I get extra excited each day as I study one thing new. Nonetheless, I even have my justifiable share of issues in regards to the future—particularly on the subject of AI and the way it will affect the position of community engineers. Okay… I most likely have extra than my justifiable share of issues. (That received’t come as a shock should you’ve been following the previous few years of my journey, exploring the “AI FUTURE!!!”)
First off, I wish to be very clear. I’m excited about the way forward for community engineering, community automation, and my place on this great world and group. The truth is, my current weblog, Navigating the AI Period as a CCIE, discusses how superior it’s to be a CCIE proper now.
I typically deal with the place I see the constructive potentialities. How AI could make our lives and work as community engineers higher.
However at present, I wish to speak about one thing that worries me: how the AI future is being mentioned and described. My hope is that by discussing it, we are able to keep away from the worst potential dystopian imaginative and prescient of that future. Whereas I like studying books or watching films about these dystopian futures (a responsible pleasure of mine), I don’t wish to stay in a kind of worlds. I’m additionally hoping that you just, my group, will help me perceive whether or not my concern about the way forward for AI is overblown. So, let’s dive in, lets?
I don’t wish to be an AI babysitter…
There’s a phrase that has been displaying up in shows, blogs, articles, movies, press releases, authorities documentation, and nearly in all places else discussing how AI will affect the way forward for work. The phrase refers to an strategy referred to as “human-in-the-loop.”
So, what is “human-in-the-loop?”
I simply did a Google seek for “‘human within the loop’ ai cisco” and Gemini was useful in giving me this abstract:
Cisco emphasizes “human-in-the-loop” AI, which means integrating human oversight and suggestions into AI techniques to make sure accountability, moral issues, and dependable decision-making, particularly in areas like safety and knowledge evaluation.
That doesn’t sound dangerous, proper? Right here’s one other snippet from a paper I lately learn on AI and the way forward for job roles:
The extent to which it [Gen AI] can substitute people within the office will depend upon the need for human oversight of machine-performed duties.
Little question you’ve seen or heard comparable descriptions of what it’ll take to “safely” combine AI into day-to-day duties. Right here’s my understanding of why human-in-the-loop comes up time and again in discussions.
It comes down to a couple factors:
- Utilizing AI affords a “worth” companies can NOT ignore. What that worth is can differ, nevertheless it typically comes down to hurry: AI is solely sooner than people.
- AI isn’t all the time proper. And AI can’t be held accountable for errors.
- By having a human log out on the AI work, errors will probably be caught. And in the event that they aren’t, there’s somebody to be held accountable.
I’m NOT saying that the above factors are factually legitimate. The truth is, every of these statements on their very own deserves a variety of deep consideration and dialogue. However for the sake of this weblog publish, let’s take them as they sit to additional discover my issues a couple of future the place Hank is a “human within the loop” for AI techniques.
Right here’s the issue with “human-in-the-loop”
I like being a community engineer. I like creating community designs to fulfill enterprise calls for. I take pleasure in creating configurations and engineering strong routing protocols. I discover the method of troubleshooting a community situation rewarding.
I’ve spent years of my life studying the talents it takes to DO community engineering. And I nonetheless have a few years forward of me as a community engineer. I even have lots to supply the businesses, networks, and staff members I’ll work with sooner or later.
Each description I’ve learn or heard about “human within the loop” locations the human close to or on the finish of “the loop.” An AI device is posed an issue, query, or set of knowledge to work on. Then, AI generates its answer, which is then despatched to a human to evaluation, settle for, reject, or make adjustments.
After I take into consideration this idea, I can’t assist however conjure up an image of row after row of people spending their days listening for the “ding” of a brand new proposed AI work merchandise, ready for the human to do their factor so the AI can proceed on its “loop,” finishing the work. That simply doesn’t sound like the longer term community engineer I wish to be.
Which is able to come first: AI or expertise?
There’s something else I ponder about on this “human within the loop” imaginative and prescient of the longer term. A human community engineer’s potential to establish a mistake made by AI depends on whether or not that community engineer has made that very same mistake previously. Or, on the very least, they want sufficient community engineering expertise to note when one thing is mistaken.
As of now, we’ve got skilled community engineers who can “oversee” AI brokers and establish potential points. Heck, that’s half of what senior community engineers and CCIEs do anyway: help the up-and-coming community engineers on our staff by reviewing their work and serving to them study from their errors.
However how will future up-and-coming community engineers achieve the expertise of being a community engineer if they’re merely a cog in “the loop?”
And sure, I’m absolutely conscious that that is an excessive instance and never what individuals imply after they say “human within the loop” or “human oversight.” Regardless, it’s vital that we think about such a excessive end result now, when the way forward for community engineering is being written. As a result of I completely assume there’s a means this narrative may be circled—a future imaginative and prescient the place community engineers proceed to be community engineers greater than in identify solely.
Let’s flip it round: “AI-in-the-loop”
I suggest that we invert the loop. Make no mistake—synthetic intelligence completely affords worth to community engineers doing community engineering jobs day in and time out. The truth is, I take advantage of it myself. However I take advantage of AI as a useful resource—like every other—at my disposal.
Suppose I’m referred to as in to troubleshoot an intermittent routing drawback at our Web edge. Utilizing my well-worn community troubleshooting expertise, I collect particulars in regards to the situation, carry out completely different checks, and attempt to replicate it. I examine operational output from the routers and have a look at our community administration techniques. Possibly I ask round, “What modified?”
And if everybody tells me, “Nothing. Nothing modified.” I then ask, “Properly, what modified earlier than nothing modified?”
As I do all of this, I leverage many instruments and sources. I’ll seek the advice of our inside documentation in regards to the community. I’ll evaluation the current change requests. I would head over to Cisco.com and seek for error messages or eventualities. (Properly… no, I’ll most likely go to my favourite search engine and seek for error messages and eventualities. 🙂 )
It’s right here, throughout this a part of my work, the place I’ll carry AI into “the loop.” Not solely is AI quick, nevertheless it has been skilled on and has instantaneous entry to all kinds of helpful knowledge that’s related to my work.
AI-in-the-loop: A device for community engineers
I could also be struggling to recollect the precise present command to show all the small print in regards to the BGP prefixes realized by my router. Or I’ll wish to arrange a filtered packet seize and am on the lookout for an instance configuration. Or I’m reviewing a whole lot of strains of debug messages and will use assist in shortly discovering the anomalies. These are examples the place AI could make ME a greater, extra environment friendly community engineer.
You see, I’m a community engineer. I’m a fairly first rate community engineer. I’ve typed hundreds of thousands of CLI instructions with my fingers, seen numerous pings drop, configured routing protocols, entry management lists, VPNs, coverage maps, EtherChannels, and so forth and so forth. However I’m nonetheless only a human, not a pc. I’ll not have instantaneous entry to all the things buried in my mind, however I do know when the reply is in there. I do know that if I see the right reply (or one thing shut), I can acknowledge it and get to the answer. It’s the identical cause an skilled community engineer can remedy a posh drawback with one net search and a look at a discussion board publish or Cisco command reference.
We should always keep within the driver’s seat. We should always keep accountable for the networks and the community engineering. We should always embrace the capabilities of AI to enhance our community engineering work. AI shouldn’t be utilizing us to enhance its community engineering work—we must be utilizing AI as a useful resource to develop into more practical community engineers—now and into the longer term.
Actually Hank… is that every one AI must be?
So, you is perhaps considering:
Oh, Hank, you good outdated boomer community engineer. Get with the occasions… AI affords us far more than only a next-generation search engine!
Sure, it completely does—and I’m enthusiastic about a variety of the enhancements to the techniques and software program we use each day. To not point out the utterly new techniques and software program which are enabled by AI. Simply Cisco’s bulletins within the AI area this previous yr excited me about its potential for community engineers.
Simply think about what we’ll have the ability to do sooner or later. For the reason that first community engineer began capturing log knowledge, we’ve acknowledged that it’s almost unattainable for a human engineer to make sense of the flood of data in any well timed trend. Consider all of the outages that would have been prevented if we had been capable of finding the small and early hints buried in counters, NetFlow knowledge, and log particulars. As for safety… wow. There’s a lot potential within the safety area to establish and reply sooner.
Embedding AI capabilities into networking merchandise will give us a large enhance as community engineers. However this additionally isn’t something all that new. For a few years now, machine studying capabilities have been added and iterated on to boost the community assurance options for the campus, WAN, and knowledge middle. They’re getting a brand new enhance from the GenAI hype and buzz proper now, however most of them aren’t GenAI.
One thing is coming to the community engineers’ world that pertains to GenAI that has me very, very excited. Pure Language Interface, or NLI, will quickly be a part of the a lot cherished and lauded Command Line Interface (CLI) and the slightly-bummed-it-isn’t-the-new-kid-on-the-block-anymore Software Programming Interface (API) as strategies community engineers work together with the units and techniques we handle. And that will probably be superior. Really, a sport changer.
Sure, a part of changing into a community engineer is studying all the particular instructions required to make the community work. When community engineers collect collectively and share conflict tales, somebody will all the time complain (lovingly) about the way it is not sensible that it’s “ip ospf authentication-key” however “ip authentication mode eigrp,” and why can’t they only be the identical?! And we’ll chortle and chortle and chortle.
However let’s be sincere. It isn’t memorizing particular command line syntax that makes us community engineers. It’s realizing how, why, and when we have to configure authentication for our routing protocol that’s necessary. Gained’t we be a lot happier after we can merely inform our router:
“Allow authentication for EIGRP and OSPF on all interfaces. EIGRP ought to use md5 with key-chain 5, and OSPF wants to make use of plaintext due to the legacy system we’re linked to.”
Positive, some community engineers will grumble and say issues like “again in my day.” However I do know I’ll be happier for all of it.
So what now?
So what now, you ask? Properly, I wish to hear what you all assume. Don’t be shy. When you assume I’m overreacting, please inform me. When you share my issues, let me know I’m not alone. What excites you about the way forward for community engineering with an AI assistant in your pocket? Are there some duties you’ll be able to’t anticipate AI to take over for you? Go away a remark beneath to let me know your ideas!
Within the meantime, listed below are some solutions for wonderful locations to study extra about AI and begin constructing expertise. As a result of there’s one factor I’m completely positive of… AI is coming, and we gotta be prepared for it.
- Spend about 45 minutes Understanding AI and LLMs as a Community Engineer with this nice tutorial by Kareem Iskander.
- Make investments extra time on this wonderful Community Academy course, Introduction to Trendy AI, with my new favourite teacher, Eddy Shyu. (Don’t let the truth that it’s on Community Academy scare you away. It’s implausible for anybody trying to get a strong basis in AI.)
- Dive in deep and “Rev Up” your recertification journey (34 Persevering with Schooling credit!) with AI Options on Cisco Infrastructure Necessities. Free in Cisco U. till April 26, 2025, and with content material and movies from 5xCCIE (and my hero) Ahmed Moftah.
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