Enterprise hits and misses – AI-for-good versus AI-for-yuck, edge computing hype versus reality


Enterprise hits and misses – AI-for-good versus AI-for-yuck, edge computing hype versus reality
Jon Reed
Sat, 06/19/2021 – 19:21

Summary:
This week – applying AI across industries brings use case lessons. But the AI-for-good versus AI-for-yuck issue looms, given the scale of live systems. Edge computing hype gets a reality check; cloud repatriation gets a critical look. Your whiffs include “no meeting Wednesdays” gone wrong.

King Checkmate

Lead story – applying AI across industries – use case lessons

MyPOV: The overriding view on practical AI is that your data set is a big limitation. So I was interested to check Madeline’s Porsche Formula E team races to success with AI, billed as “How to build a machine-learning system with limited data and a mixed bag of talent.”

Yes, you have my attention with that one. This use case is still a work-in-progress, but the challenges of bolstering real world data with realistic training data, and earning user trust, are worth airing. 

Let’s shift to retail with Stuart’s Drinking from the AI fountain at H&M – democratizing AI in retail. H&M’s prior AI approach wasn’t really scalable. How did they change that? Stuart’s quotes H&M’s Head of AI Foundation:

Everything we do rests on data…data enablement is the key for delivering on these values that we’re looking at. So it’s around having proper Master Data Management, having a federated data model that enables all the product teams to work autonomously on the data catalog, data lineage, compliance etc, making sure that those are in  place. But when we talk about the Fountainhead, we talk about the capabilities…When you’re doing ML ops, you shouldn’t just start from scratch with something; you need to have building blocks in place. That’s what we have done.

Next up: AI in financial services. Stuart again: AI in financial services – what sort of future do we want to see? Some considerations from The Alan Turing Institute. AI is already well into real world use in many industries, financial services included. And yet, as the Turing Institute warns, the potential for misuse and harm is absolutely real. We’ve rolled out powerful tech, with impact on constituents we don’t always grapple with. Stuart quotes from the Turing Institute report:

If firms are deploying AI and machine learning, they need to ensure they have a solid understanding of the technology and the governance around it.

That may border on the obvious, but each week, we see evidence that the obvious must not be so obvious: Facial Recognition Failures Are Locking People Out of Unemployment Systems.

Diginomica picks – my top stories on diginomica this week

Vendor analysis, diginomica style. Here’s my top choices from our vendor coverage:

Sapphire Now 2021 is a wrap, but if you’re still in a SAPpy mood, we’ll have more for you as ASUGForward kicks off next week:

Jon’s grab bag – “Employee experience” is the cure-all-du-jour, but how do companies finally move that needle? Madeline shares tips (and data realities) in HR and consumer tech – applauding best practice in employee experience. Stuart asks the kicker question in EU, US tech relations get a photo opp boost, but will this build the digital society we want or just the one we deserve?

Finally, for those weary of buzzword flatulence exuberant pitches about how the edge will solve everything cloud didn’t solve, Derek issues a practical view in Throwing cold water on the edge computing hype: “Wanting to skip over cloud and head straight for edge is near impossible, and buyers should instead be focusing on their outcomes and customer needs.”

Best of the enterprise web

Waiter suggesting a bottle of wine to a customer

My top seven

Next up, we’ve got a good AI/bad AI mashup. Let’s start with AI-for-good:

AI-for-yuck:

It’s not an setback that AI isn’t good at certain sophisticated tasks. But it’s not a comfort knowing both of these use cases are widely deployed in real world settings. Meanwhile, the collateral damage of people wronged by immature “AI” piles up. Enterprises would be wise to avoid this kind of overreach.

Project Health Check is Key to Business Transformation Success – It’s astonishing how few projects employ the kinds of independent health checks Eric Kimberling of Third Stage advocates here.

Overworked businessman

Whiffs

At this point, making fun of self-driving cars is almost too easy to qualify as a whiff. But if Kurt’s gonna do it:

I keep forgetting about this keeper via our own Alex Lee:

Hey, managers need sleep too!  As for the glorious future of hybrid work:

Might be time for “no Airbnb Wednesdays,” and add Mon, Tue, Thur and Fri to the list while you’re at it. Finally, this isn’t really a whiff, nor am I sure of the story’s veracity, but it’s a good update headline to leave on: Dog ejected from vehicle in Idaho crash found herding sheep. See you next time…

If you find an #ensw piece that qualifies for hits and misses – in a good or bad way – let me know in the comments as Clive (almost) always does. Most Enterprise hits and misses articles are selected from my curated @jonerpnewsfeed. ‘myPOV’ is borrowed with reluctant permission from the ubiquitous Ray Wang.

Image credit – Waiter Suggesting Bottle © Minerva Studiom, Overworked Businessman © Bloomua, King Checkmate © mystock88photo – all from Fotolia.com.

Disclosure – Oracle, Workday, ASUG and Salesforce are diginomica premier partners as of this writing.




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