Natural Language Computing. Jeff Bohn Lauren Finkelstein Mike Goodridge Cam Montague John Power Brendan Ricciardelli

Transcription

1 Natural Language Computing Jeff Bohn Lauren Finkelstein Mike Goodridge Cam Montague John Power Brendan Ricciardelli

2 Chatbots: Utilizing chat or other natural language interfaces (i.e. voice) to interact with people, brands, or services and bots through artificial intelligence Chatbots Text/Voice Natural Language Processing Machine Learning

3 Chatbots for Customer Service (KLM)

4 The Transition to Chatbots Web Mobile Apps Messaging Chatbots

5 Timeline to Date Turing Test Created ELIZA Parry Jabberwacky Dr. Sbaitso A.L.I.C.E. Smarterchild IBM Watson Apple Siri Google Now Alexa Google Home

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7 Perceived Benefits- Chatbots vs. Apps 100 Person Survey Friendliness Detailed Answers Timely Complaint Resolution Good Customer Service Quick Answers to Complex Questions Easily Register Complaints Easy Communication Convenience Quick Answer to Simple Questions 24 Hour Service App ChatBots

8 Current Use Cases Conversational Commerce Customer Service Virtual Assistants Social

9 Verticals Now 2025 Real Estate Bot Real Estate Agents Direct Real Estate Bots (No Middlemen) Hospitality Simple Assistance Comprehensive Customer Service Retail Conversational Commerce Personalized Shopping Healthcare Simple Triaging Personal Health Assistant Government Appeal Parking Tickets Virtual City Hall Media Push News Pull News

10 Bots Aren t Perfect

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15 Chatbot Platforms

16 Who Will Capture Profit? Gatekeepers (Deployment Channels) control transactions Difficult for bot creators to capture large percentage of value Industries have differing business models Profit pools cannot be generalized Recall

17 The Business of Chatbots BaaS (Bots as a Service) - Alexa Skills, Azure Sponsored & Native Content, Affiliate Marketing Quick Market Research of users Lead Generation Ask Gather Direct Profit Pure Retail Sales - Macy s, Home Depot Cost per Conversation/task - Lawyer, Oprah, Mechanic Bot

18 Financial Analysis - AI Funding History

19 A Growing Number of New Players

20 Cost Savings in Using Chatbots Employee salary, benefits, ect Capacity smoothing and shifting agents to other positions Potential Annual Savings Customers Service Reps $23 $79 Sales Reps $15 $43 Reduction in attrition of staff Customer Service savings estimated at 29% Securities, Commodities, and Financial Services Reps Insurance Sales Reps $15 $12 $20 $32 $0 $20 $40 $60 $80 $100 $120 Potential Annual Savings Total Annual Salary Expenditure

21 Effect on Businesses and Customers Benefits Commerce Costs Less choice for Customers Customer Service Not as intuitive as humans Unintended outcomes Commerce Going to where customers are (App Fatigue) Frictionless integration Customer Service Always on fast response time Self Sufficiency

22 Industry Tipping Point

23 Industry Tipping Point Theory 1 Passes Turing Test Theory 2 Messaging platforms are THE platform Satisfies all user requirements with full app integration People are reluctant to install apps Solves discovery issues

24 Bot Evolution Today Platform Many Oligopoly Oligopoly, duopoly, or monopoly Key Technology Approach Platform dependent constraints & experimentation with one-off bots Industry forms best practices Standardization via APIs Bot Owner Supply Side Platform or Demand Side Platform or Demand Side Personalization Low High Very high Role of Commerce Experimentation Disrupts ecommerce industry Mainstream purchasing route Role of Social Isolated Connected Social 2.0 Capital Flow Supply Side Demand Side Transformation of digital advertising

25 How Chatbots Will Work in 2025 Demand Side Start Need Arises Need & Preferences Communicated Need Met End AI Platform Need Intelligently Interpreted * Supplier Intelligently Selected * Supply Side Suppliers Assessed via API API Utilized * * * Personalized bots consider demand side model preferences and supply side marketing

26 Future Timeline App Overload & Discovery Aggravation xxxx AI Bots Consistently Pass Turing Test Personal Assistants Scour Relationships and Become Predictive Explosion of Messenger Platforms App Services Integrate into Bots - App Stores Disappear Legacy Equipment is Obsolete - Fully Integrated Future

27 Ethical Implications Should people know they are interacting with a bot? Do I care? I am getting the service, so does it matter? Does the situation matter? Do I want to tell a human about a private matter, or would I rather tell a bot? Are we more willing to engage with a bot? For example, Google search - we interact in way we likely wouldn t with a human; essentially, we self censor to some degree when interacting with other humans Will I even think about that? If I m chatting with someone and tell them I ll meet them at the event in 15 minutes and Uber automatically pops up, will I even think about the bot interaction at that point? Can/will this greater accessibility into private life become dangerous or abusive - will it change how humans evolve (e.g. interactions, habits)?

28 Chatbots Beyond 2025 Implants Physical Manifestation Integrated Household

29 The End

30 Appendix

31 Tech Giants Map Network OS B2B Consumer Multi-Product Single-Product

32 The Uncanny Valley

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34 Cost and Benefit (remove/combine with jeff) Conversational Commerce Benefit: Going to where customers are (App fatigue) Benefit: Frictionless Cost: Less Choice for customers Customer Service Benefit: Always on Benefit: Response Time Benefit: Self:Sufficiency One-third say they'd 'rather clean a toilet' than speak with customer service Cost: Not as intuitive as phone reps Cost: Unintended Results (MS Tay)

35 Industries that will see increase automation Source: Oxford Study on Future of Automation

36 Sources