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There is Simply Nothing Like On-The-Job Experience – OK Boomer! AI Part 1

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When I was first assigned as a district engineer, the utility company wisely put me right to work on a power line crew. A fresh college graduate on a line crew? Yes, I loved it. A tie to the real world opened my thinking to the way things actually work. Now we can make some of those ties without spending decades on the job. This blog series will look at modern data techniques like artificial intelligence (AI) and how utilities can leverage impressive new capabilities in straightforward ways.

That summer I worked for Gene, the crew supervisor. He enjoyed breaking in the new engineer - correctly. He gave me experiences alright -- digging plenty of pole holes over six feet deep by hand. Gene had 20 years on the job and had set hundreds of poles all over the district. We both recognized the value of his experience.

He knew where native rock made it very hard to dig a deep narrow pole hole. He knew where he would need the heavy-duty digger truck or a jackhammer. He knew where he would need additional employees to flag traffic and extra tree trimming. He had experience. Gene accumulated data in his mind and used it well.

As the utility workforce ages, gray-haired experience is walking out the door - the silver tsunami! Boomers are digital immigrants. They learned their way before the widespread use of digital technology. They distinctly recall solving utility problems with graph paper and pencils.

“OK Boomer” is an amusing catchphrase that gained popularity. It is used to dismiss stereotypical baby boomer views like those surrounding decades of experience. “You can’t be a good crew supervisor until you’ve had 20 years of experience!” … “OK, Boomer!”

Today, employees with less experience are being promoted earlier than their boomer predecessors. They need to be set up for success. As digital natives, they grew up with information at their fingertips. They do not feel the same glory in decades of trial and error experiences.

Astonishingly, some of Gene’s valuable boomer insights can now be gained with contemporary digital techniques. Many are found by simply bringing data together, correlating it, and visualizing its meaning. For example, GIS easily uses abundant soils data to shed light on the digging equipment needed for a particular work order, even if the crew had no direct experience in that region. The opportunities to apply GIS to straightforward applications like this are nearly overwhelming.

Now, trends are enabling AI to surge. AI crunches data with a computerized mathematical approach to find patterns and make predictions. Many of these approaches (algorithms) are open-source making them readily accessible. Current cloud resources allow anyone to essentially rent a supercomputer for a few seconds and analyze mountains of data. Analytical capability skyrockets. If you have data, you can use it to solve problems!

AI is extremely promising – think self-driving cars, more accurate labor estimates, and optimized renewable integration.

AI can also sound a little menacing to some. This blog series will help unpack AI, make it more approachable, and answer some questions.

  • What is it?
  • What can it do for utilities?
  • What about data?
  • How do you actually use it?

For over 100 years, experience has been the holy grail of utility work. Will AI replace knowledgeable employees? No. Yet, AI is causing a shift -- adding new ways to discover insights formerly only available through experience.

 Remember this – AI is all about data, and location is absolutely crucial for utility data. It is compelling to include location technology in the AI process. There is no better way to incorporate location and exploit AI than with ArcGIS. AI can help utilities address their many challenges. See new ways to use data, discover its meaning, and enable people to work better together by downloading our free ebook

Pat  Hohl's picture

Thank Pat for the Post!

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Discussions

Matt Chester's picture
Matt Chester on Jan 27, 2020 11:14 pm GMT

For over 100 years, experience has been the holy grail of utility work. Will AI replace knowledgeable employees? No. Yet, AI is causing a shift -- adding new ways to discover insights formerly only available through experience.

I think it'll also go further than that-- not just insights formerly available through experience, but also generating new insights that even the experienced employee may have missed (and perhaps even stubbornly disagreed with if the data wasn't there to back it up)!

Pat  Hohl's picture
Pat Hohl on Jan 28, 2020 3:57 am GMT

Yes sir! 

Bob Meinetz's picture
Bob Meinetz on Jan 28, 2020 7:25 am GMT

"Astonishingly, some of Gene’s valuable boomer insights can now be gained with contemporary digital techniques."

Astonishing is how often technology has been judged a suitable replacement for experience, and how predictably and miserably it has failed.

Guess you'll have to learn the hard way (talk to the electrical and structural engineers who designed the Boeing 737's airframe and avionics).

Matt Chester's picture
Matt Chester on Jan 28, 2020 1:59 pm GMT

I think if you consider the whole of this article, you'll see it's not about replacing experience with AI, but using it as a tool that can augment and enhance the insights available when put in the hands of those with experience and who understand the context:

Will AI replace knowledgeable employees? No. Yet, AI is causing a shift -- adding new ways to discover insights formerly only available through experience.

 

Bob Meinetz's picture
Bob Meinetz on Jan 31, 2020 4:00 pm GMT

How does AI discover an "insight" Matt?

insight n. the capacity to gain an accurate and deep intuitive understanding of a person or thing.

By definition, insight is beyond the realm of artificial intelligence.

Matt Chester's picture
Matt Chester on Jan 31, 2020 5:23 pm GMT

OK, got me with semantics there-- but the fact is if AI extracts useful data that would have taken immense time and effort for a person (who is prone to human error) and presents them in useful and clear ways for the employee who can then take that information and apply their knowledge and act upon that. AI + experience will deliver more value than experience alone, and those with the knowledge should welcome these advances that can enhance their abilities

Bob Meinetz's picture
Bob Meinetz on Feb 2, 2020 4:50 pm GMT

"Got me with semantics" is sometimes used to dismiss arguments by relegating them to linguistic nit-picking - that for some words, arguing about precise meaning is unimportant. It's gradually becoming clear, however, that accurate and impartial definitions of words like intelligence and intuition are important - in direct proportion to the importance of the results they deliver.

In the 1950s, as computers began to perform increasingly complex calculations with astounding rapidity, it almost seemed as though they were capable of human thought, and the term artificial intelligence was born. It's true - when the results are relatively unimportant, such as rounding to the nearest dollar on my tax return, my iMac is a scholar, a genius.

But when friends insisted the day would come software would be able to make any decision for me, regardless of its importance; to drive my car, identify my priorities, even buy a house for me, I was inspired. I contemplated a security device - an AI Security Hat. When walking the most dangerous, crime-plagued areas in town, digital video cameras embedded in the hat would use complex AI algortithms to instantly identify approaching criminals intent on robbing or harming me, and incapacitate them with an embedded firearm. No more looking nervously about for threats - I could go about my business, confident in the knowledge I would be protected wherever I walked.

My friends have resisted investing in my invention, however. They say "that's different" - when the only difference is the importance of the decision my hat would be making.

"AI extracts useful data that would have taken immense time and effort for a person (who is prone to human error)..."

But the human who engineers the AI which determines what data to extract, what data is useful, is incapable of error? Or do these contemporary AI techniques spring into existence by themselves?

Pat  Hohl's picture
Pat Hohl on Feb 6, 2020 8:26 pm GMT

I appreciate the discussion. Webster's definition: 

1: the power or act of seeing into a situation

Sean Clark's picture
Sean Clark on Feb 6, 2020 6:50 pm GMT

Currently available intelligent solutions engine platforms, like AMMI's PRISM (PRedictive Intelligent Solutions Modules), while not quite true AI, are capable of aggregating critical rulesets, knowledge, and experience in a way so as to perform mega-data analyses, decision-making, and solutions development faster, cheaper, and with far more predictability and certainty than even acheivable with the best expert-dependent processes today.  It is still absolutely necessary to capture the pertinent knowledge and expertise from all us old Boomers, as well as that of all the younger workers going forward, for such platforms to be totally effective.  PRISM is fully integratable with most existing data acquisition and management platforms, and works on virtually any hardware platform.  It may not be perfect, but it is a very important tool to address the loss of knowledge and expertise posed by the retirement and attrition of Boomer workers, as well as the challenges posed by the highly mobile nature of Millennials, Gen X'ers, and Gen Z'ers.

Susan Brissette's picture
Susan Brissette on Feb 10, 2020 3:03 pm GMT

"Today, employees with less experience are being promoted earlier than their boomer predecessors ... They do not feel the same glory in decades of trial and error experiences." This is a good example of real differences in attitudes and motivators between younger and older workers. The introduction of new technologies is not new, and boomers in their youth would also have embraced and adapted to technology's relentless march. The above quote highlights 2 issues ... what gives employees a sense of pride, value and accomplishment and how do we learn from mistakes. Rita May Brown's quote "Good judgment comes from experience, and experience comes from bad judgment", is a truism that is appropriate for the boomer generation but is it still applicable for Millenials and GenZs navigating a world dominated by AI? AI carries much potential, including the elimination of some types of human error and risks. However, AI will undoubtedly introduce new types of errors and risks. What problem solving and other skills will younger workers need to develop to identify and address those new risks and error likely situations, and can the acquisition and demonstration of these skills bring value to corporations while instilling a sense of pride in younger workers? Perhaps boomers and millenials - humans - have more in common than it might initially appear!

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