Next Executive Session: What about a debate on Big Data & Ethics ?

Pierre Nicolas Schwab -EBU_Big_Data


Next Executive Sessions :

After the interesting talk of Stephen Brobst CTO#4 we now want to organise a debate on Big Data & Ethics. Pierre-Nicolas is proposing the following format: Short presentations by each participant representing the vision of his/her company followed by a debate. Any suggestions ? Who wants to participate ?


Philippe, Puis-je te proposer que tu organises un atelier de travail avec une dizaine de responsables Big Data sur l’éthique et le Big Data ? 
Il faudrait limiter l’audience à des décisionnaires Big Data qui puissent vraiment représenter le point de vue de leur société.
En termes de structuration :
 – 10-15 min (TED format) de présentation de chaque société sur les enjeux éthiques, sur la manière dont les algorithms sont conçus pour tenir compte de ces aspects éthiques, sur les enjeux et limites du Big Data, ce que les entreprises s’interdisent de faire en termes de collecte de données (la “ligne rouge” à ne pas dépasser)
 – un atelier d’échanges / débat


Here is some inspiration on the topic.

The RTBF’s big data expert Pierre Nicolas Schwab reflects on how to develop algorithms for PSM which match their values and mitigate the potential flaws of artificial intelligence. He invites EBU Big Data Initiative participants to join the RTBF workshop addressing this issue this December in Brussels.

“Most large companies are investing massively in Big Data technologies to leverage the value of their data. While many still consider Big Data as an inescapable business trend, concerns are growing regarding the impact of Big Data on our daily lives.

A ‘man vs machine’ Artificial Intelligence (AI) milestone was reached in March this year when the deep-learning algorithm AlphaGo defeated one of the world’s best players at Go, Lee Sedol. In an article I published before the game, I was wondering how advances in AI were changing our lives. Cathy O’Neil, a Harvard PhD mathematician, expressed similar concerns at the USI conference in Paris in early June and will be releasing her book “Weapons of Math Destructions” in September. This book elaborates on the concerns she has expressed on her blog about ill-based decisions triggered by algorithms and how big data “increases inequality and threatens democracy”. The title may be provocative but promises to go beyond the filter bubble effect made popular by Eli Pariser.

Because algorithms are only as good as those who build them, we need to open up the models, and not only the data. Those models need to be subject to criticism, peer-review and third-party scrutiny. This will avoid the use of biased or even dangerous algorithms (e.g. the French universities selection algorithm scandal revealed earlier this month) and will increase people’s trust in organizations which use algorithms. To illustrate the latter, the French fiscal authorities are now forced to render public the criteria that play a role when submitting a tax payer to a control. This exemplifies that a change is ongoing and, as PSM, we must embrace and support it.

Not only must we avoid replicating flawed models (in particular recommendation algorithms that trap users in “filter bubbles”) but we, as public organizations, have duties towards our democratic societies and their citizens. That’s why we need to (1) engage in a global reflection on how our algorithms need to be shaped to reflect our values and (2) pave the way for better practices that will inspire other organizations in different industries.





Data scientists aren’t domain experts – Prof Stijn Viaene, 2013

Obtaining maximum value from Big Data projects requires multidisciplinary knowledge in:

  • Business to comprehend the business problems and identify business opportunities that can be tackled with Big Data
  • Analytical to skilfully apply the Big Data models that create the most value
  • IT/Database to understand the IT requirements related to Big Data projects
  • Management to view process as a whole with a focus on change management and people

This Executive Master Class provides participants with the necessary skills to successfully manage this multidisciplinary competencies and to create value with Big Data in their organization.

Are you ready to discover the opportunities out there and be part of a 17 day programme in Brussels and San Francisco?


Why this programme?

By participating in this Executive Master Class, you will:

  • Understand how exploiting Big Data can benefit your company
  • Get a thorough understanding of Big Data modeling techniques
  • Share best practices in Big Data inside and outside your sector
  • Develop a Big Data project for/in your organization


For whom?

Because this programme addresses both business and Big Data, it’s beneficial for a number of professionals. However, understanding Big Data models requires at least a basic analytical background.

This programme is ideal for a multidisciplinary team of 2 people from the following backgrounds:

  • Business analysts who want to use Big Data analytics in a business context
  • Professionals with an IT/technology background who want to learn how this technology can be used to create business value
  • Business experts with a strong analytical background who will be involved in Big Data projects


Module 1 – Modeling

(23, 24 & 25 October 2014; Brussels)

This module connects the worlds of data scientist and business expert by:

  • Presenting an overview of typical analytical & Big Data applications that create value in several industries (Finance, Retail, Telecom, Pharmaceuticals, …)
  • Creating awareness of the latest business trends in Big Data
  • Aligning Big Data investment with business benefits


Module 2 & 3 – Discovering

(27, 28 & 29 November; Ghent – 11, 12 & 13 December 2014; Leuven)

This module introduces participants to more advanced Big Data solutions, focusing primarily on creating value from large volumes of data.

  • The IT infrastructure that is needed to apply Big Data analytics
  • The main advantages & disadvantages of multiple Big Data technologies
  • Data modelling and visualization
  • How to get business value from text data, web data, social network, audio and video data: moving towards customer centricity
  • State of the art in Fraud Analytics: improving Fraud detection using social network analysis
  • Hands-on exposure to tools that turn Big Data into value


Module 4 – Operationalising

(19, 20 & 21 February 2015; Brussels)

This module focuses on turning the insights gained from the previous modules into actions by adapting business processes, architecture and BI systems.

  • How to take advantage of high-velocity data
  • The organisational capabilities that are needed to successfully implement Big Data projects
  • How to put Big Data into action using decision-management solutions


Module 5 – Cultivating

(6, 7, 8, 9 & 10 April 2015; Silicon Valley, San Francisco)

This module investigates how management can optimally exploit the newly created Big Data benefits by cultivating data-driven decision-making in their organisation.

  • A deep dive into organisational strategies to cultivate Big Data innovations
  • How to optimally communicate Big Data projects
  • How to deal with ethics and privacy in a big data world




Discover our Faculty:



23-25 October; 27-29 November; 11-13 December 2014; 19-21 February; 6-10 April 2015

17 days

Vlerick Campus Brussels , Vlerick Campus Ghent , Vlerick Campus Leuven ,Silicon Valley, San Francisco


11495 euros (excl. 21% VAT)
+ €850 catering costs & €1450 for module in San Francisco

Financial Benefits