Showing posts from December, 2020

Can AI feel curious?

I have been pondering on these topics for a while  “Can AI have feelings?”  “Should AI have emotion?”  What would it mean for AI to be curious? I posted, can a dog feel disappointment? Exploring our attachment to the projection of feelings.   I have written an executive brief about how a “ board should frame AI” here . The majority of the debates/ arguments I read and hear centre on either creating the algorithms for the machine to know what we know or for the data to be in a form that allows the machine to learn from us.  A key point in all the debates is that we (humanity) should control and it should look like us. The framing of a general rule for emotional AI is that it mimics us. However, I want to come at AI feelings from a different perspective based on my own experience, one where AI creates feelings by its own existence.  I am on several neurodiverse scales; this means my mind is wired differently, and I am so pleased it is. My unique wiring gives me the edge in innovation,

As McKinsey roles out the “Gartner Disillusionment” graph, I think it is time to look for a new one!

The article “ Overcoming pandemic fatigue: How to reenergize organizations for the long run ”  in typical McKinsey style is a good read, but have you noticed yet that over time how big consulting companies have framed you to think a certain way.  Like it or not you have accepted their “illustrative curves” and way of thinking. If they frame a story in a familiar way you are going to accept their tried and tested approach.  You have accepted that the old worked and was true so applying it again must make sense.   This saves brain energy and learning time and it is why we love heuristics.  We have outsourced thinking and just a ccept it without considering. However ,  this overly simplistic movement from one level to another level should be reconsidered in a wider systems approach where one can look at the order of the response (first, second, third and higher)  Below is a graph showing the different order of responses to an input stimulus to force a change in the output to a new level.

Given 2020 was **** and 2021 is unlikely to be much better, what are the macroeconomics signally for 2030?

T he Tytler cycle of history provides an exciting context for thinking about the struggle between belief and power and where next. We are using this to considering the macroeconomics of where we are right now going into 2021. I am taking a view for North America and Eurozone.  This viewpoint is certainly not valid for the Middle East, Africa, South America, Russia and most of Asia.  I would love to read the same commentary from some in those regions. The observation is, where are we in the Tytler cycle?  I would propose for North America and Eurozone we are spread from liberty (the 1950 baby boomers) and dependence (massive increase in numbers due to COVID19 who are now dependent on a state.)   The majority in our society are in the Selfishness, (I am an individual and have rights) and Complacency  (my tiny footprint can only have a small impact on the climate and I cannot make a difference on the global stage).  Whilst liberty was c.1800’s and Abundance was c.1950 they are still ver

Executive Leadership Briefing. Is the data presented to you, enabling a real choice?

This article explores why senior leaders need to develop skills to see past big noticeable loud noises and uncover small signals if we want to be part of a Board who makes the challenging judgment calls. Prof Brian Cox said during his opening keynote at Innotribe/ SIBOS 2019 , give or take a bit; “if you cannot find it in nature, it is not natural.”  This got me thinking about how choice is created and then have we make decisions and judgement.  How humans choose, decide and make complex judgement draws heavily on psychology and the behavioural sciences. Alongside judgement, I have a polymath interest in quantum mechanics, microbiome and consciousness. I was relaxing and watching “ His Dark Materials ” which it turns out was worth hanging in for and had finished Stuart Russels “Human Compatible” and Carlo Rovelli “The Order of Time”.  Then whilst watching this mini-series on the BBC about free will this article emerged.  Choice has a prediction that you have agency and can choose o

Revising the S-Curve in an age of emergence

Exploring how the S-Curve can help us with leadership, strategy and decisions making in an age of emergence: (properties or behaviours which only emerge when the parts interact as part of an inclusive whole) History and context There is a special place in our business hearts and minds for the “S” curve or Sigmoid function , calling it by its proper maths name. The origin of the S curve goes back to the study of population growth by Pierre-François Verhulst c.1838. Verhulst was influenced by Thomas Malthus’ “An Essay on the Principle of Population” which showed that growth of a biological population is self-limiting by the finite amount of available resources. The logistic equation is also sometimes called the Verhulst-Pearl equation following its rediscovery in 1920. Alfred J. Lotka derived the equation again in 1925, calling it the law of population growth but he is better known for his predator: prey model .   In 1957 business strategists Joe Bohlen and George Beal published the D