Talked about the importance of transparency in data use between consumers and companies, but also about the importance of data fairness, as well as resulting problems in the user experience.
How to measure data fairness?
Proposed the below framework to measure data fairness, based on 4 key pillars:
- Security: are you storing customer data securely, encrypted and taking prevention measures against breaches?
- Privacy: if your customers don’t want to be seen (tracked), do you allow them this option?
- Monetization: is the value your customer is getting out of your service equal to your profits or are you making an unproportional profit from your customer’s data?
- Ethics: are you treating your customer’s data with respect or are you asking them much more than what you really need for them to complete the transaction?
How to increase data fairness?
To make companies behave more ethically in their data use but also to help consumers get more empowered, the 3 key pillars below should be addressed:
- Education: data literacy is a ongoing, lifelong process. Technology evolves faster than humans can adapt, so ongoing education on the topic is essential.
- Software: software applications that are easy to use will make the difference in bringing transparency to user data
- Labeling: by regulating and certifying fair data usage, consumers can find trusted partners and build long-lasting relationships with companies that respect their data.
Problems in the user experience
Last but not least, I highlighted the problems in the user experience nowadays caused by lack of understanding of technology tools and how the knowledge gap is magnified by new technologies, especially for a big part of the society today. Most internet users nowadays are faced between 2 extremes: either accept it all or reject it all; and when they are exceptionally able to manage their preferences this is a very effort-full and time-consuming process.
More info on the keynote and on Open Belgium conference can be found here