PANEL « BUILDING TRUST »EBU BIG DATA CONFERENCE, 21 MARCH 2017

Pierre-Nicolas Schwab

Head of Big Data, RTBF (Belgium)

psn@rtbf.be

WHY TRUST MATTERS

• Trust in medias has decreased further: 26% trust in online media *

• Online media lesstrusted of all. Yet, main source of news among younger audiences(source: Reuter digital news report 2016)

* Source: Kantar Sofres (2016, 2017)

ALGORITHMS TOO CAN BUILD (DIS)TRUST

Personalization represent a challenge with 3 key problems identified :

– Too much personalization key information may be missing

– Alternative viewpoints may be absent

– Privacy may be threatened

Source : Reuters Digital Report 2016

5 RULES TO MAKE ALGORITHMS MORE ETHICAL

1. Avoid discrimination

2. Promote gender equity

3. Open up customers’ minds (exploration) rather than trapping them (exploitation)

4. Respect right of not being tracked

5. Educate users on algorithms

EDUCATION IS KEY

• Empower users: give control back

• Build knowledge

• « Show » your algorithms (open the black boxes !)

“An [algorithmic] system that you can't audit is a system that you can't use" Marc Rotenberg, CPDP conf. 2017

4 MEASURES TAKEN AT RTBF (1/4)CONFIDENTIALITY CHARTER

• New privacy and confidentiality charter (effective 01 Dec 16)

• Simplified yet complete

• Clear promises

• Special focus on children

• Dedicated video

4 MEASURES TAKEN AT RTBF (2/4)SINGLE-SIGN-ON

• Single-Sign-On (SSO) launched 01 Dec 2016

• Personal information centralized

• Easier for user to control, modify and erase information

• Essential tool for reconciliation of online usages and respect of GDPR

4 MEASURES TAKEN AT RTBF (3/4)RECOMMENDATION SYSTEMS

• Design of recommendation systems follow ethical rules

• Personalization will follow the concept of deliberative democracy

• Focus on exploration and discovery (≠ filter bubble)

4 MEASURES TAKEN AT RTBF (4/4)EDUCATION TO ARTIFICIAL INTELLIGENCE

• 1-hour TV program with real users (shooting on 29 March)

• Communication on corporate website

• Badge on website to signal algorithmic curation

• Systems designed to support visualization of algorithms’ effects

CONCLUSIONS

• Media consumption more and more digital : gaining online trust is key

• Recommendation algorithms are not neutral design them carefully and ethically

• PSM have a major role to play to educate users on the role of algorithms