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From Chatbots to Augmented Conversational Assistants
The document outlines an experimental study on enhancing chatbot capabilities through AI and crowdsourcing. It discusses various methodologies to improve chatbot knowledge, including AI techniques like computer vision and recommendation algorithms, and emphasizes the importance of human contributions and inclusivity in chatbot design. The talk aims to provide insights on future improvements and adaptive answers to enhance user interactions.
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From Chatbots to Augmented Conversational Assistants
- 1. From Chatbots to Augmented ConversationalAssistants: An Experimental Study combining AI and Crowdsourcing Frederic Jacquet Chief Innovation Officer Lao-dja S. Tchala Data-Scientist
- 2. Agenda § Talk Overview:What can you expect § AI/ML to Augment Chatbots capabilities § Methods & Human to improve bots knowledge base § Perspective: Making an Inclusive Chatbot § Wraping Up
- 3. • Talk Overview:What can you expect • AI/ML to Augment Chatbots capabilities • Methods & Human to improve bot knowledge base • Perspectives: Making an Inclusive Chatbot • Wrapping Up
- 4. "By 2020, theaverage person will have more conversations with bots than with their spouse" Gartner 2016 Gartner's Top 10 Strategic Predictions for 2017 and Beyond: Surviving the Storm Winds of Digital Disruption
- 5. An Experimental Studycombining AI and Crowdsourcing Identifying the most relevant AI/ML features that bring advanced conversational capabilities to Chatbots. Bringing more understanding and replying abilities to Bots defining a progressive methodology where data are improved based on crowdsourcing. • Methods and Human • AI/ML to Augment Bots
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- 7. • Talk Overview:What can you expect • AI/ML to Augment Chatbots capabilities • Methods & Human to improve bot knowledge base • Perspectives: Making an Inclusive Chatbot • Wrapping Up
- 8. AI : ComputerVision – multiple choices • What is it? • Why? • Our hypothesis • Which technologies?
- 9. AI : ComputerVision – multiple choices • How it works?
- 10. AI : ComputerVision – multiple choices Train a model with a set of images 1 Track a hand on the images 2 Calculate the center of the cercle around the hand 3 Coding an action depending on the center’s position 4 ACTION 1 ACTION 2
- 11. AI : ComputerVision – multiple choices • Demo
- 13. AI : ComputerVision – multiple choise • Future improvements
- 14. ML : Recommendation algorithm •What is it? • Why? • Our hypothesis • Which technologies?
- 15. ML : Recommendation algorithm •How it works?
- 16. ML : Recommendationalgorithm • General Qi Qj Qk Full Text Full Text Full Text Ai Aj Ak Ai Aj Ak Ai Qi Aj Qj Ak Qk Qi Qk Key_word_i1 Key_word_i2 Key_word_k1 Key_word_k2 User send message 1 Bot answers 2 Mapping 3 Key words extraction 4 Model prediction 5 Qi Qk Ai Aj • Helpdesk use case : equipment's recommendation Qj Full Text Full Text Full Text Qi Qk Manager Equipment_i1 Equipment_i2 Equipment_k1 Equipment_k2 Authentificated users send messages 1 Key words extraction 4 Developer Administrator Qi Qk 2 3 Rôle prediction 5 Administrator Developer Administrator tips Bot predicts the user’s rôle and proposes supplement equipments 6 Equipment_i1 Equipment_i2 You must be an Administrator You might also need Administrator
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- 19. ML : Recommendation algorithm •Future improvements
- 20. • Talk Overview:What can you expect • AI/ML to Augment Chatbots capabilities • Methods & Human to improve bot knowledge base • Perspectives: Making an Inclusive Chatbot • Wrapping Up
- 21. Humans’ contribution • Whatis it? • Why? • Our hypothesis • Which technologies?
- 22. Humans’ contribution • Howit works?
- 23. Humans’ contribution Qi Qj Qk Ai Aj Ak Qi Ai Qi1 Qi1 Qi1 Ai Qi1 Qi1 Ai Ai Ai QiAi Qi1 Qi1 Qi1 Ai Qi1 Qi1 Ai Ai Ai Qi Ai Qi1 Qi1 Ai Qi1 Ai Ai Augmenting Data 1 Cleaning Data 2 Feeding the bot 3 Ask for clarification Reformulating answers Adaptive answers
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- 27. Humans’ contribution • Futureimprovements
- 28. Adaptive answers • Whatis it? • Why? • Our hypothesis • Which technologies?
- 29. Adaptive answers • Howit works?
- 30. Adaptive answers Qi Qj Qk Full Text FullText Full Text Ai Aj Ak Ai Aj Ak Ai Aj Ak Ai Ak User send message 1 Bot answers 2 Training Data from user 3 Model predict which answers the user may like or not 4 Model training 5 Aj Al Ak New answers’ prediction True values Predcitons Memory to use in next conversations Al Ak 6
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- 33. Adaptive answers • Futureimprovements
- 34. Reformulating answers • Whatis it? • Why? • Our hypothesis • Which technologies?
- 35. Reformulating answers • Howit works?
- 36. Reformulating answers Qj User sendmessage 1 Ai Ai1 Ai2 Ai3 Ai Ai1 Ai2 Ai3 Bot chose a response and send it to the user 2 The already given responses are removed from the ones the bot will chose from 3 Qj Ai Ai1 Ai2 Ai3 OR 4
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- 39. Reformulating answers • Futureimprovements
- 40. Ask for clarification •What is it? • Why? • Our hypothesis • Which technologies?
- 41. Ask for clarification •How it works?
- 42. Ask for clarification Qi 2questions are similar 0 Qi Qi1 Qi1 Qj Qj1 Qj1 Qi Qj Qf Qe Qf User ask one of them 1 Key_word_i1 Key_word_i2 Key_word_k1 Key_word_k2 Key_word_i1 Key_word_i2 Key_word_k1 Key_word_k2 Keys words are extracted from each of those questions 2 Keys words are used to ask clarification to the user 3 Do you mean Key_word_i1 Key_word_i2 Key_word_k1 Key_word_k2 or Key_word_i1 Key_word_i2 Key_word_k1 Key_word_k2 ?
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- 45. Ask for clarification •Future improvements
- 46. • Talk Overview:What can you expect • AI/ML to Augment Chatbots capabilities • Methods & Human to improve bot knowledge base • Perspectives: Making an Inclusive Chatbot • Wrapping Up
- 47. Inclusive Chatbots Because textingor talking may prove to be temporarily or permanently challenging because of morphology specifics, trauma, mobility deficiency, stroke, diseases or any deficiency.
- 48. • Talk Overview:What can you expect • AI/ML to Augment Chatbots capabilities • Methods & Human to improve bot knowledge base • Perspectives: Making an Inclusive Chatbot • Wrapping Up
- 49. Feedback / Questions Doyou have any questions? Your feedback is important to us. Don’t forget to rate and review the sessions.