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Is it better to prevent or correct?

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This link gives you access to all the articles and archives for </Hello CDO> “Prevention or Correction” is something society has wrestled with for a very long time. This article focuses on why our experience of “prevention or correction” ideas frames the CDO’s responsibilities and explores a linkage to a company’s approach to data. Almost irrespective of where you reside, we live with police, penal, and political systems that cannot fully agree on preventing or correcting. It is not that we disagree with the “why”; is it the “how” that divides us! I am a child of an age when lefthandedness was still seen as something to correct, so we have made some progress. A fundamental issue is that prevention is the best thinking; but if you prevent it, it does not occur. We are then left with the dilemma, “did you prevent it, or was it not going to occur anyway?” The finance team now ask, “Have we wasted resources on something that would not have happened?” When something we don’t lik

Why I think that asking if “AI can be ethical” is the wrong question!

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Many ask the question “can AI be ethical?” which then becomes a statement “ AI must be ethical! ” In reality we do not tend to unpack this because it appears so logical, but maybe it is not as obvious as we would like. In May 2021 I wrote this article “ What occurs when physical beings transition to information beings? ”  It started to question what happens when an AI does not have the same incentives and bias as humans.  It was building on this the idea that an # AI should not make complex decisions about wicked problems that involve compromise.   There is an implicit assumption in the question “Can AI be ethical?,” that AI is either fundermentall not ethical or is already amoral today but #AI must somehow become ethical and have morals. (or worst it must adopt ours.)   I am not sure AI cares if it is ethical or not but that is a different piece of thinking which I explored here “ Can AI be curious? ”.  We know carbon forms can be curious but we worry about a silicon form being curi

Testing the fitness of your organisation's preparedness for data.

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Click here to access all the articles and archive for </Hello CDO> Day zero, you have arrived and you have 100 days to plan. ( H 0 ) How do you determine if your new company is addressing the underlying issues that hold back data from being what they imagine it can be?  The issues that hold back an organisation from really capturing the value of data are at a  minimum: org structures, people issues, a lack of accountability, and incentives. Whilst having a CDO, doing data science, having analytics, using artificial intelligence, testing data quality, and a world class data governance structure make a difference; true transformation will remain a struggle if the structural issues remain. The question is how do we, as a CDO, test the fitness of our organisation's preparedness for data.  If the results are acceptable to the leadership team is one of politics and is way beyond  the scope of this article.   To test the fitness of your organisation's preparedness for data, it

What happens when is tension is too low to improve performance or conflict too much to bare?

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Right now, in your current situation, you are asked to or informed to, undertake or perform certain actions.  When these instructions and activities align with your natural instinct it is easy.  When there is a lack of alignment we know that there are tensions, contradictions, conflicts and compromises created.  Often these creep up on us, where one small thing leads to another until the snowball is in full avalanche mode.   When you feel that comfort blanket of alignment, you should use the peak paradox framework to look for paradoxes, because you are aligned.  It does not mean everyone is aligned or you are doing the right thing, but it feels easy.  The sense of natural alignment is a conformational bias that is hard to fight, but it is time to focus on where paradoxes can exist. When that comfort blanket is missing and we are in the open white waters of turmoil, the Peak Pardox framework is designated to unpack where and from who and what decision means you feel destructive tension

#Identity. Are we (the industry) the problem?

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How many people do you need before identity has value - two! How come, as an industry where 3.2bn ( McKinsey ) people have a digital identity, are we so fragmented, uncoordinated and disagreeable?  It is evident that our ongoing discussions about identity, ethics, bias, privacy and consent revolve around a lot of noise (opinions) but little signal (alignment), but why?  Recognising that in 30 years of digital identity, we still lack coherent and coordinated action to make it work for everyone is a reality. Perhaps it is time to recognise that it is “us”, the industry, who are the problem.  We continue in our self confirming opinions, righteous products and determination to win at all costs.  I am not saying we have not made progress or done amazing things, but we have not done as well as we should have! As identity now takes several forms insomuch that it emerges from interactions with a system (say payment & reputation), is foundational (given by an authority, a credential), and

CDO Day 0 - The many faces of evidence

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Click here to access all the articles and archive for </Hello CDO> A very modern problem for leadership, executives and boards is, in fact, a very old problem; it is just that the scale, impact and consequences have increased.  Evidence .   There are two sides to the evidence coin, the proof the problem is the priority problem for scarce resources, and the other side is that that solution is the one that will drive the outcomes we desire.  Very different evidence requirements, and each side have many faces. Complexity and uncertainty mean that the historical preference for gut feeling and big leadership power plays provide insufficient rigour in the decision-making process. However, evidence gathering and presentation have similar issues.   Evidence can always be found to support the outcome you want (is this a problem or not), and incentives mean that evidence about which solution creates the best outcome will be lost, reframed and distorted.  Unpicking these two sides and man