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  • 08:00

    REGISTRATION & LIGHT BREAKFAST

  • 09:00

    WELCOME NOTE & OPENING REMARKS

  • PLENARY SESSION

  • THE FOUNDATIONS OF CONVERSATIONAL AI

  • 09:15
    Natalia Konstantinova

    Conversational AI: Pathway to Success

    Natalia Konstantinova - Architecture Lead in BP - BP

    Arrow

    Conversational AI is a powerful technology and can deliver great results if used appropriately. In this talk we would discuss which types of interactions and projects are more suitable for Conversational AI and which are not. We will also cover some recipes to deliver a successful Conversational AI such as attention to conversational design, smart use of data and tracking the right metrics.

    - The types of interactions suitable for conversational AI 
    - Recipes to deliver a successful conversational AI 
    - Smart use of data and tracking the right metrics 

    Natalia Konstantinova is a great enthusiast with over 15 years' experience in the application of Natural Language Processing, Artificial Intelligence, IT and machine learning technologies to real world problems. 

    She is currently a Staff Data Scientist at BP and her role is to develop standards and best practices to accelerate the adoption and implementation of AI enabled solutions, and doing so with the right level of compliance and standards within BP.  

    Natalia got her PhD from the University of Wolverhampton and worked in various fields such as machine translation, ontologies, information extraction, dialogue systems and chat bots. Natalia is a strong believer that modern technology can transform businesses and our everyday life. 

  • 09:45
    Ben Hazel

    Conversational Designers Are Everywhere: How Hiring Internally Helped Admiral Focus On a More Technical Build

    Ben Hazel - Senior Chatbot Conversational Designer - Admiral Group Plc

    Arrow

    With technologies becoming more advanced we had to build our chatbots to keep up, while also fulfilling the customers needs.

    By hiring most of the team internally, this helped us focus on a more technical build as we brought in individuals who already understood Admiral’s goals and objectives, and the processes behind customer’s queries. This in turn helped streamline the design and build of our bots to the companies’ vision and customer’s needs.

    It empowered the whole team to learn themselves how to re-build a chatbot better, sleeker and a design that can be re-used across multiple chatbots.

    - Employing experienced staff members from within has allowed us to accelerate our conversation design and service capability within the bots 

    - Allowed us to focus on learning the tech side to build better chatbots and scale up 

    - “People who like what they do, do it better” - Admiral’s culture of enriching the staff to develop whilst also striving and maintaining excellent customer service has helped us make sure we are getting better all the time at building better chatbots 

    Senior Chatbot Conversation Design working specifically with Dialogflow ES & CX and LivePerson's conversation builder. Worked in customer service for 12 years previously.

     

  • Michael Archer

    Michael Archer - Conversational Designer - Admiral Group Plc

    Arrow

    With technologies becoming more advanced we had to build our chatbots to keep up, while also fulfilling the customers needs.

    By hiring most of the team internally, this helped us focus on a more technical build as we brought in individuals who already understood Admiral’s goals and objectives, and the processes behind customer’s queries. This in turn helped streamline the design and build of our bots to the companies’ vision and customer’s needs.

    It empowered the whole team to learn themselves how to re-build a chatbot better, sleeker and a design that can be re-used across multiple chatbots.

    - Employing experienced staff members from within has allowed us to accelerate our conversation design and service capability within the bots 

    - Allowed us to focus on learning the tech side to build better chatbots and scale up 

    - “People who like what they do, do it better” - Admiral’s culture of enriching the staff to develop whilst also striving and maintaining excellent customer service has helped us make sure we are getting better all the time at building better chatbots 

    Enthusiastic about developing new skills to implement A.I. solutions which benefit both business and customer.


     

  • 10:15

    Personalising Information with Reactive and Proactive Engagement

    Arrow

    - Reactive vs Proactive – what's the difference and what is their importance for conversational AI? 

    - Use cases of both types of engagement 

    - Framing the expectations of the customer and creating effortless conversation 

  • 10:45

    COFFEE & NETWORKING BREAK

  • STREAM 1

  • ADVANCES IN NATURAL LANGUAGE PROCESSING

  • 11:15

    AI Assistants: The Future Sound of Conversation

    Arrow

    - Applying NLP in AI assistants to improve your service experience 

    - Investigating the current challenges and future direction for chatbots 

    - How to measure NLP performance 

  • 11:45
    Andrew Carpenter

    Innovating With Chatbots And AI in A Restricted (Large Organisation) Environment

    Andrew Carpenter - Chatbots and AI Manager - Virgin Media O2

    Arrow

    - It is possible to innovate and grow a new channel even within the confines of a larger organisation 

    - Be agile… but take your stakeholders on the journey with you! 

    - Innovation in the early stages can be fast with lots of quick wins… once its more mature then the stakeholders you’ll have brought on the journey with you will start to be impacted so keep them engaged and track the benefits. 

  • 12:15
    Jyoti Mishra

    Setting Up AI Agents for Success: Defining the Right Metrics

    Jyoti Mishra - Senior Data Scientist (NLP) - Peakon, A Workday Company

    Arrow

    With technical advancement in conversational AI moving at a dizzying pace, it can get overwhelming for businesses to make the right bets and receive the best possible return on their investments. In this presentation, I look forward to sharing some insights on how to approach this by selecting the right outcomes and tracking the right metrics. New AI advancements often create a lot of excitement in tech enthusiasts and early adopters but may also make a lot of conservative business leaders uncomfortable at the thought of investing in such technologies that have a level of uncertainty associated with it. Does the recent innovations in the space of Conversations AI like OpenAI's ChatGPT improve the success rate of conversational AI technology?

    - Removing the overwhelming feeling of new technical advancements in conversational AI 
    - Selecting the right outcomes and tracking the right metrics 
    - Does the recent innovations in the space of conversations AI improve the success rate of conversational AI technology? 

    With around 10 years of experience in tech Industry and most of those years focused on Natural Language Processing (NLP) ranging from but not limited to semantic search, conversational AI, knowledge graphs, ontology development, recommendation engines, Jyoti has worked with companies ranging from very early stage startups to big multinational organisations. Jyoti is a T shaped professional and has worn different hats while solving NLP problems ranging from User Research, Product Management, Roadmap Development, Key Metrics Identification, Data Governance, Data Quality and Integrity, Data Security to implementing latest research papers in NLP domain, productizing cutting edge NLP solutions, working on backend engineering to implement NLP models, DevOps, MLOps, Data Engineering and ML/NLP Engineering. Jyoti has enabled non technical teams and stakeholders to make informed decisions throughout NLP product lifecycle to make efficient use of resources. She has also worked along side Legal, Privacy, Security, Marketing, Competitive Intelligence teams to enhance user privacy and also attain a leading position in the market.

  • 12:45

    LUNCH

  • INFRASTRUCTURE & FRAMEWORKS

  • 13:45
    Somnath Biswas

    Use Of Large Language Models For Better Job Search Through Conversations

    Somnath Biswas - Head of Product - Conversations - TotalJobs

    Arrow

    Job Search, when compared to most other online activities, has a vastly higher potential of being life altering and is usually in equal measure a lonely activity. The use of conversational AI, especially the inclusion of Large Language Models ( for instance GPT-3/ChatGPT models, Sparrow, Blender Bots etc), allows for the automated job search conversations to be far more engaging, supportive, and personalized compared to traditional interfaces. Large language models, however present their own challenges as in terms of fine tuning with enterprise specific data, hallucinations hindering reliability and cost. Some practical work arounds exit, but for now only certain use cases will see inclusion in Enterprise grade solutions. However, conversational interfaces in JobTech domain are bound to see significant progress in the future.

    - Why conversational AI is best suited for JobTech given the unique nature of job search which requires multiple engagements and has softer aspects inherently entrenched. 

    - Contemporary Large Language Models, a quick comparison of the same and top use cases from a Job Tech perspective – with insights from our implementations

    - Key challenges faced when building Enterprise grade solutions using Large Language Models and potential work arounds explored by us.

    Somnath Biswas has been working on enterprise and retail digital products for the past 20+ years, working with Tier 1 consultancies and multiple startups including his own in the enterprise conversational AI space. His products have spanned across Telecommunications, Financial services, Healthcare, Regulatory & Compliance and JobTech domains. For the past 6-7 years he has been building core ML and NLP products for the likes of NatWest, IQVIA, Amazon and most recently with the TotalJobs Group, where he heads the conversational products domain.

  • 14:15

    Optimising Workflows Using No-Code/Low-Code Platforms

    Arrow

    - Use cases of No-Code and Low-Code 

    - Exploring the benefits and drawbacks of this platform 

    - Which one would be better for your company?

     
  • 14:45
    Aaron Brace

    Chatting Up A Marketplace with Conversational AI

    Aaron Brace - Conversational AI Analyst - Yell

    Arrow

    As Yell (formerly Yellow Pages) evolves into an online marketplace where businesses and customers can connect, our virtual assistant Hartley exists in many facets of our ecosystem. Hartley can be customer or business-facing; can answer Yell account and product queries, support interactions with our marketplace, and facilitate conversations between customers and businesses, as well as with Yell’s customer care agents. Yell’s Conversational AI team are taking a data-first approach, using a unique blend of Conversational AI tools by LivePerson, HumanFirst and OpenAI to help Hartley develop and integrate further into our ever-growing marketplace.

    - Experiment with AI for non-traditional applications 
    - Don’t be afraid to use third-parties for specialist resources 
    - Design a data-centric monitoring system for all new features, and always have a backup plan 

    In the past decade, Yell (formerly Yellow Pages) transitioned from printed telephone books to an online directory - and now, its evolving into a marketplace where businesses and customers can connect. We're building a messaging-focused ecosystem, and our virtual assistant, Hartley, is adapted for several use-cases across the Yell website and app, and is available on web, by SMS, and some native in-app messaging channels.

    A Conversational AI Analyst at Yell, Aaron has a Master’s in Data Science and focuses on how data and insights gathered from Hartley’s interactions with users can be used to tackle pain-points and improve customer experiences.

     

  • Andrew Watkinson

    Andrew Watkinson - Conversational AI Analyst - Yell

    Arrow

    As Yell (formerly Yellow Pages) evolves into an online marketplace where businesses and customers can connect, our virtual assistant Hartley exists in many facets of our ecosystem. Hartley can be customer or business-facing; can answer Yell account and product queries, support interactions with our marketplace, and facilitate conversations between customers and businesses, as well as with Yell’s customer care agents. Yell’s Conversational AI team are taking a data-first approach, using a unique blend of Conversational AI tools by LivePerson, HumanFirst and OpenAI to help Hartley develop and integrate further into our ever-growing marketplace.

    - Experiment with AI for non-traditional applications 
    - Don’t be afraid to use third-parties for specialist resources 
    - Design a data-centric monitoring system for all new features, and always have a backup plan 

    In the past decade, Yell (formerly Yellow Pages) transitioned from printed telephone books to an online directory - and now, its evolving into a marketplace where businesses and customers can connect. We're building a messaging-focused ecosystem, and our virtual assistant, Hartley, is adapted for several use-cases across the Yell website and app, and is available on web, by SMS, and some native in-app messaging channels.

    Andrew joined Yell’s team of Conversational AI Analysts after completing a Master’s in Computer Vision. His focus is on NLU performance and introducing new conversational technologies into our workflow to improve perception of Hartley’s intelligence.

     

  • 15:15

    COFFEE & NETWORKING BREAK

  • 15:45
    Michael McTear

    Exploring the Future of Conversational AI: Traditional Design and Generative Approaches

    Michael McTear - Emeritus Professor - Ulster University

    Arrow

    As Conversational AI continues to evolve and become more prevalent in our daily lives, it is important to examine the different approaches that are being taken to design and develop these systems. In this talk we will review two different strands of conversational AI: traditional conversation design and generative AI. The first part of the talk will outline the strengths and limitations of each approach and discuss their potential risks and challenges. In the second part we will explore some of the exciting possibilities of generative AI, including its potential to revolutionize application areas such as customer service, healthcare support, and content creation. The talk will conclude with a brief look at how traditional approaches based on best-practice guidelines are being combined with approaches based on generative AI in a large R&D project in which I am currently involved.

    - There are two distinct strands in conversational AI, one employing traditional methods of conversation design and development based on best practices, and the other based on recent advances in generative AI in which large language models are trained to generate conversations automatically 

    - Both approaches have strengths as well as limitations and it is important to consider these issues when developing a conversational assistant 

    - Generative AI is an exciting new development in conversational AI that has the potential to revolutionize our approach to developing more powerful conversational assistant

    Michael McTear is an Emeritus Professor at Ulster University with a special interest in spoken language technologies. He has been researching in the field of spoken dialogue systems for more than 20 years and is the author of several books, including Spoken Dialogue Technology: Toward The Conversational User Interface (Springer, 2004), Spoken Dialogue Systems (Morgan and Claypool, 2010), with Kristiina Jokinen, The Conversational Interface: Talking to Smart Devices (Springer, 2016), with Zoraida Callejas and David Griol, and Conversational AI ( Morgan & Claypool 2020). Michael has delivered keynote addresses and tutorials at many academic conferences and workshops, including SpeechTEK, Conversational Interaction, ProjectVoice, REWORK AI Assistant Summit, the European Chatbot Conferences, and the Altrusia Conversational AI and Customer Experience Summits. Currently Michael is involved in several research and development projects investigating the use of conversational agents in socially relevant projects such as mental health monitoring and home monitoring of older adults.

  • 16:15

    PANEL: Automated Speech Recognition in IoT Devices. Are They the Future?

    Arrow

    - Why is the technology so popular and what’s causing the shift towards voice? 

    - Voice-first technology is enhancing the customer experience by adding convenience to communication 

    - Combining IoT capabilities with speech recognition technology to meet the shifting consumer demands and unlock business advantages 

  • 17:00

    NETWORKING RECEPTION

  • 18:00

    END OF DAY 1

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  • 08:00

    REGISTRATION & LIGHT BREAKFAST

  • 09:00

    WELCOME NOTE & OPENING REMARKS

  • REAL-WORLD APPLICATIONS OF CONVERSATIONAL AI

  • 09:15
    Rahul Agrawal

    Persuasive Ads: Conversational AI Meets Computational Advertising

    Rahul Agrawal - Senior Director AI - ShareChat

    Arrow

    Conversational AI has enabled interesting human computer interaction scenarios. In this talk we discuss one such unique solution space where we leverage conversational AI to personalize to the users and deliver unique advertising interfaces to them. The current applications of conversational AI focuses on applications where humans initiate a conversation with a specific query in mind. We extend conversational AI to scenarios where computers can initiate a conversation with humans and deliver advertising messages back to them. We focus on unique challenges that confront such a system and how we can leverage signals from user interactions to model latent intent of the users and orient them towards task completion.

    - How to model task completion through conversations 
    - How to model latent intents and conversation starters 
    - Impact of modeling relevance of conversation along with objectives around task completion 

    Rahul Agrawal is a senior director AI at Sharechat where he leads a team of 40+ machine learning engineers and scientists to build the computational advertising platform. Prior to Sharechat, he has worked at Meta, Microsoft Bing, Yahoo! Labs, and Veveo. He has 18+ years of experience in building large scale recommendation systems, natural language understanding/generation, computational advertising, and large scale ML on graphs.

  • 09:45
    Abanoub Rodolf Boctor

    The Future Of Work At Sanofi: How Chatbots Are Revolutionizing Internal Communications

    Abanoub Rodolf Boctor - Head of Architecture | Chatbot Project Manager - Sanofi

    Arrow

    At Sanofi, we have implemented chatbots to improve the way our employees communicate and get work done. Our chatbots are helping employees to quickly and easily access HR information, request time off, and submit expenses, freeing them up to focus on more important tasks. Additionally, our chatbots are enabling cross-functional and cross-border collaboration, making it easier for teams to work together and share information regardless of location. In this presentation, we will share case studies and best practices for implementing chatbots in the workplace and discuss the benefits we have seen at Sanofi. Attendees will learn how chatbots can help to improve efficiency, increase productivity, and create a better work experience for employees.

    - Implementing chatbots can help to improve efficiency, increase productivity, and create a better work experience for employees.
    - To be successful, chatbots must be continuously monitored and updated to ensure that they are delivering value and meeting the evolving needs of users.
    - Chatbots have the potential to transform industries and the way we work, and it is important for organizations to stay informed and embrace new technologies as they emerge.

    Rodolf is responsible for the architecture of chatbots at Sanofi, having gained four years of experience in the field. He has previously worked at Wizz Air, where he was part of the team who created the chatbot Amelia, and at Artive, where he contributed to the development of the SCAI chatbot platform. Rodolf has also partnered with various top-tier AI applications, such as synthesia.io and IBM Watson Assistant, and has expertise in natural language processing, machine learning, and artificial intelligence. Currently, he is working at Sanofi on a mission to create and develop a standalone multi-intent chatbot to provide the best possible experience for Sanofi employees.

     

  • 10:15

    Digitalising Personalisation to Meet Customer Demand

    Arrow

    - Understanding your customer’s personality 

    - Personalisation enables brands to increase customer engagement, improve loyalty, increase sales and completely understand their customers 

    - How does personalisation drive customer conversion? 

  • 10:45

    COFFEE & NETWORKING BREAK

  • VOICE TECHNOLOGY

  • 11:15

    Essential Fundamentals of Voice Interaction and Conversation Design

    Arrow

    - Developing a strategy for voice is challenging 

    - The architecture needed to develop your own voice assistant 

    - Using human conversation patterns to design more natural digital interactions 

  • 11:45
    Fang Xu

    Leveraging Question Answering for Enhancing Human-Computer Interaction in Voice Platform

    Fang Xu - Senior Data Scientist/AI Expert - Deutsche Telekom

    Arrow

    Question answering technology has the potential to improve customer service by providing instant and accurate answers to inquiries. In this talk, we will explore the latest developments in question answering technology, including the use of large language models and neural networks, and how we build German question answering services for our voice platform. In this talk, we will discuss the benefits of using question answering, as well as the challenges and limitations of current technology.

    - Question answering system for a voice platform
    - Is multilingual better than mono-lingual models for NLP ?
    - Challenges and limitation of current technologies

    As a Senior Data Scientist at Deutsche Telekom, Fang Xu specializes in AI technologies for Natural Language Processing (NLP). Having completed his Ph.D in the field, he brings extensive project experience to the table, having worked on a wide range of topics such as question answering, text ranking, and chatbots development. Most recently, he worked on question answering systems for Telekom's Magenta voice speaker and platform. He is not only involved in ideation and research, but also in bringing these ideas to life, taking them from early prototypes to scalable production.

     

     
  • 12:15

    Applying text-to-Speech (TTS) for Improved Integrated Voice Technology

    Arrow

    - High quality TTS voice that sounds similar to a human voice will improve comprehension 

    - Selecting a bi-modal TTS program to highlight the presented word as it is pronounced out loud 

    - How to differentiate your brand with a customised, realistic voice generator with different speaking styles and emotional tones  

  • 12:45

    LUNCH

  • RESPONSIBLE AI

  • 13:45
    Jon Howard

    Safeguarding and Duty of Care Requirements For Conversational Interfaces

    Jon Howard - Executive Product Manager (AI, Machine Learning, Data and Innovation) - BBC

    Arrow

    The proliferation of conversational AI technology is transforming the way we interact with machines and access information. However, as its usage becomes more prevalent, it is imperative that we consider the implications on user's safety and privacy. This session will cover the necessary facets of safeguarding and duty of care with regards to conversational models. The importance of privacy and data protection, the need for transparency in AI systems, the potential for bias and discrimination, the requirement for explainability, the need for safety, the role of human oversight, and the importance of continuous monitoring - by understanding these key aspects, we can ensure that systems are used responsibly and ethically.

    - The ethical considerations
    - Practical steps that should be taken
    - The core principles to apply that will ensure that conversational interfaces are employed in a safe and responsible manner.

    Jon is an Executive Product Manager for BBC Children’s and Education with a responsibility for bringing the benefits of new technologies to young audiences. He has worked with AI, intelligent systems and digital products for over 15 years. Jon was a member of the core team that authored the BBC Machine Learning Engine Principles, as well as delivering many successful innovative awarding-winning products.

  • 14:15

    PANEL: The Impact and Importance of Ethics in Conversational AI

    Arrow

    - Building a framework of ethics 

    - Ethical concerns in conversational AI differ depending on the application domain, target user group and goals of the agent 

    - Encouraging contextual and plural approaches over a set of abstract principles to develop ethical and responsible AI 

  • 15:00

    NETWORKING RECEPTION

  • 16:00

    END OF SUMMIT