My Digital FootPrint

The Mind is Flat (book) by Nick Chater Rare find as the quotes live up to the content and have to say READ IT.    If you are thinking like me about ethics and AI - this is essential reading.   ----- A radical reinterpretation of how your mind works - and why it could change your life’ 'An astonishing achievement. Nick Chater has blown my mind' 'A total assault on all lingering psychiatric and psychoanalytic notions of mental depths ... Light the touchpaper and stand well back' We all like to think we have a hidden inner life. Most of us assume that our beliefs and desires arise from the murky depths of our minds, and, if only we could work out how to access this mysterious world, we could truly understand ourselves. For more than a century, psychologists and psychiatrists have struggled to discover what lies below our mental surface. In The Mind Is Flat , pre-eminent behavioural scientist Nick Chater reveals that this entire enterprise is utterly mis

Decisions Not Data - Lisa Schutz Why the (decision) revolution won’t be televised Lisa delivers a punchy “How-To” book based on her successful consulting business practice. It is a guide to using data and analytics to achieve organisational goals and avoid the “Data Trap” that many organisations unwittingly fall in to….. It is a plane ride book, two hours and your through. A key message is to ask the question about what decision you want to make - before you plan on the collection and analysis of data - the trap being what does the data tell me, rather than what data do I need to help me make better decisions. She perfectly draws out the different decisions that can be supported by data (operational, product, sales/ marketing, customer) - they key being if you apply the wrong data to the wrong decision and then ponder why something went wrong - stop leading with data. Different parts of the business also need different data and having one data lake may not in all cases be the best

Original Article :  https://www.trustedreviews.com/news/self-driving-cars-life-death-3640133 These are fantastic discussions and as humanity we are not having enough of them but rather than clink-bate with headlines for adverting revenue, what are the first principal questions? This specific moral dilemma make a number of assumptions : the machine can differentiate the machine can make the choice (algorithm/ software/ data) it is possible to do one action over another (physics: motion and time) where is experience / learning in the feedback loop who said we had the choice in the first case Given that the road accident for the victim is currently random (other than premeditated and malicious) - who gave someone the right to pick or select me. If I am selected that means a new liability for someone.  The existing system being based on risk and acts of freewill, allowing machines to decide, as the human has determined by programming and selection this removes freewill.  H

This is also published on LinkedIn and Medium as well  Data is Data.  It is not Oil or Gold or Labour or anything else! Words, in general, are a creative symbolic linguistic invention through which people invoke concepts and meanings that are flexible enough to enable we Homo sapiens to shortcut detailed explanations.  A dog = mammal, furry, four legs, barks, teeth etc. However, words; because they are a shortcut, often lack context and relationship that add “meaning”. Words are “data” which requires the addition of meaning derived from context to “inform” the listener - to become “inform-ation.”   Love, for example, can mean, or be interpreted to mean, many propositions depending on context and relationship. The 2019 update to the New Oxford Dictionary brings in the words   agender and intersexual to help define better and enable more nuanced conversations about  sexuality and gender identity, as society has words without the specific context and better words help avoid

The video is not new and neither is the thinking. The Verge did a write up on this and an update - worth reading.  The general response was always about the creepy line - however now seeing clearly that the issue is about where the data is.  What I mean by this is that the data is in Google Silo and Google's view is not to find the data from other sources - but to find a way to get the data itself, making a bigger silo. My problem with this is that this very model of one big silo is the one model that will get broken first. As trust is the issue in the big silo model, why does trust become the game changer.... that idea is explored  here 

We know and love the original thinking from Clayton Christensen - however is this model about itself to be disrupted?   https://en.wikipedia.org/wiki/The_Innovator%27s_Dilemma Investing today into an early stage high growth business is largely predicated on the target having a product or service that collects and stores data. They have a proposition the market wants and enabling the business to collect unique data is critical to funding (growth and defence) and  there is a foreseeable route to exit. As a business you combine your data set with anything else you can buy, enabling you as a business to refine your proposition, grow customers, improve satisfaction, increase engagement, uplift revenue and create more value by having better data and analysis.  It is virtuous circle based on collecting, storing, analysing and using data. Essentially we are still very early in this thinking and investment cycle.  The majority of early stage venture money is following this proces