Real Impact of AI in the Workplace
- Job shifts. Impact of AI in the workplace demands upskilling and adaptive strategies.
- Artistic evolution. Impact of AI on creativity reshapes originality boundaries.
- Bias challenge. AI transparency is key to unmasking and addressing inherent biases.
I’ll confess that I’ve been guilty of some of what I’m about to say, but as a proponent of agile and continuous improvement in general, we should all strive to do better. As tempting as it is to talk about artificial intelligence either in awe of its rapid adoption and growth or in fear and contempt about its potential to destroy jobs, livelihoods, as well as our privacy, I believe that there are more real conversations we should be having. Having these conversations means getting to the real heart of the challenges and opportunities that AI in the workplace presents.
I realize that, reading this publication, you’re most likely in a marketing, customer experience, technology, or some other knowledge worker position, so you can look at this from the perspective of what McKinsey has estimated as 30% of your job being able to be automated by 2030. A question, though is would you miss that 30% if it were replaced by other, more rewarding work?
I don’t mean to sound callous here, but I rather want to focus our attention on some tangible things we can do.
In this article, I’m going to explore these topic areas and look at what I think are the real conversations we need to be having.
Let’s take a look at the impact of AI in the workplace, creativity and ethics.
The Impact of AI in the Workplace
There’s no pretending otherwise: AI is going to displace some roles, and completely upend some jobs as we know them. For instance, by 2026, Gartner predicts that 20% of repetitive processes in every industry (yes, every) will be automated by domain-specific generative AI implementation.
The Hype: AI Job Displacement Fears vs. Empowering Creatives
On its surface that’s scary to employees, and perhaps reason for excitement for some chief financial officers (CFOs) out there. But let’s take a step back and look a little more closely at the impact of AI in the workplace here.
AI might be taking jobs, but it’s democratizing types of work in ways never before possible. After all, generative AI is creating the opportunity to create content, imagery, videos, sound and combinations of all of the above — to which customer experience and marketing professionals can relate — to those who aren’t fortunate enough to have the access to years of experience and training on those tools. That type of democratization means that many people with great ideas but who (for many potential reasons) lack the technical skills can now share those ideas with others and the world.
Also, let’s talk about AI job displacement. While I don’t want to ignore the fact that for some who are struggling to make ends meet the threat of losing one’s current employment for even a day is catastrophic, let’s look in a few areas that show a different view of the types of jobs that AI will be taking.
Let’s take the threat of self-driving cars and trucks, for instance. While there are over 3.5 million truck drivers in the US in 2022, there are also consistently nearly 250,000 open positions each year, and this is projected for the next decade. Or, how about the fast food industry, which is also becoming more automated, with nearly 750,000 projected job openings (nearly 20% of the total potential jobs in the industry), or cashiers with over 550,000 projected job openings, and many more?
The Real Issue: Anxiety Over Upskilling
The real issue is anxiety about upskilling and reskilling our workforces while we curb anxiety about the impact of AI in the workplace. There is some genuine evolution that needs to happen here, but in the meantime, employers, educational institutions and others need to get serious about retraining people with skillsets that may go obsolete to utilize new and upcoming technologies.
For the knowledge workers out there, this also means teaching humans to work better with AI, and to prioritize their efforts on the things that humans do best, such as their ability to be creative and strategize, something right in the marketer’s wheelhouse. This will keep people employed, allow AI to continue to innovate and companies to continue to become more efficient. That’s a win-win-win.
It’s also about embracing AI in the workplace and the democratization of new AI-augmented skills, new opportunities and new jobs that are now available to a more diverse workforce than ever before, and not dependent on a privileged few who have had the education and access to the education and training necessary to perform certain types of work.
Finally, it’s about filling in gaps with AI-based solutions where we simply can’t find enough people to do the work or where human insight, creativity, and strategy are simply better used in different roles. If there are permanently-open positions, then it’s not a matter of AI replacing a person’s job, but it’s a matter of AI filling a much needed role. For instance, AI can be a fine content-writing assistant and idea-starter for a marketing or customer experience team.
The issue with the impact of AI in the workplace is not that there isn’t an issue, but that we need to focus on the tangible solutions, most or all of which we can do something about today.
Related Article: Artificial Intelligence Replaces Nearly 4,000 US Jobs in May
Let’s Talk About Creativity
While I was a relatively early adopter of tools like Adobe Photoshop (yes, I used version 1.0 before there were layers and more than a single “undo” so I supposed I’ve dated myself), I remember the fear and the panic about “photoshopped” pictures being so pervasive that we wouldn’t be able to tell fiction from reality. Since then, we’ve been faced with more sophisticated efforts, deepfakes and the like. Parallel to that, I also remember the reluctance for the photography community to give up on film cameras. Or for writers to embrace “blogs” as a legitimate form of expression, as I’m sure many of you do as well.
On a long enough timescale, you can see how all of these things are simply part of an evolution of, yes, technology, but also of creativity.
The Hype: Is There Truly Original Art?
Pablo Picasso said it perhaps most succinctly when he stated that “Art is theft.” There is concern, of course, that the impact of AI on creativity, and in this case, generative AI in particular is killing creativity in marketing and customer experience circles by making it too easy to create images and writing, but you have to remember that there’s no such thing as truly original art.
It is true that the large language models that generative AI tools like ChatGPT or others are based off are trained on large databases of existing content and images; how, exactly, is that different from your own experience? You’ve likely been “trained” on images and writing from television, movies, museums, books, radio, podcasts and more. In some cases the data that you’ve been trained on may be exponentially more than an AI-based tool, but in many cases it may not be.
Also, we’re concerned about AI writing too much of our formerly original content, but have you ever used spellcheck, autocomplete, or even used a human editor? At what point do you cross the line between your original words being corrected and compromised? In other words is asking ChatGPT to “write me a 1,000 word article about AI” too much, but sending an article in need of heavy editing to a human editor OK?
You can say the same with visual content. When does a photograph cease to become original and instead overtaken by edits and other “fakery?” This is certainly not a new thing either, as airbrushing (which for those Gen Zers out there was an actual physical thing photo retouchers would use) was around before the “airbrush” was a tool in Photoshop. If we’re going to be real about the problem, we have to acknowledge that the line is blurry at best (gaussian blur set at 2.0 pixel radius, for some).
The Real Issue: More Diverse Ideas, Not Less
The real issue here is about the democratization of creative work and intellectual property. As I said in the last section on jobs, I only see benefit to the democratization of work, including the impact of AI in the workplace, in this case creative work. We need more, and more diverse ideas, not fewer. But with that democratization, we also need clearer guidelines on what is stealing an idea versus using it as inspiration. This is a real issue, and I don’t believe it has been solved in a meaningful way yet. To me, it’s the conversation we need to have more of, and create more guidance on.
The real issue here is also about the nature of where an original, creative set of ideas comes from. For the time being, that is a realm that humans occupy. It may not always be, but for the time being, I am in favor of enabling more humans to realize their creative potential, and if the impact of AI on creativity is a tool for that, let’s move forward, keeping in mind that we need some AI guardrails on intellectual property and ownership of work to protect the very creatives we are trying to empower.
Related Article: ChatGPT and Generative AI: Just Another Tool in the Creative Toolchest?
Let’s Talk About Ethics
Last, but certainly not least, let’s address ethics, bias, privacy and all the areas where AI can arguably do the most damage.
The Hype: AI’s Not the Only Biased One
There is bias in AI, but I hope I don’t need to tell you that there is bias here in the real world, too. Plenty of it. While some of this bias is blatant and easily identifiable, some can be pervasive and subtle. In cases like this, AI could be our worst enemy or one of the best potential opportunities to find and root out bias. Some of this depends on how we focus some of our efforts as a community and as businesses, to create tools to identify and eliminate bias, rather than looking the other way.
The Real Issue: Transparency Matters
The real issue here is transparency of both the way that decisions are being made (to expose potential bias), and the information being used to make those decisions (to expose potential data privacy issues). We’ve already seen in countless examples that while AI has “intelligence” in its acronym, it is most often anything but. AI is also becoming more pervasive, but that does not need to mean that it is increasingly opaque.
So let’s focus on AI transparency, and it might expose not only the bias in the technology, but the bias in ourselves, the creators of the technology. Acknowledging this and making innovation in AI transparency and identification of bias part of the innovation process in general can and will go a long way in addressing the real issue here.
Conclusion: Embracing Responsible AI in the Workplace
There is no denying that we should tread lightly rather than blindly embracing AI in all aspects of our work and think about the impact of AI in the workplace. As you can see, however, by digging a little deeper to talk about the real issues and addressing them with actions that we can utilize today, we can make real progress as the nature of work and our relationship with AI continues to evolve over the months and years to come.
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