Despite all the hype and buzz, I am sometimes surprised at how little most people truly understand about artificial intelligence (AI) and how it works. It seems that they either believe that other than Alexa and Siri, it’s all hype — or that we are on the verge of a Terminator-like apocalypse.
Even more surprising, however, is how people see AI in the context of the so-called Future of Work. Again, they either see it as having virtually no impact — or they see the coming decimation of almost every job known to man.
Neither extreme is correct. But the real question, then, is how will AI really affect your future?
The Big Idea: AI, Automation and the Future of Work
As you hopefully picked up on during the introductory series, I believe that we will automate almost anything that we can reduce to an algorithm. (And if you didn’t pick it up, please tell me because I said it like 7 times!)
This process began some time ago (long before AI was really a thing) and will continue apace, picking up steam over the next several years. While I think it’s impossible to say exactly how quickly this transition will occur, I believe that it’s going to happen sooner rather than later.
The automation of anything we can reduce to an algorithm (which is basically what AI is doing), will impact most jobs that humans are presently doing. The trick is that while it will impact most jobs, it will not eliminate most of them. Instead, what we’re going to see is that the application of AI will dramatically transform the jobs that humans do.
To understand the full ramification of this nuance, you need to start by understanding what AI really is and how it works.
I’m not going to go into all of it here, but the first thing to know is that AI isn’t a technology. It’s a broad category of technologies (and ideas, really). Under that banner exist a number of technologies that you’ve probably heard about, like machine learning, natural language processing (NLP), deep learning, and many others. Each of these technologies are developing and evolving at different rates — and each of them address different elements or types of so-called digital intelligence.
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Moreover, all of these technologies fall under a sub-category of AI called Artificial Narrow Intelligence (ANI). ANI is basically intelligence that is focused and purpose-built, meaning it is artificial intelligence applied in a specific manner to achieve a specific objective.
This is distinct from Artificial General Intelligence (AGI). If all of this SciFi, apocalypse stuff happens, the achieving of AGI is what will trigger it because it’s when machines will begin to mimic human capabilities in all ways and could potentially become sentient. (If you want to dig deeper into understanding all of this, and I suggest that you should, read The AI Revolution: The Road to Superintelligence by Tim Urban on his blog, Wait But Why.)
The big question is whether or not we will ever achieve AGI — or if we should even try.
But for the foreseeable future (even rosy estimates put us at least 20-30 years away from AGI), what we’ll be working with is ANI technologies — and that fact will dictate how this will really impact your future.
The Impact: Should I Be Worried About ANI?
Given that ANI is technology-powered intelligence focused on a specific set of narrow tasks and objectives, and given that until we reach AGI it is highly unlikely that we will see machines perform activities that require things like creativity, imagination, or empathy (although they may be able to fake it), you can start to see the outlines of the real impact of AI on your future.
I would argue that most jobs that humans do today involve a mix of routine tasks that we can reduce to an algorithm and tasks that require varying degrees of creativity, imagination, and empathy.
So, as we look toward an ANI-powered future, we will primarily use AI to augment current jobs by automating all or most of the algorithmic elements and leaving humans to do the parts that require humanness.
The challenge is that some jobs have a very high percentage of algorithmic activities and others have a low or medium level.
Those jobs that have high levels of algorithmic elements will either be eliminated outright, with any non-algorithmic functions moved to other employees, or they will be subject to heavy consolidation. For all practical purposes, even if these roles continue to exist, they will no longer look anything like their current state.
Those jobs that have low-to-medium levels of algorithmic activities will see an up-leveling transformation in which employees are able to leverage various forms of AI to do the repetitive elements of their jobs and will replace the time they would have otherwise spent doing these activities with higher value functions.
Even in these cases, however, expect the nature of these job functions to look very different by the end of this process. Even if only 30-50% of a job is automated, the automation itself will change the nature of that work with greater value being placed on leveraging the results of the automation and adding human elements to it.
No matter where your current job stands on this spectrum, however, the critical path to future relevance demands that you stop focusing on specialized, but ultimately replaceable, skills and instead focus on developing and enhancing your human capabilities.
The Next Step: AI-Proof Assessment
In the end, the only person who can really and truly assess the impact that AI may have on your job is you. In your heart-of-hearts, you likely know the degree of repetitiveness of your job function.
This week’s exercise is to bring this to the surface.
Using a simple two-category list, break down your current job function into the specific things that make up what you do on a regular basis. As you do, place each activity into one of two columns: algorithm or human.
Before you begin, a few notes.
First, anything that we cannot reduce to an algorithm, by definition (at least for our purposes) should fall into the ‘human’ category. You will find, however, that these elements of your job are going to largely be either creative, imaginative, or empathetic elements. If they’re not, you should double-check it.
To that point, you must be very careful that you are assessing the algorithmic potential correctly. Many knowledge workers do very complex tasks that, on the surface, may not appear to be algorithmic. When you begin to break these tasks down, however, you will realize that, instead, they just represent very complex algorithms, but are algorithms nonetheless.
The more complex the algorithm, the harder it will be for a computer to automate it, but it should still be placed in the algorithm category. If you like, feel free to rate the level of complexity.
The result of breaking your job function down into this two-column list is a sort of AI risk self-assessment. The more things in the algorithm column, the greater your risk. The more complex those things are, the longer you may have before it impacts you.
But remember, ultimately, we’re all going to end up in the same boat. We all need to be working on developing our humanness.
Let me know how your self-assessment turned out.