In a very interesting presentation at the 2015 ISC2 EMEA Congress in Munich, Dr Lucas Feiler posited that any big data analytics performed, whether internally or outsourced, is going to attract significant legal challenges related to privacy. And even if the challenges CAN be resolved, it will likely be in ways that make something of a mockery of the EU General Data Protection Regulation (GDPR)’s intent.
Getting around privacy regulations will involve token human interaction (i.e. smoke and mirrors) where none is desired. In areas that needs to be dominated by AI and the resulting automated decisions (insurance for example), adding the human element to avoid the appearance of prejudiced results will probably be standard until the algorithms become smart enough to be considered ‘reasonable’ (my absolute favourite legal term, right up there with ‘appropriate’).
Human interaction is not desired by those doing the analysis mind you, we may think otherwise.
While not in place …yet, the European Council aims for adoption of the GDPR in 2017 and have it in full effect after a “two-year transition period“. While 4 years may sound like a long time, when you consider the following statistics (taken from www.unifiedsocial.com) you can only imagine how difficult it will be to clean up the mess if organisations don’t start following the regulation now:
- The data volume in the enterprise is estimated to grow 50x year-over-year between now and 2020
- 35 zettabytes (that’s 35,000,000,000,000,000,000,000 bytes) of data generated annually by 2020
- According to estimates, the volume of business data worldwide, across all companies, doubles every 1.2 years
Granted, the vast majority of this data will be in the form of cat videos and Kardashian tweets, but that still leaves an extraordinary amount of YOUR data sitting on servers just waiting to mined, manipulated, and analysed in ways we cannot even imagine. We cannot imagine them because they have not been INVENTED yet, and that’s the Holy Grail for any organisation, and the impetus behind big data analytics in the first place; How to manipulate the data they have into the development of new revenue streams.
To put that another way; How to take the data they have on you already and present it back to you in a way that makes you spend more money.
I’m actually not against this per se, Amazon are already doing a mild version of it with their “Frequently Bought Together” and “Customers Who Bought This Item Also Bought” sections, but can you imagine how much data they have on their more than 1.5 MILLION servers across 17 global regions?
The card brands and Facebook can predict within a two week window whether or not you’re going to get divorced, how much other data do THEY have? Or Google?
But can the GDPR actually make a difference? Probably, it has a VERY big stick, and you know how lawyers love their class action suits!
Look at GDPR CHAPTER II, PRINCIPLES, Article 5 – Principles relating to personal data processing:
Personal data must be:
(a) processed lawfully, fairly and in a transparent manner in relation to the data subject;
(b) collected for specified, explicit and legitimate purposes and not further processed in a way incompatible with those purposes; (…);
(c) adequate, relevant and not excessive in relation to the purposes for which they are processed (…);
…and now CHAPTER VIII, REMEDIES, LIABILITY AND SANCTIONS, Article 79a – Administrative fines:
The supervisory authority (…) may impose a fine that shall not exceed 1 000 000 EUR or, in case of an undertaking, 2 % of its total worldwide annual turnover of the preceding financial year, on a controller or processor who, intentionally or negligently:
(a) processes personal data without a (…) legal basis for the processing or does not comply with the conditions for consent pursuant to Articles 6, 7, 8 and 9;
If you LOSE personal data the fines can be a much as 5% of worldwide annual turnover.
Will that make a difference?
I hope so.