The logic of automated decisions;
ransparency through audits ..?

Not bashing, nor FUDhyping…
Was triggered by various treads, e.g., The Book on the subject (or, het boek in Dutch), and scores of elucidation (yes. be happy finally there is some truly) from the legal perspective, on GDPR article 15.1h and article 22.

The latter two not being conclusive, however. They are about requirements of transparency on the logic underlying automated decisionmaking. But there is no clarity about how deep that should go. Will “Hey your data is processed by some AI system [literally, factually incorrect statement because it’s only Machine Learning at max, today; does that construe a false statement i.e. fraud ..? ed.] and even we the builders ourselves have no clue what goes on in there – that’s the whole point of using it besides being able to fire a great many inherently expensive humans and we don’t care the least about the biases and other grave errors of the system it works fine for us!” be acceptable? Hint: No. Will “Oh it’s so intricate that we, let alone you, have no clue when looking at the audit trails that the system generates” fly? Same hint.

Because here, we see a new area developing for IS auditors: Auditing ‘AI’ [quod non but read ‘ML’ and you’re good; ed.]. As IS auditors are (supposed to be, I happen to know a fair share of peers … etc.) the experts in gauging systems functioning qua .. reliability overall, too. Which goes way beyond mere C-I-A but still, has Always been part and parcel of IS auditors’ education, right ..? I will come back to you soon, with more definitive info on how IS auditors should go about this all.

Oh by the way yes I did already notice that the more the system in scope behaves, and is constructed to behave, intelligently like the average (sic! statistically you have zero reason to put yourself above that! oh wait you read my blog so you are definitely, way off the right end of the scale) human, the more the audit will have to be like we audit humans today. Uniting psychoanalysis and explicit rules on paper (in procedures, algorithms et al.), very dogue much fun.

[Though a flat, and has iron, legally misidentified as flatiron …; NY – Pic tilted to fit in the pic frame of course]

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