My Digital FootPrint

The problem defined by responses   We don't know how automated decisions are being made We don't know what the impact of the automated decisions is / are We don't have a complete map of where the automated decisions are We have little to no qualified insight into the effects on the business or our customers There is no reporting to management when automated decisions have problems - as we don't know when it does There is a sense of trust in the (cto, cio, coo) that they will be on top of it We have no idea about bias in the original algorithm, data set and what updates changes have been made and the effect How our automated decisions effect people in the organisation and their behavior has not been qualified excellent writing and thinking on automated decisions and algorithms https://fpf.org/2017/12/11/unfairness-by-algorithm-distilling-the-harms-of-automated-decision-making/ https://www.infoq.com/articles/Can-People-Trust-Algorithm-Decisions/ htt

Have been doing some work and thinking about automated decision making; specifically looking at a credit algorithm. Below are the questions I set the owner of the algorithm to help in the assessment. I am publishing them here in the hope they are helpful. 1. Where did the algorithm come from? What is it providence ? does it have a serial or product number? Which company supplied it ? (inc internal) Who maintains it ? How long has it been in the company? Is there any IP owned by other or the company? 2. Who wrote the algorithm ? ( company, team, individuals) What it a generic algorithm/ bespoke build? What was the acceptance procedure? What else did they write do for the company or others? 3. What data/ processes/ procedures were used to build it  Is it stand alone? What process it is part of ? Are you using the same processes now?  Did it replace a procedure? Where did the data come from to set the boundaries/ maths ?  4. What

Algorithms vs Processes.  In both an input is transformed to an output – there is a difference in HOW.  Algorithm = a set of mathematical instructions or rules that, especially when coded enable a computer to calculate an answer. Typically, specific instructions that can be followed or learnt, that can be mechanised and reduces human involvement to zero. It is a tool it is driven with an idea about better or the most efficient resource allocation. An algorithm is a WHAT and HOW Process = a series or method of tasks/ steps/ actions that are taken in order to achieve a result. Typically, instructions that can be followed or learnt, that enable human and compute/ machine involvement to achieve a set goal, objective or result. A procedure is the prescribed way of undertaking a process. A process is a therefore a WHAT and a procedure is HOW Why important, we debate a lot about the dependence on algorithms in the computer age and how these algorithms will talk over the world and put

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

Hello World by Hannah Fry .   Follow Hanna on Twitter My take If you are having any issues explaining algorithms, data or the impact to anyone from a student to the CEO. READ this book ! It is brilliant. I highlighted more in this book than most Hannah brings out that algorithms and data bias is part of society, however the scale is now something we cannot hide from.  Past controls were hidden but now are out in the open, but sometimes we don’t have a clue how it happens We have a choice every time we use a service - be lazy or be in control.  Neither is better however, to become dependent on the algorithm is not about the loss of control but about the loss of identity Control of the algorithm is not limited to the code, but the weaknesses of the machine, design and data. Love Hannah’s take on AI, will be writing up another book on AI soon - so will keep thinking on AI for that. When people are unaware that they are being manipulated, they tend to believe that they