My Digital FootPrint

The economic argument and case for data portability (mobility) is set out here. Running with the assumption that you agree that data portability/ mobility will create value for the data economy, we need to also think about the thorny issue of layered consent. Some posts that have explored areas of consent Layered Consent: like peeling the onion, only to find it is not an onion! Why “#Privacy-by-Design” is more than playing the game of #ethics of opt-in or the #morals of opt-out. What level of consent is reasonable ..... However in this post, the purpose is to explore what happens when a copy of the data has arrived at the new home, where is consent.  Define :     User                                   [an individual who has agreed to the T&Cs’ to access or use a Data_Holder’s service] Define :    UserData                           [data collected by a Data_Holder from a user] Define :    Data_Holder                     [the entity that has collected UserData fro

This is the PEW report BY LEE RAINIE AND JANNA ANDERSON Code-Dependent: Pros and Cons of the Algorithm Age "Algorithms are aimed at optimizing everything. They can save lives, make things easier and conquer chaos. Still, experts worry they can also put too much control in the hands of corporations and governments, perpetuate bias, create filter bubbles, cut choices, creativity and serendipity, and could result in greater unemployment" Download the full report  Theme 3 is focused on "Humanity and human judgment are lost when data and predictive modeling become paramount"   is excellent - indeed the whole report is.   https://www.pewinternet.org/2017/02/08/theme-3-humanity-and-human-judgment-are-lost-when-data-and-predictive-modeling-become-paramount/

Just read "We Are Data" Algorithms and the Making of Our Digital Selves by John Cheney-Lippold On Page 191 John explores the Else Test ---- At a simple level a nested Python If; Else statement can look like the code below. This is beautiful in its simplicity and offers a repeatable and deterministic way to match a grade to the logical number of the mark obtained.   In each case there is one output;   based on the actual input mark. Happy days if grade >= 90 :     print( "A grade" ) elif grade >= 80 :     print( "B grade" ) elif grade >= 70 :     print( "C grade" ) elif grade >= 65 :     print( "D grade" ) else :     print( "Failing grade" ) Let’s change the case slightly to something which says has more difficult to answer.   “Are you are good parent?”    We can approach the problem in two ways.   The simple way that hides the complexity and based on a score which deter

It is insane that this book has such a low coverage and poor reviews. It is brilliant. The book explores the way algorithms interpret and influence our behaviour. The book forces you to re-assess what you think data says you are. We love the idea that data and the compute model follow our mental models for binary abstraction in defining who we are. The “I am male, female or prefer not to say,” is how we believe the systems see us. John explores why they don’t. In the system we are all part-everything based on the data and how you react to media, because of this the machine see you as your behaviour to what they can see and not what you think or believe. This delta between what you think you are and what the machine thinks you are is unknown and often not reachable. We can correct false data but not false interruption. John quotes lots of people and work we all know, but also many who are not on the usual circuit which makes the book far more informative as it brings in new thi

Key message : decisions regarding the right type of initial explicit and informed “consent” sort from customers is currently a delegated authority from the board. This article argues that there is an imperative to bring back “consent” decisions to the board; at least for a while. The board needs to debate “consent” in light of ideas such as “privacy by design”, ethical AI, brand values, privacy policy, cookie policy and culture; given that consistency across these critical business areas are increasingly core differentiators. - - As a context, much of the classic(al) thinking and definition(s) of consent are here on wikipedia . There is excellent technical work on consent from Kantara for both the user interface and back office processes based on new consent thinking. MEF is publishing really helpful thinking on UI/UX. In the idea of implementing “privacy by design”, I published this blog exploring the concept of Approval vs Forgiveness as the method of gaining consent when consid

“The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power” So I took this one for the team, and read every single page of the near 700 pages.  It is a slog, even for me as a massive advocate of privacy, PII, identity, security, trust and data.  Massive respect to S hoshana Zuboff for 15 years of thinking, research, dedication and writing on and to the topic. This is half of a life's dedication.  Yes I wrote and published " My Digital Footprint - where your privacy is someone else's business model "  10 years ago and whilst we now have lots of proof now, the theory has not moved on.  There is a lot written on this book already. If you want a summary of Shoshana work these are some of these better write ups. WIRED , FT ,  ZDNET ,  The Guardian ,  Harvard , Linux Journal , The Verge , Philosophical .  For those who want a few videos try these TWIT , Democracy Now My thinking I am critical of this book , and can only as

Zucked: Waking Up to the Facebook Catastrophe . The next post will be Surveillance Capitalism vs Zucked - this one is just a quick review of Roger's book. Further to reading the book worth listen to Roger on Sam Harris https://samharris.org/podcasts/152-trouble-facebook/ As background: Roger McNamee is a Silicon Valley investor for thirty-five years. He was a former mentor to Facebook CEO Mark Zuckerberg and helped recruit COO Sheryl Sandberg. What you will read is how the BigTech (esp Facebook) amplify tribalism, allow “bad actors” to “harm democracy” and as there is no accountability there is an ever “shirking civic responsibility.” The book is how we got to this point and not really one on how to answer the problem (will come back to this below). The key point which might be missed is that mafia of funding giants, such as the Peter Thiel, Reid Hoffman and many others shape the culture of start-ups and models. Don't blame one person (company), the eco-system is not tak