BIG DATA III - Vrijdag 14 dec 2018
After two successful editions of BIG DATA, we invited a number of experts to further discuss ongoing developments in the field of big data and machine learning, followed by a panel discussion.
13u30 - 14u00: Welcome and introduction by Pieter Buteneers (Sales and Project Manager at Robovision)
14u00 - 14u40: "Domain-specific NLP pipelines" Aleksandra Vercauteren (Senior Data Specialist at Faktion)
Just like you have general purpose clothes for everyday use, there also are a wide variety of specialised clothing that are a better fit for certain situations. The same thing is true for Natural Language Processing pipelines. General purpose NLP pipelines are used successfully in a wide variety of applications, but in some use cases domain specific components are required, especially when the text to be processed contains specialised language and an industry-specific vocabulary. Illustrating with several use cases, Aleksandra Vercauteren will explain in which situations it makes sense to build a custom pipeline.
14u40 - 15u20: "UgenTec:Improved quality of life through industry-changing software" Wouter Uten (Chief Operations Officer at UgenTec)
UgenTec develops diagnostic software to replace subjective and time-consuming manual DNA analyses in clinical labs with accurate and fully automated analysis software. This software allows for automatic and objective patient diagnosis with higher accuracy levels, saving time and eliminating the risk of human error. In this talk Wouter reveals how UgenTec is translating data and algorithms in economic opportunities and value creation.
15u20 - 16u00: “AI - How can Europe compete?" Rachel Alexander (Founder and CEO of Omina Technologies)
Are China and the US outfoxing Europe in AI? If the development of artificial intelligence is an arms race, then China and the US want to become the world's unchallenged AI superpower.
16u00 - 16u15: Break
16u15 - 17u00: "The ethics of algorithms" Katleen Gabriels (Assistant Professor at Eindhoven University of Technology)
In designing and developing technology, there are always risks involved. Next to calculating a design's hard impacts, in terms of safety and health, also 'soft' impacts, such as undesirable consequences, deserve our attention. Today, logging off has become an illusion in our always-on world. Enormous data sets are generated every day. Algorithms not only have an important share in how we see the world, they also predict our future behavior and even influence our thoughts. Yet, neither algorithms nor data sets are ever neutral; on the contrary, users' and developers' biases slip into them. And still we rely on them on a daily basis. How can we anticipate and reduce undesirable consequences and pitfalls?
17u00 - 17u30: panel discussion
Friday December 14th 14u00 - 18u00
Flanders Business School