online) and chat on Messenger

Facebook provides the tools

It's like "casual"
Customer Service

It works for traditional
Customer Service too

And the natural question is:

Can we automate this B2C conversation with AI?

Chatbots!

Chat Robots, Chatbots, Bots

What is a chatbot?

Types of chatbots

• On the left side Mobile Apps

• On the right side AI Assistants

Chatbots as

AI Assistants

The vision of AI Assistants

AI Assistants can

• converse in natural language 
• understand what people mean
• act accordingly to serve people

Rose

• July 2016, just around the time that messaging platforms were opening up for chatbot development

• Web-based, users can talk to Rose over a website

• "UBS has a new advertising campaign starring «Rose,» a quirky chatbot. Although «Rose» won a prestigious award for how lifelike she is, a practical test shows that artificial intelligence – as banks hope to use it – still has some ways to go at winning clients over."  -- finews.com

Rose

What it takes to be human? -- nytimes.com

Rose

What it takes to be human? -- nytimes.com

Rose

• Open-ended conversation is tough to handle; "off-script" answers show the weaknesses of the chatbot

• A storytelling experience is maintained with tricks like moving on with conversation regardless of answers

Tay

• March 2016, Microsoft releases @TayandYou on Twitter, a bit before the beginning of chatbot spike 

Tay

• Microsoft showcases the power of (its) AI, by allowing the chatbot to train itself on the responses by users

• The experiment goes bad and chatbot shuts down..

Tay

• This serves as evidence that it's (still) tough to make machines that understand and use natural language

• E.g., consider Microsoft's resources on AI, VMs, etc!

• Note that Tay essentially served marketing purposes for showcasing the cutting-edge AI by Microsoft

• "Microsoft terminates its Tay AI chatbot after she turns into a nazi" -- arstechnica.com

Chatbots as AI Assistants

• It is tough! But we have seen this before!
• As for many technologies (and AI itself), the vision is often over-hyped and reality reveals the challenges

Types of chatbots

• On the left side Mobile Apps

• On the right side AI Assistants

Chatbots as
Mobile Apps

Chatbots as Mobile Apps

• Messaging Mobile Apps, e.g., Facebook Messenger, have most of the UI elements that one needs to build a mobile app: Button, List, Text-box, Images, etc

Chatbots as Mobile Apps

Images in carousel

Buttons

Links

Chatbots as Mobile Apps

• While the AI Assistant vision aims at chatbots that you talk and ask them anything, a practical alternative is the familiar "screen-based" Mobile App experience

• This is an "app-in-app" experience: instead of downloading a different app for every case, e.g., brand or service, the user can just "talk to" the corresponding persona in the chat app
• Let's see some examples!

Facebook provides the tools

• Facebook pages support chatting 

• Users can send "Inbox" messages on Messenger

Burberry

• It is natural to add a "smart answering machine" that gives digital marketing content and information

Tommy Hilfiger

• More advanced ones may offer personalized content based on a quick interview

Chatbots as Mobile Apps

• The fashion business has embraced social media and digital marketing and is very active on such solutions

• Many other cases too:

  • News

  • Retail

  • Travel

  • Sports

  • Games

  • ...

Kayak

• Very similar to what you would do on the website or the mobile app, with a touch of natural language

Hi Poncho

• Popular chatbots offer a chat experience with emoticons, animated GIFs, chat slang, etc

Chatbots as Mobile Apps

Links to the ones we saw:

• Burberry
• Tommy Hilfiger

• Kayak

• Hi Poncho

• Nearbot

You can find and try some more on chatbot listings such as ChatBottle, BotList

OK, but how do you build a chatbot?

Chatbot Anatomy and AI

Anatomy of a chatbot

• A platform plays the intermediary between a user and the chatbot, e.g., Messenger, Intercom
• When a user sends a message it passes it to the choatbot to decide what to reply and serves the reply

Anatomy of a chatbot

• The insides of a chatbot vary but there are three main components we can abstract: NLU, CM, NLG

Anatomy of a chatbot

• Natural Language Understanding (NLU): This component processes the user message, classifies it, extracts parameters and information
• Conversation Manager (CM): This compoment keeps track of the conversation history and decides the chatbot's next steps
• Natural Language Generation (NLG): This component generates an appropriate response to the user, e.g., with emotion, variety, etc

Types of chatbots

• On the left side Mobile Apps

• On the right side AI Assistants

Anatomy of a chatbot as a Mobile App

Anatomy of a chatbot as a Mobile App

Anatomy of a chatbot as Mobile App

Chatfuel

• Chatfuel is a very popular online tool for developing chatbots following this metaphor

Chatfuel

Chatbots as Mobile Apps

A lot of chatbots recast existing solutions such as:

• website, e.g., showing information about a catalog
• blog, e.g., showing recent news on topics
• webapp for an online service, e.g., giving information about the weather
• e-shop, e.g., for buying clothes and shoes
• customer support, e.g., answering based on FAQ
• assistant, e.g., booking appointments
• ...

Chatbots as Mobile Apps

Many tools for developing chatbots without coding, based on adding content and following templates!

• https://chatfuel.com/
• https://www.motion.ai/
• https://octaneai.com/
• http://www.converse.ai/
• https://www.firebot.io/en
• https://www.botplatform.io/
• https://flowxo.com/
• ...

Types of chatbots

• On the left side Mobile Apps

• On the right side AI Assistants

Anatomy of a chatbot as an AI Assistant

• Relying solely on AI is still in research

• Not mature for commercial use (yet!)

Anatomy of a chatbot as an AI Assistant

A practical approach that works

Anatomy of a chatbot as an AI Assistant

Practical Natural Language Understanding NLU 

A practical approach that works

• Intent detection based on examples: whatever the user says, the systems map it to one of a small number of curated cases of intents

• Authored responses for each detected intent

Practical Natural Language Understanding NLU 

A practical approach that works

• Parameter detection allows for more tailored responses; a lot of pre-trained tools allow to detect common entities such as dates, numbers, colors, etc

• Typically some programming skills are needed 

Practical Natural Language Understanding NLU 

• Facebook Wit.ai
• Microsoft LUIS
• Google Api.ai - DialogFlow
• Amazon Lex
• Open source: Rasa.ai

Limitations

• This is closer to a "Conversational AI" but still it is far away from a system that understands any question 
• Lots of simple things that cannot be handled with existing "general-domain" tools, e.g., an intent that answers questions of the form "Is Ned Stark dead?" cannot handle question "Is Ned Stark alive?"

• This is where you need to talk to AI experts ;)

Anatomy of a chatbot 

• Note: It's all about the services
• The chatbot acts as a new front-end for these

Limitations

Chatbot UX

Chatbot UX 

Some simple but powerful guidelines

• Alternative Answers: Don't give the same reply twice

• Memory: Don't offer the options that the user has already selected before in the same session

• Default fallback: Use smart ways to provide constructive feedback

• Navigation as Interactive Storytelling

Interactive Storytelling

• As human-like AI is not achieved yet for NLU, CM, NLG, chatbot design is closer to curated storytelling

• Chatbots are computer programs; this allows for dynamic stories and interactivity

• No golden standards for designing interactive stories

• There are similar challenges in other digital media, in particular extensive studies in videogames

• We will follow some main ideas from there using the gaming terminology

Linear Storytelling

• Linear storyline similar to the “one story” of films

• Strict order of plot points, only one way to move forward

Open-world Storytelling

• Players may visit plot points in any order they choose

• E.g., World of Warcraft, Grand Theft Auto

Linear-Islands Storytelling

• Several open-world groups (islands) in a linear order

• E.g., in Syberia all chapters start and end in a fixed way but the order of sub-parts of the story can vary

Branching Storytelling

• Branching depending on player action that may lead to different endings

• E.g., Heavy Rain, Beyond Two Souls

Interactive Storytelling

• The player picks story paths with his choices

• A "Drama Manager" selects to enable/disable parts of the story based on the player's detected type

Interactive Storytelling

• As the story graph grows, special tools are needed to design, maintain, and debug the storytelling experience

Takeaways

Chatbots are a new channel

• Targets well a large demographic (Millennials)

• Can be seen as an additional channel along with Website, Social Media, Mobile Apps

• As the mobile platform is dominating the way we consume information (e.g., in comparison to desktop PCs) the chatbot medium can become "the new website"; it's already "the new mobile app"

Chatbots are easy to build

• Plenty of DIY solutions for common use cases

• Plenty of developers available for custom solutions

• There is a hype similar to the "mobile app craze", you can't go wrong with building one now ;-) 

Chatbots are hard to build

• AI is over-hyped and in reality it needs a lot of effort to build "human-like" assistants

• No real guidelines for Conversational UX yet!

• Content is king (here as well)!

• Similar to website design and development: it's the narrative and the experience that matters ;-)

Chatbots are a new medium

• It is still in the beginning!

• Every month the big platforms release more features (Facebook Messenger is leading)

• Group chat with chatbots

• C2C (Chatbot to Chatbot) communication

• Chatting as a common API

• Hybrid chatbot and human operator ecosystems

Questions?

Stavros Vassos, AI Architect at Helvia.io

About.me: https://about.me/stavrosv
Email: stavros@helvia.io
​Twitter: @stavros.vassos

Google+: Chat is the new black

Brief CV

• 1996-2001: Diploma in ECE,
  National Technical University of Athens, Greece
• 2002-2008: MSc & PhD in Artificial Intelligence, University of Toronto, Canada
• 2009-2012: Research Associate,
  National & Kapodistrian University of Athens, Greece
• 2012-2016: Assistant Professor,
  Sapienza University of Rome, Italy
• 2017: Founder, AI Architect,
  Helvia Technologies -- helvia.io