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Midwest km pugh conversational ai and ai for conversation 190809

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Conversational AI (chat bots) is here to stay, and it's teaching us a lot about transactions, human language patterns, and the limits of computer-human interaction. But what about AI for Conversation? Can we learn from the Conversational AI research and improve how human-to-human conversation works? Where can we use pattern recognition and predictive analytics to improve how we are present as managers, coaches, analysts, family members or diplomats?

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Midwest km pugh conversational ai and ai for conversation 190809

  1. 1. Midwest KM Symposium Conversational AI and AI for Conversation: Our Role as KM’ers? Katrina Pugh, Columbia University and AlignConsulting July 9, 2019
  2. 2. Agenda 10:00-10:20 • What’s the difference between Conversational AI and AI for Conversation? Short tour of conversational AI and AI for Conversation research today 10:20-10:35 • Table discussion: What’s our responsibility as a KM community? 10:35-11:00 • Report outs and group discussion 2
  3. 3. Alchemy of conversation: from individual identity to collective wisdom • The World Café [conversation] process reawakens our deep species’ memory of two fundamental beliefs about human life. • First, we humans want to work together on things that matter to us. In fact, this is what gives satisfaction and meaning to life. • Second, as we work together, we are able to access a greater wisdom that is found only in the collective. Conversational AI and AI for Conversation Margaret Wheatley, 2005 3
  4. 4. We now have the tools and insights to make conversation better, but it appears we have started backward • The World Café [conversation] process reawakens our deep species’ memory of two fundamental beliefs about human life. • First, we humans want to work together on things that matter to us. In fact, this is what gives satisfaction and meaning to life. • Second, as we work together, we are able to access a greater wisdom that is found only in the collective. Margaret Wheatley, 2005 What if humans (individuals and teams) were augmented or nudged to improve the tone or accuracy? What if wisdom were compiled and presented back in aggregate to solve known problems? 4 AI for Conversation Conversational AI and AI for Conversation
  5. 5. The father of dialogue, David Bohm, was a particle physicist. •Dialogue: “To turn toward another” or “Meaning flowing through” •“I can hold the [Field/space] for you, but I bring my own experiences.” …New, shared meaning 5Four Discussion Disciplines Bohm, David, Donald Factor and Peter Garrett, Dialogue: A Proposal (1991) http://infed.org/archives/e-texts/bohm_dialogue.htm Conversational AI and AI for Conversation
  6. 6. 6 Conversational AI  Definition: Use of messaging apps, speech-based assistants, and chatbots to automate communication and create personalized customer or employee experiences at scale. Studies practices of human conversation, informs conversation content or guardrails, then new conversation participation involves humans with bots Conversational AI and AI for Conversation
  7. 7. Ingestion: Conversational AI for full spectrum of human communication 7 Our interactions will be way more conversational, much more multi-modal. Apps will be able to pick up on our gestures, our facial expressions, our emotions, what is being said in our voice.” Gabi Zijderveld, Chief Marketing Officer, Affectiva Source: IBM Scientists have found a way to decode brain signals into speech It’s a step towards a system that would let people send texts straight from their brains. by Antonio Regalado MIT Technology Review, April 24, 2019 Google’s AI can now translate your speech while keeping your voice Researchers trained a neural network to map audio “voiceprints” from one language to another. by Karen Hao MIT Technology Review May 20, 2019 Conversational AI and AI for Conversation
  8. 8. Ingestion: Google Perspective AI learns about tone, slang • API uses machine learning models to score the perceived impact a comment might have on a conversation. Developers and publishers can use this score to give real-time feedback to commenters or help moderators 8https://www.perspectiveapi.com/#/Conversational AI and AI for Conversation
  9. 9. Ingestion: Intent recognition example: Sarcasm 9 Check out Indian Institute of Technology research Sarcasm Suite Source: Quartz (2016) and NVDia Humans don’t always recognize it! It requires context (speaker, situation, world) Approaches: 1. Machine learning (volume, then phrase matching / information retrieval) 2. Rules (e.g., unexpected juxtaposition, exaggeration) 3. Deep learning Conversational AI and AI for Conversation
  10. 10. Ingestion and production: Open source code working from open-source content Example: Stanford Question and Answer Dataset SQaD 10 Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable. Leader Board has coders who have taken both the question and the text and interpreted them effectively. Source: SQaDConversational AI and AI for Conversation
  11. 11. Chatbots/intelligent agents range from playback, to suggesting, to personalized chitchat (illustrative) General Inquiries Handle basic customer inquiries traditionally hidden in FAQs. Complex Inquiries For requests that a Bot cannot complete hand off to a human agent. Appointment Booking Handle simple “anonymous” tasks via chat, e.g. booking an appointment. Account Inquiry Handle inquiries that require identification of the customer, e.g. account balance enquiry Make Payment Perform actions that require a user to be authenticated and authorised, e.g. make payment to predefined payee. Self-service content Take existing FAQs and content, enable staff to self-serve knowledge via Bot. Simple Customer Bots Know-you Bots Playback Bots Advisor Bot Assist a customer with a multi-step process, solve a problem IT Helpdesk Report an IT problem and check the status. Bot can provide self-help and escalate to engineer if required. Future: Dialogue ? Source: EY researchConversational AI and AI for Conversation
  12. 12. AI for Conversation Definition: Use of natural language processing (NLP) to interpret conversation structure, language, tone, and impact. AI for Conversation will provide personalized input to speakers/authors and teams to improve performance at scale. Can we improve how modern organizations and societies use conversation to collectively surface and solve problems? 12Conversational AI and AI for Conversation
  13. 13. The “Conversational firm” is a model for our time 13 • “Conversation” was more apt [than ‘Openness,’ as a term]…The key is to have an open enough communication environment so that the organization can collectively surface the needs of the current moment and thoughtfully approach the next.” • Employees at TechCo expect to have a voice, conversation-friendly corporate policies and related convening structures (physical layout, wiki).Source: A look inside a “Conversational Firm” MIT Sloan Management Review Ideas Made to Matter, 2-016Conversational AI and AI for Conversation
  14. 14. AI for dialogue is improving: Context switching 14 “How do you really carry context throughout a dialogue? This is the biggest challenge. A lot of how you understand what I’m saying depends on what I said maybe five sentences ago, or fifteen sentences ago. You’re building up a state of the conversation.” Satinder Singh, Director of the Artificial Intelligence Lab at the University of Michigan. Source: Kore.ai Source: IBM (Hold and resume concept (Kore.ai)) Conversational AI and AI for Conversation
  15. 15. Facebook/Stanford Research: “What Makes Good Conversation?: How controllable attributes affect human judgments“ SIKM Leaders Conversational AI 15 Goals and Previous research FB authors used six variables: Independent: 1. interestingness, 2. inquisitiveness, 3. repetition, 4. specificity, 5. question-asking, Dependent: 6. humanness and 7. engagement. Previous research didn’t grasp conversation: Shorter dialogue (Q&A) affords crude evaluation. Single dependent variable Approach (used PersonaCh at content) Used conditional training (CT) and weighted decoding (WD) to control repetition, specificity, and response-relatedness. CT controls at the dialogue, rather than utterance, level, and WD uses just in time vocabulary limiting, based on the score for each possible “next word.” Researchers trained originally on 2.5MM Twitter message-response pairs Training on the PersonaChat dataset: 8,939 conversations and 955 personas. Instructions: Each participant has persona. “Gets to know one another” In 6-8 turns. Experiment: 1,000 conversations and, 100 personas for evaluation, Findings 1. Good conversation is about balance (repetition, specificity, question-asking) 2. Interestingness, listening, and inquisitiveness are important determinants of humanness and engagement ratings. 3. Could be “engaging” even if not “human”! Conversational AI and AI for Conversation
  16. 16. Facebook/Stanford Research: “What Makes Good Conversation: How controllable attributes affect human judgments” (cont’d) 16 • Source: Facebook research, “What Makes Good Conversation: How controllable attributes affect human judgments,” North American Chapter of the Association of Computational Linguistics, See, Abigail, Stephen Roller, Douwe Kiela, and Jason Weston, 7/28/19. • https://research.fb.com/publ ications/what-makes-a-good- conversation-how-controllab le-attributes-affect-human-ju dgments/ Conversational AI and AI for Conversation
  17. 17. Columbia/Motorola Research: 4 Discussion disciplines Skifstad and Pugh, “Beyond netiquette: Discussion discipline drives innovation” (In Smarter Innovation, Ark Group, 2014). Discussion discipline Description 1. Integrity Use true voice, research views, Ask questions that propel 2. Courtesy Respect others and forum. 3. Inclusion Broaden the perspective. Explain terms, call others in. 4. Translation Summarize/use insights generated, and help others with summarizations. Benefit to Collaboration Primarily tonal; builds community and social capital. Primarily content-related; drives innovation. 17 Columbia Information and Knowledge Strategy Master’s Capstone with sponsor Motorola Solutions: Coded over 400 jive posts and regressed productivity and innovation on the use of the four discussion disciplines. Conversational AI and AI for Conversation
  18. 18. Use AI to nudge us into better conversation behaviors 18 https://sps.columbia.edu/news/knowledge-base/four-discussion-disciplines-drive-effective-online-collaboration We could use AI to detect good discussion “moves” and applaud or "nudge." These play out across email and enterprise social networks, Twitter, analyst calls. Conversational AI and AI for Conversation We could improve on public conversation: • Fake news (anti-integrity) • Steamrollling (anti-courtesy) • Closed-mindedness (anti-inclusion) • Certainty, abstraction (anti-translation)
  19. 19. Let’s use our KM experience to change the world through conversation! 19 What if humans were augmented or nudged to improve the tone or accuracy? What if wisdom were compiled and presented back in aggregate? SIKM Leaders at KM World, 2018 Conversational AI and AI for Conversation
  20. 20. Table Discussions: What’s our insight on this topic as a KM community? Each table will discuss for 15 minutes and report out their insights on Conversational AI and AI for Conversation: - use cases - topics - tools - resistance/readiness - ethics / diversity and inclusion - improving quality and access (e.g., through crowd sourcing) 20Conversational AI and AI for Conversation
  21. 21. Table 1: Why AI FOR CONVERSATION now? 21 Why does AI for Conversation matter more today than ever? (E.g., with communications tech availability, demographics, digital commerce) What Conversation Modalities merit our using AI to improve them? (E.g., Enterprise social networks, Twitter, voice-assisted smart devices, comments and replies to blog posts). Conversational AI and AI for Conversation
  22. 22. Table 2: What AI FOR CONVERSATION topics? 22 What Conversation Topics are growing in our companies and civic spaces? Which of those merit our using AI to improve them? For example projects, sales teams, diplomacy, negotiations, civic conversations, leadership development. Conversational AI and AI for Conversation
  23. 23. Table 3: What CONVERSATIONAL AI topics? 23 Why does Conversational AI (Intelligent agents/chat bots) matters now more than ever? For example, customer support, online ordering and logistics, public agencies, safety. Conversational AI and AI for Conversation
  24. 24. Table 4: CONVERSATIONAL AI: Bots are taking over! We need more bots! 24 What Conversational AI Applications are growing, for good? Which are worrisome? What Conversation AI bots do we want to see in the future? Conversational AI and AI for Conversation
  25. 25. Table 5: What concerns us about ethics, diversity and inclusion? 25 What are ethical and/or diversity and inclusion concerns do we need to raise about AI for Conversation and Conversational AI? Conversational AI and AI for Conversation
  26. 26. How might we, as KM’ers, contribute to discover and improve AI for Conversation? For example, can we crowd-source conversation memes (e.g., integrity, courtesy, inclusion, translation)? Table 6: How do we contribute to our AI FOR CONVERSATION future? 26Conversational AI and AI for Conversation
  27. 27. Our work-life is just a series of conversations. Let's live and interact deliberately. Conversational AI and AI for Conversation
  28. 28. Appendix • Conversational AI opportunities and risks • Links to Six leading tech companies Conversational AI teams • Resources 28
  29. 29. Appendix: Opportunities and risks in AI 29 Conversation Conversational AI Conversational AI: Opportunity or Risk? Collective intelligence Crowdsourced, multi-sourced content O: Super-human R: Bias Voice, inflection, pitch “Data,” including these, plus history, comparables, other factors O: Super-human R: manipulation Mindfulness Context awareness O: Helps the forgetful R: De-humanizes Intention (personal purpose) Intention (goal) O: May help complete R: Absolves responsibility Container (trust) History (intelligence) O/R: Trust can be broken “Affect” “Sentiment” O: Can reduce extremism R: Can be manipulated Emergence Bounded randomness O: Innovation R: Lose the human will Accountability, shared fate, shared faith Shaming, isolation O: Enforce/remind R: Lose the higher power Conversational AI and AI for Conversation
  30. 30. Appendix: Six leading tech companies Conversational AI teams 30 Facebook Natural Language Processing and Speech Our natural language processing and speech researchers focus on the interaction between people and computers using human languages, both in diverse written and spoken forms... 6,000 languages, deep learning/neural networks, natural language processing, language identification, text normalization, word sense disambiguation, and machine learning, to break down the problems, and build and deploy robust language translation solutions. Google Language Research Team We advance the state of the art in natural language technologies and build systems that learn to understand and use language in context. Uses ML to detect negative conversation Google's Perspective API and this article. The NY Times uses it to handle comments Microsoft Research Natural Language Processing Group Develops efficient algorithms to process text and to make their information accessible to computer applications. The goal of the group is to design and build software that will analyze, understand, and generate languages that humans use naturally, so that eventually people can address computers as though they were addressing another person. Apple Machine Learning Journal Apple is dedicated to advancing state-of-the-art machine learning technologies. As part of this, we’re building a team of exceptional researchers and engineers who can infuse intelligence into our devices and services to touch the lives of millions of users every day. We’re people with backgrounds in machine learning , deep learning, reinforcement learning, computer vision, and language technologies. Amazon Alexa AI The Alexa AI team contributes to the magic that is Alexa. Our goal is to make voice interfaces ubiquitous and as natural as speaking to a human. .. cutting-edge techniques, like highly scalable deep learning, to train our speech models. ..virtually all fields of human language technology. This WIRED article, which includes interviews with several Alexa scientists, provides good insight into our customer-centric approach to research and development, as does this interview with Rohit Prasad, vice president and head scientist, Amazon Alexa. IBM Watson Research labs for Conversational AI IBM Research is tackling some of AI's greatest challenges. Our scientists and engineers focus on fundamental scientific breakthroughs to help guide the advancement of AI. Browse some of our latest publications spanning a wide range of core AI disciplines. Watson Assistant is an offering for building conversational interfaces into any application, device, or channel. Conversational AI and AI for Conversation
  31. 31. Appendix: Resources • Facebook research, “What Makes Good Conversation: How controllable attributes affect human judgments,” North American Chapter of the Association of Computational Linguistics, See, Abigail, Stephen Roller, Douwe Kiela, and Jason Weston, 7/28/19. https://research.fb.com/publications/what-makes-a-good-conversation-how-controllable-attributes-affect-human -judgments/ • IBM, How conversation (with context) will usher in the AI future https://www.ibm.com/watson/advantage-reports/future-of-artificial-intelligence/ai-conversation.html • Nanalyze, Conversational AI Examples (featuring Clinc) https://www.nanalyze.com/2019/06/conversational-ai-enterprise-applications/ • Nanalyze, “Latest trends in AI” https://www.nanalyze.com/2019/03/latest-trends-artificial-intelligence/ • Forrester Wave on Conversational AI, June, 2019. https://www.forrester.com/report/The+Forrester+New+Wave+Conversational+AI+For+Customer+Service+Q2+ 2019/-/E-RES144416 • Columbia University, Four discussion disciplines http://sps.columbia.edu/information-and-knowledge-strategy/news/four-discussion-disciplines-drive-effective -online • Stanford Stanford Question Answering Dataset SQaD • MIT Technology Review, Scientists have found a way to decode brain signals into speech It’s a step towards a system that would let people send texts straight from their brains. by Antonio Regalado Technology Review, Apr 24, 2019 • MIT Technology Review, Google’s AI can now translate your speech while keeping your voice Researchers trained a neural network to map audio “voiceprints” from one language to another. by Karen Hao Technology Review May 20, 2019 • Quartz, “Snark Attack,” Quartz (2016) SIKM Leaders Conversational AI 31Conversational AI and AI for Conversation

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