My Digital FootPrint

Customer Commons have presented a research paper:  Lying and Hiding in the Name of Privacy http://customercommons.org/2013/05/08/lying-and-hiding-in-the-name-of-privacy/ Abstract A large percentage of individuals employ artful dodges to avoid giving out requested personal information online when they believe at least some of that information is not required. These dodges include hiding personal details, intentionally submitting incorrect data, clicking away from sites or refusing to install phone applications. This suggests most people do not want to reveal more than they have to when all they want is to download apps, watch videos, shop or participate in social networking. Keywords :  privacy, personal data, control, invasion, convergence Download a   PDF of the paper here . They surveyed 1704 people showing that 92% of the people do something:  hide, lie, click away or refuse to install an app.. in order to control their data and create some kind of privacy.   I

Electronic Freedom Foundation (EFF)   has recently released   a new report   about which companies protect their users' digital data/ identities. Download the complete   Who Has Your Back? 2013   report as   a PDF from here. Executive Summary When you use the Internet, you entrust your conversations, thoughts, experiences, locations, photos, and more to companies like Google, AT&T and Facebook. But what do these companies do when the government demands your private information? Do they stand with you? Do they let you know what’s going on? In this annual report, the Electronic Frontier Foundation examined the policies of major Internet companies — including ISPs, email providers, cloud storage providers, location-based services, blogging platforms, and social networking sites — to assess whether they publicly commit to standing with users when the government seeks access to user data. The purpose of this report is to incentivize companies to be transparent about how da

21 years ago there was no digital footprint ideas so there is no digital trace or record, but I do have the press cutting that got me into a lot of trouble.  I had no idea back then how advanced the technology was as it seemed normal to me or how long it would take to generate adoption.   Of interest to me is that the big issue of the day was privacy ( you answer the phone and someone can see you, can they remotely switch on the camera and look round my home).  I have never appeared to escape the clutches of privacy issues. The context is; I was working at GEC Marconi on Videophones with Tom, Dave , Mark , Alvin , Rob and Andy , Andy , Les to name a few of the team.  I was at the Ideal Home exhibition in London and on the BT stand and launching the Videophone. The Relate 2000 videophone was the first one BT made commercially. It promised callers the chance to see, and be seen by, the person they were talking to. It featured a flip-up screen on the right, where the video

Image. It is an algorithm: globalimaging.com/images/modis-atmos.jpg Algorithms     are the foundation of your computing interactions. An algorithm is the means by which a computer program can make decisions about you, for you, or decisions that affect you.  Algorithms are the translation of what you do into rules and policies that a computer understands (i.e. 0s and 1s). Like it or not, you are influenced by them as much as you influence them. Algorithms need data, they use digital data that you give, leave or have tracked about you (willingly or not).  This input into an algorithm is your digital footprint, which comes from Facebook, Twitter, text messages, email, key stokes, swipes, gestures, play lists, payment records, your routes, navigation – indeed anything you do which is an interaction with an electronic device. This is the basis of what an algorithm knows about you. It is how an algorithm can model you, it takes input and predicates based on what you have done and

Researchers at Massachusetts Institute of Technology (MIT) and the Catholic University of Louvain studied 15 months' worth of anonymised mobile phone records for 1.5 million individuals. Here's  the full study. With no real surprise they found from the "mobility traces" - the evident paths of each mobile phone - that only four locations and times were enough to identify a particular user. We are predictable and so Dan Ariely Work comes true.  In their own words “ They studied fifteen months of human mobility data for one and a half million individuals and find that human mobility traces are highly unique. In fact, in a dataset where the location of an individual is specified hourly, and with a spatial resolution equal to that given by the carrier's antennas, four spatio-temporal points are enough to uniquely identify 95% of the individuals. We coarsen the data spatially and temporally to find a formula for the uniqueness of human mobility traces given their resol