Lead story - Barriers to AI project success - skills, regulation, and bias<\/p>\n
MyPOV: Say this for AI projects in 2021: the obstacles are coming into focus. In his article Main barrier to AI in the enterprise now skills, not culture, Derek cites an O'Reilly AI report, which found:<\/p>\n
Looking at the problems respondents faced in AI adoption provides another way to gauge the overall maturity of AI as a field. Last year, the major bottleneck holding back adoption was company culture (22%), followed by the difficulty of identifying appropriate use cases (20%). This year, cultural problems are in fourth place (14%) and finding appropriate use cases is in third (17%).<\/p>\n
Data challenges persist, but this year, the top AI obstacle is skills. O'Reilly again:<\/p>\n
The biggest skills gaps were ML modelers and data scien? tists (52%), understanding business use cases (49%), and data engineering (42%). The need for people managing and maintaining computing infrastructure was comparatively low (24%), hinting that companies are solving their infrastructure requirements in the cloud.<\/p>\n
In sum: this report indicates AI projects are maturing, but maturity brings its own challenges. As Stuart notes, in Uh oh, AI, EU - what could possibly go wrong? The risky business of regulation, regulatory barriers remain. One huge issue: vague definitions, forged by policy makers without the AI chops. Stuart:<\/p>\n
Without crystal-clear definitions, tech firms developing AI futures will be at the mercy of regulatory box-tickers whose understanding of the underlying tech is little better than those opportunistic politicians who stand up and declare that something must be done.<\/p>\n
Then there is the potent problem of AI bias. Neil revisits, via a fruitful LinkedIn exchange: Is there good bias in AI, or is AI bias always undesirable? Responses to a LinkedIn debate.<\/p>\n
Diginomica picks - my top stories on diginomica this week<\/p>\n
Vendor analysis, diginomica style. Here's my three top choices from our vendor coverage:<\/p>\n
A few more vendor picks, without the quotables:<\/p>\n
Jon's grab bag - Content marketers are flummoxed and tantalized by the potential of audio and video - but it's not text. That means SEO curveballs. Barb looks at where the traction is, including multi-purposing content across mediums, in Casting an eye over the future of content marketing - Casted CEO Lindsey Tjepkema on the role of audio and video.<\/p>\n
Put aside your quantum-computing-will-save-the-world-hangover buzzword overload, and check Chris' hype-free review of the quantum computing use cases: \"Khan believes that quantum computers could serve humanity well in two ways: either by doing things that classical computers are unable to do, thanks to the limitations imposed by the laws of physics; or by carrying out calculations much, much faster.\" (Giant leaps from small things - UK quantum firm sees reason).<\/p>\n
Finally, Stuart (properly) undermines Netflix's wet noodle excuse that their slowing numbers are about the end of the pandemic. It's about the competition, and a brutal pun from headline maestro Stuart: A tale of two broadcasters - why Netflix's post-COVID slump is the talk of The Ton.<\/p>\n
My top seven <\/p>\n
This last year in a nutshell: a woman called police on a home intruder - but it was her robot. Meanwhile: Apple Must Face Lawsuit Over iTunes \"Buy\" Button. It's about time, though Apple is hardly the only offender in the \"own this movie\" scamjob.<\/p>\n
My colleague Phil Wainewright spotted this one:<\/p>\n
Perhaps, but:<\/p>\n
Yeah, this happened a few days ago:<\/p>\n
Yep, I'm calling a self-whiff. That's what happens when you don't replace your placeholder text before you hit the \"publish' button. And, I reached another event overdose:<\/p>\n
Bring on the patio grills please:<\/p>\n
A guy can dream - see you next time...<\/p>\n
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.<\/p>\n<\/p>\n
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Link: <\/p>\n
Enterprise hits and misses - AI confronts its project barriers, ERP gets buried, and IBM pulls an earnings surprise - Diginomica<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Lead story - Barriers to AI project success - skills, regulation, and bias MyPOV: Say this for AI projects in 2021: the obstacles are coming into focus. In his article Main barrier to AI in the enterprise now skills, not culture, Derek cites an O'Reilly AI report, which found: Looking at the problems respondents faced in AI adoption provides another way to gauge the overall maturity of AI as a field. Last year, the major bottleneck holding back adoption was company culture (22%), followed by the difficulty of identifying appropriate use cases (20%) Continue reading