[TriEmbed] Intellectual and technical debt and machine learning cautionary article

[Mark Sidell]

For an amusing take on ML, see  "Machine learning failures - for art!" by
Janelle Shane: https://youtu.be/yneJIxOdMX4

My favorite joke generated by a neural net: How many engineers does it take
to change a light bulb? A star an alligator and because they are bees.

Favorite pick-up line: You look like a thing and I love you.

Mark

On Sat, Jul 27, 2019 at 3:10 PM Pete Soper via TriEmbed <
triembed at triembed.org> wrote:

> Reading the article below my first reaction was "so it isn't just me",
> as, many years ago, when a buddy at Motorola Research was describing his
> study of neural networks relating to making smart car technology, the
> "inside" of the network was a black box and in the decades since I
> haven't found any explanation of how they work that doesn't boil down to
> another figurative black box as far as the mappings of inputs to outputs
> for a particular pattern recognition use case after training sessions.
>
> So I was relieved to find the inner workings of machine learning (ML)
> systems can be just as impenetrable to others while also being
> distressed to read about a cat being declared guacamole after (human-)
> indiscernible changes to image files as described in the article.
>
> The two major topics that are explored, intellectual and technical debt,
> seem like the kind TriEmbed folks may find interesting both generally
> and in regards to ML.
>
>
> https://medium.com/@zittrain/from-technical-debt-to-intellectual-debt-in-ai-e05ac56a502c
>
> -Pete
>
> PS Yesterday Dan Stipe and I were marveling at a technical book offer by
> Amazon for the low low price of $4800 plus $3.99 shipping. Now I
> understand where this may have come from!!
>
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