I made the mistake this week of “upping my game” and attending two tech events that the experts hosting them described as “entry level.”
Unless post graduate, PhD, or decade-plus experience counts as the new “entry level,” they definitely were not “entry level.”
At one event, I hoped to understand the state of play with machine learning, specifically, its approach to causality. Without going into a yuge amount of detail, causality has huge implications for AI, decision support, risk management and crisis response management and the planning thereof, assuming it actually works. So, does it?
I was informed that this would be “the Wikipedia article version” of said subject, and I probably grasped about half of what was said.
I’m going on the record with my disappointment that data analysis still rests on statistical assumptions, that I don’t want it to rest on.
I want real data. Thanks.
If machines are programmed to work things out the way we already do given our existing limitations, such as our assumptions, then they’re only thing to make the same mistakes that we already do, on a larger scale.
At the second event, (which was the first chronologically speaking) it’s difficult to know who the audience is.
I appreciate that information technology operations are highly detailed, and constantly changing, but I’m not the only one here sitting in total dumb-foundedness at the monotonous monologue that issues from the presenter’s mouth, (never an effective move). We sit through whatever this is without the examples that were promised making this tedious and effortful. There is no reason that the words that are tumbling out have been chosen and if the configuration of Azure has been done correctly then a lot of this noise is unnecessary as it won’t let me deviate or depart from the process flow.
I grasp the idea of “virtual machines” and also containers, and the difference between them, and why you might choose one and not the other, by googling the answer.
I grasp that Azure is Microsoft’s cloud storage product, several times over (but not much else,) and the chairs we’re seated in, at this brand new HQ, are so wildly uncomfortable that my backside goes numb in record time, forcing me to have to sit to one side and then the other. (As a rule, I wouldn’t normally admit to any bodily discomfort at a public function, least of all in a public forum, but this was remarkable.)
Get rid of the chairs! Their backs flex.
At least one of the challenges facing technologists, (and confronting me as a communicator, on a regular basis,) is the unfortunate habit of re-purposing words that already have a popular meaning, to mean their opposite, (for example ‘hack’) or something that they just do not mean, for example ‘policy’.
(Sidenote. Dear IT industry. Is there an app for coming up with new words, perhaps using Greek, Latin, or Norse, or some non-US English modern language roots, that you might be able to deploy to make new meaning-filled, technically accurate words?
For inspiration, please refer to ‘The Surgeon of Crowthorn’ and the method etymologyists use to unpack and come up with word forms. Thx)
More than once my purpose on a project has been to explain in lay terms how the information system either is or isn’t going to work the way that management thought it might, whilst co-designing the human, manual, prerequisite inputs, interim and subsequent steps and workarounds that make up a process workflow.
In that role, in an Azure environment, I would be at pains to explain that what I.T. means when it uses the word ‘policy’ does not meet the test of a policy is, and that what they’re describing as a “policy” is at most”a business rule.”
I work in government environments. As you might imagine, they already struggle with ‘big p’ and ‘little p’ policy, by which they mean
- public policy: “we shall have a transport system funded by taxes and administered by departments” and
- corporate policy “Employees are responsible for securely holding their ID pass, reporting its lost and not allowing its misuse”.
A policy, big or little, is a statement of principle.
As examples go: ‘Thou shalt not kill’ is a pretty good one. (Also, fairly universal. It doesn’t need to be a law for people to go, hey, yeah, I can remember not to do that.)
‘Be a good person’ is another one.
Don’t misuse the corporate resources is another.
Public or corporate, policies are like the Ten Commandments, both in the sense of portent and serious consequence they convey, and how few of them one requires.
I am afraid, my dear Microsoft, that a list of permitted websites and a second list of prohibited ones, are not in any meaningful sense of the word a ‘policy,’ let alone two separate policies.
What they are, is a set of dot point specifics made pursuant to IT security rules, and the higher level principle, or policy that we don’t allow staff to access inappropriate content, whether that content is illegal, obscene or malicious, or only prospectively so.
If you would like help in defining your business rules and mapping these to policy, as part of your corporate governance and its technical manifestations, I am available for hire.