08:30
REGISTRATION
Nikola Mrksic - PolyAI
Democratising Conversational AI
Personal assistants such as Alexa and Siri are everywhere, but have trouble handling any tasks more complex than setting alarms or playing songs on Spotify. PolyAI is a new London-based startup with a next generation platform for building voice-based agents. We use machine learning to handle complex tasks across different application domains, in a wide array of world languages. In this talk, I will present our Wizard-of-Oz data collection framework, which allows us to collect high-quality datasets and train our models at a fraction of the cost compared to traditional data labelling approaches.
Nikola Mrksic is the CEO and Co-Founder of PolyAI, a London-based startup developing the next generation machine learning platform for building conversational user interfaces. Our technology enables the development of machine learning powered chatbots or voice-based agents which perform tasks across many applications, in a wide array of world languages. Nikola completed his PhD at the University of Cambridge, working with Professor Steve Young. He also worked as a machine learning researcher with the Apple Siri team in Cambridge. Before that, he was the first technical hire at VocalIQ, a Cambridge-based dialogue systems startup acquired by Apple in 2015.
NLP AND VOICE RECOGNITION IMPLEMENTATION
09:30
Elena Kochkina - University of Warwick
Opinion Mining Using Heterogeneous Online Data
Elena Kochkina - University of Warwick
Opinion Mining Using Heterogeneous Online Data
Understanding public opinion is important in many applications, such as improving company's product or service, marketing research, recommendation systems, decision and policy making and even predicting results of elections. Social media is a very powerful tool to transfer information and express emotions for users and a rich source of data that enables researchers to mine public opinion. In this talk I will describe different lines of work within our group, including rumour stance and veracity classification classification, predicting well-being based on heterogeneous user generated data and target-dependent sentiment recognition. False information circulating on social media presents many risks as social media is used as a source of news by many users. Detecting rumourous content is important to prevent the spread of false information which can affect important decisions and stock markets. Rumour stance classification is considered to be an important step towards rumour verification as claims that attract a lot of scepticism among users are more likely to be proven false later. Therefore performing stance classification well is expected to be useful in debunking false rumours. In our work we classify a set of Twitter posts from conversations discussing rumours as either supporting, denying, questioning or commenting on the underlying rumours. We propose a LSTM-based sequential model that achieves state-of-the-art results on this task through modelling the conversational structure of tweets. The task of automatically assessing well-being using smartphones and online social media is becoming of crucial importance, as an attempt to help individuals self-monitor their mental health state. In the current work, a multiple kernel learning approach is proposed as a mental health predictor, trained on heterogeneous (text and smartphone) user-generated data. The results reveal the efficiency of the proposed model and sequential approaches for time series modelling (i.e., LSTMs) are proposed for future work. Opinion mining is usually achieved by determining the overall sentiment expressed. However, inferring the sentiment towards specific targets is limited by such an approach since a Social Media posts may contain different types of sentiment expressed towards each of the targets mentioned. Our work on target-specific sentiment recognition goes beyond tweet-level or single-target approaches, and proposes a multi-target-specific sentiment classification model, which explores the context around a target as well as syntactic dependencies involving the target.
I am a Computer Science PhD student at the University of Warwick supervised by Dr. Maria Liakata and Prof. Rob Procter. Currently I am based at the Alan Turing Institute in London. My background is Applied mathematics and Complexity science. I work in the area of Natural Language Processing. My research is focused on Rumour Stance and Veracity Classification in Twitter conversations. I am studying the benefits of utilising the conversation structure in supervised learning models.
Michael McTear - Ulster University
Modelling conversation for chatbots
Modelling conversation for chatbots remains a challenge. For natural language understanding the major companies have converged on models involving intent identification and entity extraction. However, for conversation a wide range of different terminologies and models has been proposed. This talk will examine the conversation models of the main chatbot frameworks to answer questions such as: To what extent are they similar? Do current approaches go beyond hard-coded conversation flows of “happy path” dialogs to model conversational phenomena such as follow-up questions, changes of topic, out-of- scope utterances, and other types of edge case? What are the desiderata for intelligent conversational agents?
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, and The Conversational Interface: Talking to Smart Devices (Springer, 2016), with Zoraida Callejas and David Griol.
Yariv Adan - Google Assistant
Natural UI
AI is powering the next paradigm shift in Human-Machine Interaction - the Natural User Interface. In his talk, Yariv Adan will provide an insider perspective on this paradigm shift, and will demo and explain the technology driving it, using the Google Assistant.
For the past 10 years, Yariv has been leading products and product teams at Google Zurich. In his current role, he is leading the Zurich product team working on the Google Assistant. Prior to this role, Yariv worked on a wide range of products, including proprietary Google infrastructure, privacy and security, products designed for the Emerging Markets, and even the notorious non skippable ads on YouTube. Before joining Google, Yariv was an engineering manager in various Israeli start-ups and companies.
10:45
COFFEE
CHALLENGES OF BUILDING AI ASSISTANTS
Nikola Mrksic - PolyAI
Democratising Conversational AI
Personal assistants such as Alexa and Siri are everywhere, but have trouble handling any tasks more complex than setting alarms or playing songs on Spotify. PolyAI is a new London-based startup with a next generation platform for building voice-based agents. We use machine learning to handle complex tasks across different application domains, in a wide array of world languages. In this talk, I will present our Wizard-of-Oz data collection framework, which allows us to collect high-quality datasets and train our models at a fraction of the cost compared to traditional data labelling approaches.
Nikola Mrksic is the CEO and Co-Founder of PolyAI, a London-based startup developing the next generation machine learning platform for building conversational user interfaces. Our technology enables the development of machine learning powered chatbots or voice-based agents which perform tasks across many applications, in a wide array of world languages. Nikola completed his PhD at the University of Cambridge, working with Professor Steve Young. He also worked as a machine learning researcher with the Apple Siri team in Cambridge. Before that, he was the first technical hire at VocalIQ, a Cambridge-based dialogue systems startup acquired by Apple in 2015.
11:45
Hamza Harkous - École Polytechnique Fédérale de Lausanne & Polisis
Can We End the Era of Unreadable Privacy Policies with AI?
Hamza Harkous - École Polytechnique Fédérale de Lausanne & Polisis
Can We End the Era of Unreadable Privacy Policies with AI?
With the length and complexity of today's privacy policies, it's no surprise that they are rarely read. So what if AI can read these policies on our behalf, simplify them, and let us know what to do about them? That is why we created Polisis, the first advanced AI platform for analyzing privacy policies, and PriBot, the first AI assistant for automatically answering questions about these policies. In this talk, I'll be making the case for using deep learning to alleviate the huge cost for understanding these complex documents in the case of both businesses and individuals. I'll also outline our vision towards turning these documents from a costly requirement into a competitive business opportunity.
Hamza Harkous is a Postdoctoral Researcher at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. He is the creator of Polisis, the first and most advanced AI platform for automated analysis of privacy policies. He also created PriBot, the first chatbot for privacy policies. He obtained his Ph.D., from EPFL in 2017, where he worked on data-driven usable privacy. His general interests are at the intersection of deep learning, privacy and human computer interaction. He is currently working on taking this research to the next deployment stage. This will provide the opportunity for businesses to automate the full workflow of privacy practices' assessment.
CREATING PERSONALITY IN AI ASSISTANTS
Marc Paulina - Google
Empathic Design for Conversational Interfaces
We are in an age of blending horizons and blurring devices brought alive by ambient assistive companions. Everything is talking, everything has a brain...and we respond to these "presences" with many of the same feelings and reactions as if they were sentient beings. It's not our fault. It's 150,000 years of human hardwiring telling us that a speaking thing is not just an “it,” it’s alive and aware and connecting with us. With “ears” and “eyes” sensing, it becomes even more emotionally compelling and/or complex.
How might we design for Emotional Intelligence to make people feel that these experiences are useful, familiar, comfortable, positive, supportive and trust-worthy.
Marc is a Senior User Experience Designer at Google, focusing on multimodal (voice and touch) conversational experiences for the Google Assistant across a range of surfaces from mobile to wearables.
12:25
Gary McKeown - Queen's University Belfast
Creating Genuinely Interesting Conversational Partners
Gary McKeown - Queen's University Belfast
Creating Genuinely Interesting Conversational Partners
Conversational agents and digital assistants are increasingly becoming part of our lives. However, current agents are usually dry data delivery mechanisms bereft of any of the charm or wit that we prize within human interlocutors. What does it take to create conversational agents that can be genuinely interesting conversational partners? I suggest that the function of human conversation is not to deliver useful information, but to display mind-reading and perspective-taking abilities–to demonstrate ourselves to be astute socio-political actors. This can be achieved through showing we know another person's goals and desires, and by empathising and understanding. It can also be done through the creative demonstration of an ability to combine concepts in the minds of other that they had not yet noticed were related–using analogy, humour, and story-telling. Therefore, to create engaging conversational agents we must focus on the development of these empathic and creative abilities. We need to ensure that agent models can develop conversational common ground, emotional connection and empathy, and be creative and humorous. These are not simple tasks but they are necessary if digital agents are to become truly engaging conversational partners capable of developing longer term relationships with humans that humans seek to sustain.
Gary McKeown is a senior lecturer and social psychologist in the School of Psychology, Queens University Belfast. He has a primary research and theoretical interest in human communication and social interaction. His research profile is interdisciplinary with both theoretical, experimental and methodological papers in psychology journals and also many within the domains of social signal processing and affective computing. Often this research involves understanding natural human communication to inform the development of embodied conversational agents. Building on a long history of emotion and affective computing research in the School of Psychology – including the HUMAINE network, he had important roles in the SEMAINE, ILHAIRE project and within the SSPNet network. He has produced a theoretical account of the evolution of human communication with a particular emphasis on mind-reading and perspective-taking known as the Analogical Peacock Hypothesis; this has led to research work in understanding laughter, humour and storytelling. His research interests have led to many collaborations with non-academic partners, particularly commercial and industrial partnerships for the transfer of knowledge and techniques to commercial settings. From a methodological perspective, the fields of social signal processing and affective computing address challenging data collection issues from a behavioural science stance–often using dynamic scenarios with multiple streams of synchronised information. This requires new ways of thinking about data and novel statistical approaches to develop analyses that can usefully address social science questions. Dr McKeown has been actively involved in the creation of both new data gathering techniques and the statistical approaches required to address them.
12:45
LUNCH
13:55
Adi Chhabra - Vodafone
Evolution of AI & Machine Learning in Customer Experience - Beyond Interfaces
Adi Chhabra - Vodafone
Evolution of AI & Machine Learning in Customer Experience - Beyond Interfaces
The evolution of Machine learning is directly proportional to the customer believing in the non-existence of a machine in between. With deep learning and neural network implementation, the traditional ML models are becoming dated. Often when a new technology has its breakthrough; it’s impact is only felt in hindsight. But it's different with Artificial Intelligence and Machine Learning. Let’s talk about how ML powered Chatbots add value to the customer experience. From demand generation to fulfilment, all behind a seamless customer experience.
Adi is a Product Manager with over 11 years of experience across Fashion, E-commerce and Technology Industries. He is currently leading Product Management and Innovations for Vodafone UK in the space of Artificial Intelligence and Machine Learning. He is passionate about solving problems through design thinking, big data and automation. An avid reader of consumer technology and applied mathematics, he often spends his time thinking about how to merge the two to make consumer experiences worth their while. Adi holds an MBA degree from Lancaster University Management School.
HUMAN-COMPUTER INTERACTION
Artem Rodichev - Luka
Building an AI friend
Chatbots should have empathy. They need to have the ability to identify the user’s emotions from the conversation, to detect how emotions evolve over time, and to understand the user’s emotional needs. Artem will talk about how chatbots can simulate emotional connection with users using different modalities, including text, speech, and vision, and how we can use deep learning to build the best friend for a human.
Artem Rodichev is a Head of AI at Luka, a company that is best known for its recent app called Replika - an AI friend for emotional growth and awareness. Artem earned M.Sc. degree in Applied Mathematics and Computer Science from Moscow State University. Before Luka, he worked at top Russian IT companies such as Yandex, Mail.ru, and ABBYY developing NLP-driven products. Artem's area of research interest includes Conversational AI and Deep Learning techniques for modeling human conversation.
14:35
Zafeirios Fountas - Imperial College London & Emotech
Imitating Human Behaviour with Brain-Inspired A.I.
Zafeirios Fountas - Imperial College London & Emotech
Zafeirios is a mathematician/computer scientist with a passion for neuroscience, biologically inspired A.I. and cognitive robotics. Currently, he works as a researcher in the Department of Computing of Imperial College London investigating the neural correlates of human time perception. Additionally, he works at Emotech LTD, where he is building the A.I. system of the personal robot Olly. He received his Ph.D. in computational neuroscience from Imperial College, where he focused on the relation between brain oscillations, our ability to select between multiple prospective actions and motor symptoms of Parkinson's disease.
14:55
COFFEE
15:30
Denys Bernard - Airbus
Operator/AI Assistant Interaction: Challenges from a User Perspective
Denys Bernard - Airbus
Operator/AI Assistant Interaction: Challenges from a User Perspective
So called "cognitive assistants" are flourishing, but how to evaluate the benefit/cost ratio of introducing that technology into aeronautical operations? How far can cognitive assistant help operators such as pilots or mechanics at work? What impact can we expect on human-system performance? Our hypothesis is that cognitive assistants will be useful and accepted if and only if they implement a certain level of cognitive interaction with the human operator. First we question what kind of human cognitive functions can actually be supported to by a digital assistant to increase its performance at work. Then we propose a set of basic principles of cognitive interaction inspired by human sciences, e.g. cognitive philosophy and sciences of language. That definition is agnostic regarding technology. Our intention is to shape the evaluation and the specification of future cognitive assistants from a user perspective. Our purpose in this summit is to spark a discussion on the ambition and the feasibility of "natural" cognitive interaction between human operators and cognitive assistants.
Denys Bernard is an aeronautical engineer and doctor in Computer Sciences. He has relentlessly worked in research and development activities for decision support systems - both on board and on ground - particularly for aircraft maintenance. His main domains of interest are: diagnostic; planning; knowledge extraction and representation; decision making. He is now focused on the application of cognitive technologies as the foundation of virtual assistants for mechanics and cockpit crew.
Mirco Musolesi - UCL
Towards Anticipatory Mobile Computing: Challenges & Opportunities
Mobile phones are increasingly equipped with sensors, such as accelerometers, GPS receivers, proximity sensors and cameras, which can be used to sense and interpret people behaviour in real-time. Novel user-centered sensing applications can be built by exploiting the availability of these technologies. Moreover, data extracted from the sensors can also be used to model and predict people behaviour and movement patterns, providing a very rich set of multi-dimensional data, which can be extremely useful, for instance, for marketing applications and health interventions. In this talk I will discuss the scenarios that are opened by the emergence of this new paradigm of mobile anticipatory computing and I will present our ongoing work in this area.
Mirco Musolesi is a Reader in Data Science at the Department of Geography at University College London and a Turing Fellow at the Alan Turing Institute. At UCL he leads the Intelligent Social Systems Lab. His research interests include intelligent systems design, applied machine learning, human behaviour and social systems modelling, and digital health. He is interested in developing mathematical and computational models as well as implementing real-world systems based on them. More details about his research profile can be found at: http://www.ucl.ac.uk/~ucfamus/
AI ASSISTANTS - WHAT ARE WE IN FOR IN THE LONG-TERM?
16:10
FIRESIDE CHAT: AI FOR SOCIAL GOOD
Janet Bastiman - Storystream
Dr Janet Bastiman is Chief Science Officer at Storystream where she heads up the AI division. She has extensive experience in leading teams and building AI systems. With over 10 years experience at C-level, she has taken abstract concepts to innovative scalable products at multiple companies. A STEM polymath, Janet brings multidisciplinary ideas to the departments she leads, forming cutting edge research teams with an eye on delivery that is rarely seen. She has a bachelors and masters degree in Molecular and Cellular Biochemistry from Oxford, and her PhD was in the field of Computational Neuroscience.
Janet is a co-founder of the Tech Women London Meetup group and regularly speaks and writes on various technical subjects. She blogs on maths and technology at http://janjanjan.uk.
Kriti Sharma - Sage
Kriti Sharma, is an artificial intelligence tech entrepreneur, currently building AI that solves real problems facing the world today, from access to emergency services in developing countries to an AI powered financial assistant that helps entrepreneurs around the world. Kriti deeply cares about the ethics of AI and often writes about AI and bot design principles.
16:40
Jochen L Leidner - University of Sheffield
The Brave New World of Data? - Ethical Questions and Case Examples
Jochen L Leidner - University of Sheffield
The Brave New World of Data? - Ethical Questions and Case Examples
Automated information processing has revolutionised business, government and led to changes in society, for example in the way we communicate. Following the "data is the new oil" mantra, many companies offer free services in return for getting access to their users' personal data. Professional services and government departments are working on a digital agenda. In this talk, Jochen will consider the moral side of the new world of data. What ethical principles ought to underpin building systems, doing business, governing citizens from a data privacy perspective? What kind of ethical issues have already happened and will likely happen soon? For example, Eventually, automated 'black box' systems could be making decisions without transparency or recourse in the case of error. I conclude with some suggestions for remedy.
17:00
CONVERSATION & DRINKS
END OF SUMMIT
08:30
REGISTRATION
Bianca Furtuna - Independent
Bianca Furtuna is a freelance Data Scientist. She is passionate about all things data and using new and emerging technologies to deliver data focused solutions with Machine Learning and Artificial Intelligence. Until recently, Bianca was a Data Scientist at Elastacloud, where she built multiple machine learning models for forecasting tasks in the energy sector. Previous to Elastacloud, Bianca was a Technical Evangelist at Microsoft, working with various organisations to help them improve or architect their cloud solutions and support them in implementing Machine Learning and analytics services.
STARTUP SESSION
09:30
Agata Chudzińska - TheBlue.ai
Answering E-Mails in No Time – Short Story of How to Use NLP in Modern Enterprises.
Agata Chudzińska - TheBlue.ai
Answering Emails in No Time – Short Story How to Use NLP in Modern Enterprises
In order to maintain good customer relations, every company have to take care and continuously keep contact with the clients. Almost every bigger enterprise needs therefore a dedicated customer service. Here artificial intelligence comes with help. Mailbot is the answer to current market needs. It is analyzing incoming messages: either complains, order status requests, questions regarding products details or availability and supporting the answer. Using Natural Language Processing the Mailbot is proposing complete message to customer ready to send back. It could integrate with ERP and CRM systems to include current prices, discounts, availabilities in message. Customer Service could spare lots of time having all this information gathered automatically. Mailbot is also able to create complaint in system which could be processed further in separate department.
Agata is a co-founder of TheBlue.AI, company delivering AI solutions for business, specializing in NLP, ML and IP. Cooperation with partners specialized in Business Applications and Mixed Reality allows theBlue.AI to successfully combine newest technologies with deep business understanding. As a head of AI team Agata was creating solutions like Mailbot, TwitterBoard and Chatbot using Machine Learning and Natural Language Processing algorithms. Recently her main responsibilities are focusing on project management of Predictive Maintenance product. In addition she is taking part in designing complex big data architectures as well designing best possible algorithms to handle incoming time series data. Agata enjoys combining in practice her educational background from both business informatics and linguistics to solve business problems applying machine learning algorithms.
09:45
Guillaume Bouchard - Bloomsbury AI
Simplifying the Access to Information Through AI
Guillaume Bouchard - Bloomsbury AI
Bloomsbury AI simplifies the access to information through AI.
The London-based startup company developed algorithms that can learn to answer questions by automatically “reading” textual documents. The approach heavily uses deep learning and can scale to millions of datapoint and has been improved to perform real-time predictions. In this talk, we demonstrate the current ability of machine reading algorithms in different domains and for various degrees of difficulty. One of the most promising applications is our legal product, designed to help lawyers find the information they need much more easily than current approaches based on boolean search and keyword matching. We conducted quantitative experiments that show that the time spent searching for the right answer in a document can be drastically reduced by using machine reading algorithms. Finally, we discuss some insights about the next generation of machine reading algorithms that we can directly reason on legal documents, and even search for extra information when it is missing.
Jay Shah - Kiroku
Automating Expert Note Taking
Kiroku is changing the way computers understand conversational language. We believe that speech to text is not enough, and the next step is deriving the meaning from conversation. Our first product can listen to a conversation between a dentist and a patient during a dental appointment and automatically generate the clinical notes. The models are generic and can be repeated in a variety of industries and applications. In this talk, we will cover the ideas behind how we are building the foundations of this technology, and some of the obstacles we face on the way.
Jay is the co-founder and CTO of Kiroku. Kiroku graduated from the eighth cohort of Entrepreneur First (Europes leading deep tech incubator). Kiroku was listed on TechCrunch as one of the top three companies coming out of EF. Before founding Kiroku, Jay completed his masters in natural language processing and machine learning at the University of Cambridge. His research focused on translating within English, and Kiroku has built on much of this technology to create its first product, giving the company a huge head-start in solving this hugely complex technical challenge.
Mahiben Maruthappu - Cera
Abstract title: Transforming Healthcare using Deep Learning
Ben is a London-based doctor and Co-founder of Cera, a multi-award winning technology company transforming social care. He advised the CEO of NHS England on £100 billion of health spending, co-founding the NHS Innovation Accelerator (NIA) which benefitted 3 million people in its first six months. He has a strong interest in research with over 100 peer-reviewed publications and 50 academic awards. Ben has advised a range of organisations, from startups to multilaterals, including the Swiss government, the Experiment Fund and the WHO. He is Chairman of the UK Medical Students’ Association (UKMSA), and has authored three medical books. Ben was educated at Oxford, Cambridge and Harvard universities. He was the first person from British healthcare to be included in Forbes’ 30under30, was listed in WIRED's top 10 Innovators in Healthcare, and recently ranked amongst the 100 most influential leaders in health technology, globally.
Faisal Khalid - Renters Union
Replacing Lawyers and Real Estate Brokers with AI
In this talk, Faisal will share his experience of building a popular chatbot housing ‘lawyer’, Renters Union. Since launch, the chatbot has helped thousands of Londoners get free, instant, personalised legal advice, saving them from having to hire expensive lawyers. AI has many practical applications, as bots like Renters Union and DoNoPay have shown, and in this session you’ll learn about how you, too, can build practical tools on your own.
Faisal is the Founder and CEO of Renters Union, a popular chatbot ‘lawyer’ that provides free, instant, personalised legal advice to Londoners. It has been covered in TechCrunch, TimeOut, EveningStandard and numerous legal blogs, and been hailed by users as ‘something the Mayor should have built’, ‘BRILLIANT’ and ‘totally rubbish.’ Faisal previously built and sold a fintech venture, and spent several years in banking and private equity, before learning to code and moving to tech. Faisal holds a BA from Harvard University, and MBA from the Kellogg School of Management, and lives in London.
10:50
COFFEE
APPLICATION OF AI ASSISTANTS IN INDUSTRY
11:30
Kamel Nebhi - AIEVE - PECULIUM
Enhancing the Customer Experience Using AI Assistant & NLP
Kamel Nebhi - AIEVE - PECULIUM
Enhancing Cryptocurrency Forecasting by using Deep Learning Sentiment Analysis
Peculium is the first Crypto-Savings platform that combines traditional savings, blockchain technology, cryptocurrency, and artificial intelligence. Indeed, Peculium is a platform that makes use of the AIEVE Artificial Intelligence technology to forecast the market price of several cryptocurrencies and giving real-time saving-portfolios advices.
In this context, AIEVE is based on cutting-edge NLP techniques to extract semantic meaning and sentiment from large volumes of unstructured text from multiple sources such as social media or RSS feeds. In this presentation, we will present a Twitter sentiment analysis pipeline based on CNNs and LSTMs networks using fine-tuned word embeddings. We will show how these techniques help AIEVE to predict the cryptocurrency market with a higher level of accuracy to increase users savings.
Prior to joining AIEVE, Kamel was working as a Senior NLP Data Scientist at First Utility developing AI technology to improve the customer experience. Kamel has also worked at Oxford University Press as a Lead Language Technologist for the Oxford English Dictionary project. During his Ph.D at the University of Geneva in Switzerland, he has been working on several topics such as NLP, Machine Learning and Semantic Web.
11:50
Jan-Frederik Morgentha - Deutsche Telekom Group
Why Conversational Bots Disappoint & How to Build Better Ones
Jan-Frederik Morgentha - Deutsche Telekom Group
Why Conversational Bots Disappoint & How to Build Better Ones
Deutsche Telekom had for several years as other enterprises conversational bots in the market and the end-customer perception was long time not satisfying. But through AI and new interface designs finally conversational bots were accepted by our customers and are going in the lead from all channels as the most favored touchpoint.
Jan is the product & AI engineering lead at Deutsche Telekom Group. He is working with his team on several AI applications from chatbots over call emotion detection to machine learning use cases to enable with this work the European operating businesses of Deutsche Telekom to exceed customer expectations and business goals. Before Deutsche Telekom Jan worked as a project leader at a digital, boutique consultancy in Germany and South Korea. He holds a master degree in Management Information Systems.
12:10
Björn Schuller - Imperial College London & University of Augsburg
Artificial Communication Intelligence 2.0 – The Rise of Socio-Emotional Assistants
Björn Schuller - Imperial College London & University of Augsburg
Artificial Communication Intelligence 2.0 – The Rise of Socio-Emotional Assistants
Today’s AI Assistants and conversational interfaces become increasingly useful, spread, and actually used, but still lack in one major aspect – they still just aren’t emotionally or socially intelligent thus keeping communication still quite different from human-to-human examples. In this talk, the state-of-play in the ongoing ambitions of filling this white spot in virtual agent and assistant tech is demonstrated. We shall go from the noughties’ first fully-fledged audiovisual input/output emotion-enhanced “SEMAINE” system to today’s “ARIA” system the presenter both was a co-developer of and related latest information retrieval agents with growing socioemotional capabilities aiming at more personalised, natural, and engaging user and customer experiences. While deep learning has already been at the core of the first such system, the talk will also highlight the most recent end-to-end learning architectures employed in the field of Affective Computing and Intelligent Interaction. Modalities of interest include textual, acoustic, and visual, but also physiological cues of emotion or social signals. Benchmarks on performances are given from the major challenges in the field as organised by the presenter – AVEC, and ComParE. Emphasis is in particular laid on increasing socioemotional communication intelligence in tomorrow’s automated conversational customer care.
Björn W. Schuller received his diploma, doctoral degree, habilitation, and Adjunct Teaching Professor all in EE/IT from TUM in Munich/Germany. He is a Reader (Associate Professor) and Head of GLAM – the Group on Language Audio & Music at Imperial College London/UK, Full Professor at the University of Augsburg/Germany, co-founding CEO of audEERING, and permanent Visiting Professor at HIT/China. Before, he was Full Professor at the University of Passau/Germany, and with Joanneum Research in Graz/Austria, and the CNRS-LIMSI in Orsay/France. He is a Fellow of the IEEE, President-Emeritus of the AAAC, and Senior Member of the ACM. He (co-)authored 700+ publications (17000+ citations, h-index=64), and is the Editor in Chief of the IEEE Transactions on Affective Computing, General Chair of ACII 2019 and ACM ICMI 2014, and a Program Chair of Interspeech 2019, ACII 2011/2015, ACM ICMI 2013, and IEEE SocialCom 2012. He was honoured as one of 40 extraordinary scientists under the age of 40 by the WEF in 2015, served as Coordinator/PI in 10+ European Projects, is an ERC Starting Grantee, and consultant of companies such as Huawei or Samsung.
12:30
Ziv Baum - Carlson Wagonlit Travel
How CWT used AI to provide White-glove Level of Service
Ziv Baum - Carlson Wagonlit Travel
How CWT used AI to provide white-glove level of service
Despite the hype, AI-based chatbots are still not there... at Carlson Wagonlit Travel (CWT), the world's leading travel management company with over $30B of travel sold annually, deploying a service solely based on NLP and AI to respond to our travelers' needs simply doesn't cut it. CWT prides itself on the high touch customer service it provides to help its millions of travelers navigate through the not-always-pleasant task of business travel. The challenge? How to provide the same high touch service while leveraging new technologies and in particular, conversational interfaces. The solution? A hybrid between chatbot and a human, automating some tasks, but also deploying AI to deflect conversations to humans. The result? High level of satisfaction and improved human agent efficiency. During his talk, Ziv will discuss the challenge, solution, and results in more detail as well as demo CWT’s hybrid approach.
Ziv Baum is a Director of Product in Carlson Wagonlit Travel's Digital team, where he and his team are building products to help travelers through their entire business trip journey. Before joining CWT, Ziv was an entrepreneur and also worked for SAP and Qualcomm. He holds an MBA from Carnegie Mellon's Tepper School of Business and a BSc. from the Technion.
12:50
LUNCH
Aditya Kaul - Tractica
Aditya Kaul is a research director at Tractica, with a primary focus on artificial intelligence and robotics. He also covers blockchain and wearables as part of his research. Kaul has more than 12 years of experience in technology market research and consulting. He is based in London.
Prior to Tractica, Kaul was a practice director at ABI Research, where he led the firm’s Mobile Networks research group. Kaul has also worked as an analyst and team leader at firms including Pioneer Consulting and Evalueserve, and has provided independent consulting services in the areas of Internet of Things, wearables, and smart cities. Kaul started his career as an electrical engineer designing chipsets and wireless networks with stints at Qualcomm and Siemens. Kaul has been a prolific speaker, moderator, and panelist at industry conferences and events, and has appeared frequently in the media including The Wall Street Journal, The Financial Times, Forbes, CNBC, The Motley Fool, VentureBeat, Unstrung, ZDNet, Wireless Week, EE Times, and CommsDesign, among others.
Kaul holds two master’s degrees in engineering, from Colorado State University and Pennsylvania State University, as well as a bachelor’s degree in electrical engineering from National Institute of Technology, Surat in India.
PLENARY SESSION: PRIVACY, SECURITY & ETHICS
14:10
Panel Discussion - Security & Privacy - Plenary Session
Have Security and Privacy Risks Become the Ultimate Obstacle for AI and its Rapid Growth?
Panel Discussion - Security & Privacy - Plenary Session
AI holds great promise but also significant threat. As AI capabilities continue to advance at a rapid pace, so does the risk to both company and consumer. In this panel discussion we will bring together experts in AI security as well as those facing giant risks when advancing AI in their business. How do we keep AI safe from adversaries? How can we guard against mistakes? How do we protect against unintended consequences?
Bianca Furtuna - Independent
Bianca Furtuna is a freelance Data Scientist. She is passionate about all things data and using new and emerging technologies to deliver data focused solutions with Machine Learning and Artificial Intelligence. Until recently, Bianca was a Data Scientist at Elastacloud, where she built multiple machine learning models for forecasting tasks in the energy sector. Previous to Elastacloud, Bianca was a Technical Evangelist at Microsoft, working with various organisations to help them improve or architect their cloud solutions and support them in implementing Machine Learning and analytics services.
Mariarosaria Taddeo - Oxford Internet Institute & Digital Ethics Lab
Dr Mariarosaria Taddeo is Research Fellow at the at the Oxford Internet Institute, University of Oxford, where she is the Deputy Director of the Digital Ethics Lab, and is Faculty Fellow at the Alan Turing Institute. Her recent work focuses mainly on the ethical analysis of cyber security practices, cyber conflicts, and ethics of data science. Her area of expertise is Philosophy and Ethics of Information, although she has worked on issues concerning Epistemology, Logic, and Philosophy of AI. Dr Taddeo has been awarded The Simon Award for Outstanding Research in Computing and Philosophy in recognition of the scholarly significance of her two articles: An Information-Based Solution for the Puzzle of Testimony and Trust (Social Epistemology, Springer) and Modelling Trust in Artificial Agents, a First Step toward the Analysis of e- Trust (Minds & Machines, Springer). She received the World Technology Award for Ethics acknowledging the originality and her research on the ethics of cyber conflicts, and the social impact of the work that she developed in this area. Since 2016, Taddeo serves as editor-in-chief of Minds & Machines (Springer) and of Philosophical Studies Series (Springer). She is also Fellow of the Council on the Future of Cybersecurity of the World Economic Forum.
Catherine Flick - De Montfort University
Dr. Catherine Flick is a Senior Lecturer in Computing and Social Responsibility at the Centre for Computing and Social Responsibility at De Montfort University.
Areas of research have involved responsible research and innovation in health and ageing, online child protection, trusted computing, ethics and video games, ethics in AI, anonymous technologies and the darknet, and informed consent in ICT. She holds a number of EU grants on responsible research and innovation and is a member of the ACM’s Committee on Professional Ethics, and is a steering committee member of the ACM’s Code of Ethics refresh team. She teaches computer ethics and research methods to business computing and computer science students.
Shahar Avin - Centre for the Study of Existential Risk (CSER)
Dr Shahar Avin is a Postdoctoral Researcher in the Centre for the Study of Existential Risk (CSER) at the University of Cambridge. His research examines challenges and opportunities in the implementation of risk mitigation strategies, particularly in areas involving high uncertainty and heterogeneous or conflicting interests and incentives. Mixing anthropological methods and agent-based modelling, Shahar works with other CSER researchers and others in the existential risk community to identify and design opportunities for impact. He is a co-lead author (with Miles Brundage) of the report The Malicious Use of Artificial Intelligence, and managed the development of the Superintelligence mod for the popular strategy game Civilization V.
Panel Discussion - Ethics - Plenary Session
After looking at technical advancements in AI in retail, finance and AI Assistants over the course of the summit, we will join together to discuss the broader questions arising within AI ethics. Top academics and experts in industry will discuss topics around employment, skill shifts, behaviour change, AI bias and humanity. What should a regulatory framework for AI include? How do we eliminate AI bias? How do we define the humane treatment of AI? How do machines affect our behaviour and interaction?
Phil Westcott - Filament.AI
Phil is the Managing Director at Filament.AI and a former Director at IBM. He is a specialist in applied Artificial Intelligence and business transformation. Phil previously ran the IBM Watson Ecosystem in Europe and launched IBM’s global IoT practice. He is a Chartered Engineer, holds an MBA from IESE Barcelona & Columbia New York and is an Entrepreneur in Residence at Nottingham University.
Filament.AI is a venture-backed expert services and tooling firm specialising in applied Machine Learning, NLP and Computer Vision. The team of 28 AI specialists is drawn from IBM Watson, Capgemini, top academia and a leading London digital agency. Since mid-2016, Filament has delivered expert AI services for the likes of HSBC, Deutsche Telekom, IBM, Google and American Express.
Lucy Yu - FiveAI
Lucy leads public policy at FiveAI, a British technology company building fully self-driving vehicles to deliver safe and convenient shared mobility services for cities, starting in London in 2019. Lucy’s background combines startup business with technology policy and regulation. She has held roles at the UK’s globally renowned Centre for Connected and Autonomous Vehicles (CCAV), Cabinet Office, the Department for Transport and the UN, along with award-winning British technology startups SwiftKey (AI software), Reconfigure.io, and GeoSpock (data analytics). She has been on the boards of TravelSpirit Foundation (mobility innovation), HackTrain, and Ada, the National College for Digital Skills.
Yasemin J. Erden - St Mary's University
Yasemin is Senior Lecturer in Philosophy at St Mary’s University, and her research interests range from interdisciplinary (with science and technology) to philosophy of language, aesthetics, and ethics. Her most recent publications include topics in dialogue and education; thinking, agency and recognition, and; neural implants and human identity. She is Vice Chair of the Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB) and on the Council of the Royal Institute of Philosophy.
Ansgar Koene - Horizon Digital Economy Research Institute & University of Nottingham
Panelist
Ansgar Koene - Horizon Digital Economy Research Institute & University of Nottingham
Dr. Ansgar Koene is a Senior Research Fellow at Horizon Digital Economy Research institute, University of Nottingham and chairs the IEEE P7003 Standard for Algorithm Bias Considerations working group. As part of his work at Horizon Ansgar is the lead researcher in charge of Policy Impact; leads the stakeholder engagement activities of the EPSRC (UK research council) funded UnBias project to develop regulation-, design- and education-recommendations for minimizing unintended, unjustified and inappropriate bias in algorithmic systems; and frequently contributes evidence to UK parliamentary inquiries related to ICT and digital technologies.
Ansgar has a multi-disciplinary research background, having previously worked and published on topics ranging from AI, bio-inspired Robotics and Computational Neuroscience to experimental Human Behaviour/Perception studies.
15:00
END OF SUMMIT
11:30
Vasco Pedro - Unbabel
Transforming Customer Service with Multilingual Conversations
Vasco Pedro - Unbabel
Transforming Customer Service with Multilingual Conversations
How AI is redefining omni-channel customer service for the better? In a global market, where customers expect to be spoken to in their native languages, balancing exceptional customer experience across all markets, with ever increasing cost pressures and operational realities is tough. This interactive workshop will explore how AI plus humans can deliver exceptional customer experience, in 28 languages, at scale, with multilingual live chats.
Vasco Pedro is the co-founder and CEO of Unbabel, with a mission of enabling everyone in the world to understand and be understood in any language. He has a Ph.D. in Language Technologies from Carnegie Mellon and has served as a mentor at The Founder Institute and Beta-i, where he helps startups navigate the early stages of development, focusing on team building, technology challenges and building testable MVPs.
14:15
Startup Mentoring Session - BREAKOUT SESSION
Startup Mentoring Session with VCs and Industry Experts - 2.15-5.00pm
Startup Mentoring Session - BREAKOUT SESSION
The opportunity for startups to meet with leading AI investors, VCs and industry experts to pitch ideas, and gain advice on their business ideas and strategies. View the VC information here.