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As management incorporates double and triple-loop learning as part of a system they are able to optimize

At a fundamental level this means: Identifying and taking ownership for obligations Making and keeping require turning “should” statements into promises with the added step of first figuring out what “should” means and responsible disclosure around data enhanced technology like AI, automated decisions and machine learning Why it matters Algorithmic and machine learning systems evolve through their lifecycle and as such it Why it matters Algorithmic systems and machine learning applications will differ by sector.

This expertise allows for proper identification of uncertainties that could lead to near or long-term In practice, the reactive nature of audits means they can be too slow and too late to prevent issues

acknowledge: AI systems don't directly observe or experience the world – they only see it through the lens AI lies not in its ability to replicate human understanding, but in its potential to complement it, leaving

essential and best done by incorporating feed-forward processes between functions as well as implementing learn

to deliver exceptional goods and services for their customers, companies are viewing customers as a means to an end – fuel for their AI engines, shiny generative models and machine learning. When customers become a means to an end, you will get that end but not any customers. – The cybernetics

Transparency in AI algorithms, data privacy protection, and addressing bias in machine learning models

compliance many of them focus on complying with prescriptive obligations mostly through the narrow lens In the rare cases where the lens is broadened it results in a stack of separate departments each addressing You only see things through the lens of past performance, and often after you hit the guard rail; hoping While this is a road less travelled it is the road to effective compliance and one that leads to better

In his world, "hazards" have a specific meaning. Different domains have their own risk vocabularies, often leaving broader threats unseen.

Investigations into the explosion are on-going and lessons learned will no doubt be used to improve

But this still leaves us with the same question, "what are you going to do with all that technology?" However, where this leads to is even more silos of computing at the individual level using software they

This week we continue our look at the nature of environmental obligations through the lens of regulatory This leaves a significant number of obligations, many of which are environmental, under-resourced, un-managed