For some time, I’ve been looking for one “source” that curates modern takes on HR Tech, perspectives from the people who build it, and its impact on enterprise — something that’s tailor-made by professionals for decision-makers.
I never found it — so I decided to build it.
Every week, I’ll be sharing fresh insights on tech platforms, design, data, and the future of work — straight to your inbox.
This week, we’re joined by guest author Hervé Mathelier.
My name is Hervé Mathelier. I’ve been a consultant with SEI for almost two years, and I am based in Phoenix, where I live with my wife and two children.
My main focus as a consultant at SEI is change management: helping organizations feel empowered and confident in taking on the new. No matter what’s changing, the reason for change is always the same: something better has arrived. Whether that’s a tool, workflow, software, or succession — change is spurred on by growth and opportunity.
It seems natural, then, that my other focus and personal interest is artificial intelligence. As we come to rely more on data to drive business decisions, the need for automation is growing quickly and exponentially. Many organizations see the writing on the walls. They are leveraging change management to implement new AI initiatives that can help their teams be more efficient and engaged by shifting their focus away from repetitive or arduous tasks.
At the same time, the discussion surrounding artificial intelligence is growing increasingly charged. I am, of course, referring in part to the recent sentient AI scare at Google, but the fascination and concern date back much farther than we’re probably even aware. From the 1983 movie War Games and Stanley Kubrick’s HAL from 2001: A Space Odyssey to the ominous allure of Silicon Valley in Devs and the love story of a man and his sentient AI assistant in the 2013 film Her, the battle of man versus machine has always intrigued and terrified us.
However, in the modern data economy, approaching artificial intelligence with an “us versus them” mentality, even subconsciously, will hold back an organization’s digital transformation goals.
So, when Patrick approached me with a chance to be a guest author for Exit Interview, I knew right away that I wanted to use this as an opportunity to prime readers for one of the biggest changes of our time: the rise of modern AI. I hope that in this newsletter, I’ll be able to offer an overview of what AI truly is, what our responsibilities are, and how we can embrace its advantages rather than fear them.
Artificial Intelligence: The Post-Y2K View
First of all, let’s dispel the basic concerns of AI. In my opinion, not even total sentience could create artificial intelligence capable of operating in — let alone improving — society completely free of human intervention. Why is that? In the scientific community, it boils down to three primary points.
- AI takes very few creative liberties. The code on which we build artificial intelligence is like a train: it can only go where we’ve built tracks. Even AI tools that can write entire articles require a very specific set of parameters to do so. It can’t save the day in classic Don Draper fashion by thinking outside the box — it isn’t even aware of the box. So unless we program them to do it, most computers will not figure out how to destroy us.
- People prefer people. As a collectivist species, we’ll almost always prefer communicating with another person over a cold, metal box in a business meeting and certainly in our everyday lives.
- AI lacks basic emotional intelligence. To say that someone is “acting like a robot” is never a compliment. Computers are less than proficient at interpreting human emotion — although I will concede that they are better at it than ever before, thanks to a young field of research known as Emotion AI or Affective Computing.
So if AI can’t save us from the 9-5 grind, why even bother? Why not cut our losses, burn the machines, and get on with our lives?
On a philosophical level, I think we persist for the very same reason artificial intelligence falters: a drive to create. On a more relatable level, though, we understand that while AI isn’t the answer to everything, it can and does provide us with solutions we can use to make smarter decisions.
Artificial Intelligence in Today’s World
A perfect example of AI turning ordinary people into pseudo-experts is Acorns, an investing app that rose to power after Robinhood’s crash landing following the GameStop stock surge. Acorns is a micro-investing app that uses artificial intelligence to help people invest. The best part? You don’t have to know a thing about investing; users can rely on the app’s machine learning tools to offer personalized finance management tips and create a diversified portfolio based on their preferences.
Micro investing with AI is a relatively low-stakes implementation of human-assisted AI, in which the human-machine working relationship is confined to a limited scope. But when the requests get more complex, the questions grow more open-ended, and the scale becomes more gray than black and white. It’s here that leveraging emotional intelligence becomes vital to operating in a useful and safe way.
Artificial Meets Emotional Intelligence
As I mentioned, AI possesses none of the core competencies of emotional intelligence: self-awareness, self-management, social awareness, and relationship management. Without key attributes like empathy and motivation, computers would perform rather poorly in a sales pitch or performance evaluation. But do you know what computers excel in? Math — something that a fair amount of the population and I despise, struggle with, or both. Machines also don’t struggle to stay focused on repetitive tasks — nor do they become overwhelmed by massive quantities of data.
When people and computers work together in a way that complements their respective strengths, it’s most formally referred to as augmented intelligence — although you may also see it called human-assisted AI. This lesser-known field of AI focuses just as much on human learning as machine learning. Its goal is to reduce risk of bias while engaging people by involving them more purposefully in the workflow, providing learning opportunities, and empowering them to act autonomously. It’s less of a power struggle and more of an elegant dance. Or, as The Washington Post so plainly put it: robots need babysitters, too.
If you’re interested in diving deep into augmented intelligence, this piece from SmartKarrot is one I’ve found myself recommending since coming across it earlier this year. I hope you’ve enjoyed this look into the state of AI in 2022! It’s been an absolute pleasure.
We’ve just covered quite a bit of dense, somewhat philosophical content. So rather than suggesting even more reading, I want to share a fun and simple AI tool. The open-source machine learning platform and 2022 unicorn startup Hugging Face rocketed into pop culture several weeks ago when a creator launched Dall-E Mini. This AI image generation tool creates a set of images based on your text input, and the results are equal parts funny, absurd, and terrifying. Let your imagination run wild and enjoy a midday laugh on me.
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