After an exciting kick-off at EGG NYC, the human-centered AI conference is back, this time in London. Tomorrow, July 2nd, data professionals, academics and enthusiasts across different countries, industries and backgrounds, will come together to talk about the future of AI. EGG puts the spotlight on humanity and empathy in AI, diving into real-world use cases and hot topics such as machine learning interpretability, bias and fairness.
Whether you’re attending EGG LDN in person, planning to watch the live stream or simply curious about it, here are three main themes that our speakers and guests will be discussing tomorrow.
1. Ethical Challenges and Achieving Responsible Enterprise AI
From biased algorithms and data privacy concerns to deepfake imagery, the ethical implications of data has never been more crucial to restoring people’s faith and trust in the future of AI. Our speakers will talk about these issues, as well as discuss strategies for organizations and data practitioners to ensure an ethical approach to AI.
Here are all of the speakers and talks about responsible AI:
- Algorithmic Bias, Privacy Protection and EU Non-Discrimination Law. Dr. Sandra Wachter, Senior Research Fellow in Data Science and AI @University of Oxford
- Can We Make AI Likeable (at least enough to avoid the counter-revolution)? Florian Douetteau, CEO @Dataiku
- Ethical Enterprise AI - A Guideline or Compass? Martin Leijen, Architect Data and Intelligence Lab @Rabobank
- What is to be Done when Absolutely Everything can be Faked? Shaun McGirr, Head of Data Science and Business Intelligence @ Cox Automotive UK
- Ethics, Data Science, and Public Service Media. Ben Fields, Lead Data Scientist @BBC News
- AI in Business: Learning How to Be Responsible. Bernardo Nunes, Head of Science @Growth Tribe Academy
- AI in Health and Life Science: Where are we Going? Susana Frazao Pinheiro, Senior Teaching Fellow @UCL School of Management
- AI for Improved Media Ecosystem. Magdalena Lis, Data Product Manager @Factmata
- GDPR and the ICO's Proposed AI Auditing Framework. Ali Shah, Head of Technology Policy @Information Commissionner's Office
- Toward Ethical AI: Inclusivity as a Messy, Difficult, but Promising Answer. Larry Orimoloye, Sales Engineer @Dataiku
2. Empowering People and Organizations to lead a Business Transformation
While compliance with ethical standards is one of the most important steps for companies in their path to Enterprise AI, an equally crucial part of becoming a data-powered organization involves implementing the right structural changes and giving people across teams and business units the right tools.
From building a data science Service of Excellence to improving key department functions by integrating highly effective data analytics teams, the EGG speakers will reveal how their companies drive value and power business transformation with data.
These are the speakers who would be covering the fundamentals of Enterprise AI and data science:
- Enabling the Data Revolution. Caroline Carruthers, Director @Carruthers and Jackson
- The Growing Pains, Pitfalls & Future for a Data Science Team in a Hyper-Growth company. Shaun Moate, Director of Applied Machine Learning @DAZN
- How Mercedes-Benz, Vodafone, and Credit Suisse Super-Sized their Data Initiatives. Timo Gemmecker (Mercedes-Benz), Denis Avdonin (Credit Suisse), Brian McDaid (Vodafone) - panel discussion
- Balancing AI and the Human Touch. Tim Hesse, Director of Data @Carwow
- How to Build a Data Science Service Centre of Excellence. Nicholas Bignell, Director @UBS
- Cyber Risk Analytics: The Next Frontier. Paul Guthrie, Chief Technology and Product Officer @Envelop Risk
- Optimising Smart Cities with AI. Kim Nilsson, CEO @Pivigo
- Organisation + Humans + Data - Building a Highly Effective People Analytics Team at Barclays. Jesús Rogel, Director of Data Science, Analytics and Insight @Barclays
- Mapping Your Organisation’s Enterprise AI Maturity. Romain Fouache, COO @Dataiku
- Stakeholder Management: A Data Scientist's Perspective. Denis Fragkakis, Enterprise Data Science Lead @IG
- Driving A Data Driven Business Transformation. Peter Jackson, Director - Group Data Sciences @Legal and General
3. How They Actually Do It: Real-World Use Cases
The “Advanced Use Cases” afternoon breakout session will dive deep into the data science techniques and strategies that companies are actually using in order to achieve their business goals. From democratizing automated forecasting in the automotive industry to building powerful discovery systems in retail, these are the real-life applications through which cutting-edge organizations are transforming their businesses and leading the data revolution.
Here's the list of all the advanced use cases presentations:
- A Glance at ADA: Aviva’s Algorithmic Decision Agent. Damian Rumble, Senior Data Scientist @Aviva
- The Spirit of the City: Capturing Network-Generated Data for Better Cities. Luca Maria Aiello, Senior Research Scientist @Nokia Bell Labs
- Convenient and Flexible ML Pipelines with Kubeflow. Mattias Arro, Machine Learning Engineer @Subspace AI
- Leveraging the Law of Averages to Deal with Data Science Frustration. Adrian Badi, Lead Data Analyst @Demant
- How to Make a Success of Data Science: Rendezvous Architecture for Data Science in Production. Jan Teichmann, Senior Data Scientist @Zoopla
- Generative Adversarial Networks for Finance. Alexandre Hubert, Lead Data Scientist @Dataiku
- Democratizing Automated Forecasting at Mercedes-Benz. Lukas Stroemsdoerfer, Lead Data Scientist @Mercedes-Benz
- AI in Retail: Building a Brilliant Shoe Discovery System. Antonis Argyros, VP Product and Growth @SafeSize