In-Ear Insights: Will AI Make Us Lazy and Stupid? - Trust Insights Marketing Analytics Consulting

In this week’s In-Ear Insights, Katie and Chris discuss a thought-provoking question raised during a recent talk: Will AI Make Us Lazy and Stupid? Is there a genuine risk with the use of AI? Will it make us lazy and reduce the quality of our work? We explore the impact of AI on human behavior and the potential consequences of over-reliance on automated systems. We delve into examples where AI can both improve and diminish service experiences, and the importance of strategic decision-making when implementing AI. Join us as we examine the complex relationship between humans and technology in the realm of AI. Watch the video to gain insights into the risks and considerations surrounding AI adoption in various contexts.

[podcastsponsor]

Watch the video here:

In-Ear Insights: Will AI Make Us Lazy and Stupid?

Watch this video on YouTube

Can’t see anything? Watch it on YouTube here.

Listen to the audio here:

Download the MP3 audio here.

Machine-Generated Transcript

What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher Penn 0:00

In this week’s In-Ear Insights, let’s talk about people for a bit.

We’ve been talking about a lot of process, and certainly a lot of technology recently with things around artificial intelligence and all these crazy cool things it does.

But at a talk I was doing last week, one of the attendees asked, is there genuine risk with the use of AI? That it’s going to make us lazy and stupid and reduce the quality of work that we do as human beings? And will it basically make us as bad as untrained people? Because we’re going to be over reliant on the system.

So Katie, are we on a path to lazy and stupid?

Katie Robbert 0:43

I mean, here’s, here’s the thing, there is no path people are already lazy and stupid.

And the second they find even more excuses to be lazy and stupid.

They’re all over it.

And so there’s, you know, it’s the whole, there’s two kinds of people.

And I feel like artificial intelligence is not a new, it’s not solving a new problem, it’s just a new technology, you’re always going to have people who are looking for shortcuts, people who are looking for the easy way to do things, people who can do the least amount of work.

And so artificial intelligence is now just a new version of that.

And so if you have team members who are already prone to working that way, that’s it.

I mean, that’s just going to be a problem.

Humans, by nature, you know, if we don’t want to do something, we’re not going to do something, and we’ll try to find something or someone to do it for us.

You know, whether it’s we just don’t want to, we don’t have the time, we don’t have the resources, whatever the thing is, there’s always someone else willing to do it.

And that’s the case with artificial intelligence.

So in a long winded way, Chris, to answer your question, it is a real risk, because it already exists.

You know, we take automation for granted, we take other, you know, services and tools and things that do stuff for us for granted.

We’re just like, Oh, it’s just gonna do it anyway.

So I don’t even have to think about it.

I don’t have to program it, I don’t have to maintain it, it does the thing for me.

Very simple example, you know, think about a coffeemaker, so it makes your coffee for you.

But you still have to clean the machine, you have to set up the machine, you have to set the machine.

And if you don’t take care of the machine, the machine will stop making coffee for you.

But you’re like, oh, no, it just does the thing.

And then you get frustrated.

And it’s you know, you can sit you treat it like it’s disposable, like one just gonna throw it out and get a new one.

Because you are too lazy to maintain the thing that you have and actually do the work.

So yeah, I think that we already there as a society as a culture.

As professionals, we’re already lazy and stupid.

Christopher Penn 3:02

Well, that doesn’t sort of bode well for.

Katie Robbert 3:06

I didn’t say it was good news.

Christopher Penn 3:08

I know.

It’s I know, it’s not good news.

But this is something there’s a an interesting piece in the the Associated Press the other day about the ease of now doing deep fakes and voice cloning and stuff means that, again, because people are inherently less likely to do work, that they don’t want to do things like fact checking, I’ve pretty much gone out the window.

If you hear if I voice cloned you, for example, Kate and I decided to roll out in this podcast, are you saying Oh, and our next, our next strategic focus will be burning down Microsoft’s campus, right, it would sound like you it’s clearly not something you would ever say.

But absent automated ways to check for that, there’s no way to to validate that, in fact, that was not you saying such a thing.

There was an example.

And they’ve been examples, I did an example, with a group of friends.

You can make very credible, sort of how just seems like hostage calls, right? It’s someone you know, saying, you know, help.

I’ve been taken hostage, please send money to x account, and they’ll let me go with people’s voices.

And, again, if you don’t have the technology to check for that, to validate that it’s real or not, you could end up being fooled by it.

So that’s, I would call it’s late that in those cases, lazy and stupid, that’s more not having access to tools that would allow you to validate something, but these are all considerations with AI.

In the context of this previous conversation.

It was about service providers, so does the use of that tool.

Create worse service experiences.

If a company is employing people who use AI rampantly for everything? Does that does To diminish the service that people that people give,

Katie Robbert 5:04

it doesn’t have to, it’s going to, but it doesn’t have to.

And I think it’s going to be really easy to blame the technology for the dip in, you know, the quality of service, the quality of work, because they, you know, the technology can’t fight back and be like, Hey, I’m only doing what you told me to do.

But that’s exactly what’s going to happen.

And so if you think about, you know, we’ve had conversations about, you know, the risks with large learning models is people humans are training them, and they’re introducing their own personal biases into these things.

It’s the exact same with introducing, you know, artificial intelligence to, you know, handle customer service, to write content to do whatever the thing is, we only have ourselves to blame as humans, if it doesn’t work out the way we want it to work out, because we’re the ones responsible for training it.

And so if an organization sees generative AI as a solution to their, you know, writing staff problem, okay, maybe it’s like 50% of the way of the solution, but it’s not the full solution.

But what will end up happening is, they’ll be like, great, we’re just going to have ChatGPT, crank out 100 blog posts, we don’t need to hire writers, and then the quality is going to go down, their SEO is going to suffer, they’re going to lose audience, you know, so and so forth, ripple effect, and they’re gonna blame the technology, not the fact that they themselves failed to put proper guardrails around the technology.

Christopher Penn 6:30

I guess my question, though, is if you have machines at a mediocre level, right, they can they can create mediocre content, but 40% of your staff is at at underperforming level or not competent level, by the use of that those machines, either with people or without people, doesn’t that solve that problem? Get you at least to mediocre? So sort of it sort of the rising tide lifts at least the lowest boats? Doesn’t that improve the general quality of of the service you’re

Katie Robbert 7:01

delivering? Not if you have the underperformers programming machines? Well, they wouldn’t be programming

Christopher Penn 7:07

they would just be using it as as line workers.

Katie Robbert 7:12

But I mean, and so there’s a lot of dependencies in this answer.

But you know, it depends on, you know, do they know what they’re doing? Or are they just doing the bare minimum with it? Are they using the technology to its full potential? Are they maintaining it in such a way that it’s learning and enhancing? Or are they just saying great, I don’t have to do my job anymore, this thing is going to do it for me.

And the end user, the customer is still very frustrated with the overall service they’re getting from this company.

And so I don’t think that’s an improvement at all, if the end user is still unhappy with the service they’re getting,

Christopher Penn 7:47

but they’d be less unhappy with it, because instead of 40% of the time being enraged, 40% of time, they just be dissatisfied.

Katie Robbert 7:56

Because you know what, that to me is not success.

That’s, I mean, you’re still failing

Christopher Penn 8:01

it, but it’s an improvement.

Katie Robbert 8:05

I feel like we’re splitting hairs because that like someone being you know, enraged, and moving up to dissatisfied, like they’re still unhappy with you, and they’re still gonna walk away from us.

And so unless you can get your, you know, subpar employees and mediocre technology, to actually turn it around and have satisfied customers, I don’t think it’s a win.

Okay?

Christopher Penn 8:32

This because this comes back to a situation that a friend of mine who works in a call center is having where it’s funny, she works a financial institution.

And her she is measured on call time.

Like that is the the outcome of her job is is she has a call center who no longer than five minutes every second over five minutes, she’s penalized for it to the point where it you know, she gets called into reviews, because their whole your call times are sometimes well over five minutes, because sometimes you can’t solve a problem in five minutes.

And this company has said, Yes, it’s nice that your customers are happy with you.

But you’re you’re on the phone too long.

And so we’re we’re probably gonna have to let you go.

This is a company where the their success metric is five minutes, their success metric is not a happy customer.

They don’t care about a happy customer.

They care about efficient workers.

In that case, if you swapped out that person for artificial intelligence that essentially was tuned to handle a problem in five minutes or less or didn’t matter because you didn’t have to pay them wages and health care.

You could have the calls go on for however long somebody wanted to as long as it was within a reasonable amount of time.

Isn’t that an improvement is that success from the company’s perspective, even though the customer like you said it’s the customer is still unhappy? But this is a company that clue does not care if the customer is happy or not.

Katie Robbert 9:56

I mean, it’s such a bullshit question because it’s the wrong success metric.

Christopher Penn 10:01

To us, because we’re a company that likes happy customers, but this is a company that does not like happy customers.

Katie Robbert 10:07

I mean, and and that’s that companies prerogative.

And so if they end so and that’s the thing.

So if you’re asking me, it’s not successful, if you’re asking whoever said, the metrics in that company, sure, that probably works, they can, you know, churn through as many unhappy customers as they want, they can lose as much money as they feel like, and get rid of people who are actually helping them retain happy customers.

Sure, if you want to call that success, that’s great.

Christopher Penn 10:33

And so in that case, going back to where we started with this, the use of artificial intelligence would help them achieve their their success goals.

And so in terms of diminishing the experience, the customer experience, it clearly will in this case, but this is a company and don’t think this company is alone in its kind of distorted view of the world.

That customer satisfaction doesn’t really matter.

It’s reducing labor costs and and hold specific windows, the service is what matters to them.

Katie Robbert 11:11

I mean, but if that’s the case, then why have customer support at all? Or why not just have the line go dead at the five minute mark, I mean, if they don’t care about happy customers, you don’t need to introduce artificial intelligence, because people off even more, I mean, that’s the thing that I don’t fully understand.

I mean, obviously, I have almost zero context for this information.

But thinking about it, you know, from an outsider, if your goal is to churn through as many customers and calls, you don’t need artificial intelligence for that, you’d would just, you know, have some sort of a, you know, predictive chat bot set up to answer some basic questions or, you know, point people to an FAQ page on your website and never give them contact information, which is probably the most frustrating thing to a consumer.

But you as the company that don’t have to hear from them.

Like there’s other ways to handle it without investing in really expensive technology, if your measure of success is not a happy customer.

Christopher Penn 12:09

And again, this is a this is a it’s a credit card company.

So they, I’m not sure why they have a customer service department the first place, but part of their part of their success metrics, too, is is keeping customers in as much debt as possible, and by not solving their problems.

Katie Robbert 12:28

So then again, why would you introduce? I know, we’re sort of going around in circles, but to me, this is the, you know, is artificial intelligence, the right technology? The answer in that case is no, if their goal is to keep people in debt and keep them unhappy, and keep them tied into a credit card that they forgot, they signed up for, when they were 19 years old, and never paid off, then don’t even have customer support.

Like just get rid of it altogether.

And problem solved.

Like that, to me is it’s ridiculous.

But if that’s the success measure, then don’t introduce new technology that could theoretically solves people’s problems.

Drew,

Christopher Penn 13:05

I can’t say I don’t know anyone in the leadership of this company.

So I can’t I don’t know what’s going on in their heads.

But in those in these cases, where your hat will you have called them strategic imperatives that don’t necessarily make a whole lot of sense to from a customer’s point of view.

Artificial Intelligence will be very appealing to to the leadership’s of these organizations, because they will see this way to dramatically cut costs, do and to replace as many humans as possible.

And I, I have to wonder if there’s an aspect of, you know, going back to the original question, if we see rampant use of AI, not only affecting people’s individual abilities, but affecting strategic decisions.

I think that’s I also think that’s more probable where we’re someone, the company we used to work for, was run by bean counters.

I’m sure that no offense if you’re an accountant listening to this, but they cared literally about nothing except net net margin.

And if they could reduce the workforce by 40%, I think they would have immediately

Katie Robbert 14:13

Well, think about this.

So when was the last time you opened a physical encyclopedia? A month ago.

Okay, so you’re an anomaly.

From the average person’s perspective, you know, a lot of us grew up that was the only way you could find out the answer to a question was to open was go to a library, find the right volume, look it up in the encyclopedia, figure out that didn’t answer your question and then go, you know, searching in a different volume.

And that would take some time.

Now that we have, you know, search engines and smart devices, we can just yell at the smart device.

You know, what’s the answer to this question? We don’t even have to Get up from where we’re sitting, to get the answer to a question that would have, you know, otherwise taken us, you know, a few hours to get.

And so does that make us more lazy? Or does that just make the information more efficient? And the answer is kind of both? You know, it depends on how you want your information.

And so to what you were saying, Chris, it has taken out our ability, or our desire to fact check.

And so in a way that does kind of make us lazy, because we’re just sort of taking whatever the first answer is, at the top of the search engine saying, okay, great.

That’s my answer.

I don’t need to look any further.

You know, when we think about things like, you know, what are the top 10 Best SEO practices, and then we, you know, put that into a search engine, people often just take whatever comes up first, because that’s the one that happens to be the best optimized for SEO ironically, but it doesn’t necessarily mean that it’s the correct one.

And so I think technology has a tendency to make us a little bit more lazy.

All of us, even those of us who enjoy working hard, what we need to do is figure out, Where are we okay with the technology taking on aspects of our lives, so that we can then focus on the things that we care about more.

So I was having this conversation, I don’t remember where I was having this conversation, but the conversation was, you know, if technology could sort of take over everything, what would I what would be left for me, and it’s like, great, I still want to be in my garden, physically, physically putting my hands in the dirt and feeling that and someone would come in like, well, you know, at some point, like robots can do that.

It was like, great, I still want to do that for myself.

And so we as humans, we as companies have to make those choices of strategically, what makes sense, what do we still want the humans to be responsible for.

And it should be things like customer service, it should be things like relationship management, it should be things like people management, it should be things like, you know, making decisions about the company, those are the things that we should still want to have humans in charge of.

But as we’ve talked about on past episodes, artificial intelligence is going to be able to do all of that for us.

So it’s more it comes down to a choice.

Christopher Penn 17:24

I will say, at least on the customer service side, as an advocate.

I think the nuance there is whether or not your service is already good.

Or if you’re if your customer service is good, then yeah, replacing it with a mediocre, automated solution is probably not the right choice.

Because it’s, it’s definitely you’d be it’d be a step down.

But if your customer service is appalling.

replacing it with mediocre would be a step up.

Katie Robbert 17:55

Yeah, well, and again, that comes down to there has to be some self awareness in terms of the company, there needs to be, you know, you need to know if you’re offering, you know, shitty customer service or not, or if you even care, if you already have stellar customer service, your customers are happy, your employees are happy to be helping customers, introducing artificial intelligence could be too much of a disruption.

Even if you feel like it’s gonna, you know, save money and be more efficient.

You know, that’s not a question of laziness.

That’s a question of, you know, strategic imperatives to your point, Chris, of, is this the right decision for us? You know, do we want to replace something that’s working so well, and people are happy with artificial intelligence? The answer is, I don’t know, you may want to start small, and maybe have it run in parallel.

But if you already have sort of a mediocre call center, and nobody’s happy, and you know, all the customers are unhappy, sure, introduce artificial intelligence, outsource a bunch of it, and people will still be unhappy.

It’s not going to change anything except maybe the, you know, bottom line of your profit and loss sheet.

Right?

Christopher Penn 19:10

Perhaps this is a different show entirely.

But how do you get leaders to think more holistically and more strategically, instead of saying, Well, this is gonna save us 14% on wages and benefits are 80% of our budget.

So if we can save 40% on that, we will be 40% more profitable.

And if you look back, for example, at the pandemic, almost every tech company, misread the room, dramatically over hired.

And then three years later, two years later was having to cut staff left and right, you know, 10,000 layoffs, 50,000 layoffs, the headlines are full of that this last 18 months.

And the only company that didn’t was apple.

Apple’s like yeah, we’re not hiring anybody at the beginning pandemic and then when they It came out on the outside.

Yeah, we don’t have to fire anybody because we didn’t we read the situation correctly, and took a more conservative strategy to just keep on with business as usual.

How do we how do you teach people to approach to think about AI more strategically? Because I think that’s the issue here is it’s not people are lazy.

And yes, people are lazy.

That’s, that’s nature.

It’s, how do we help people understand that AI is part of a strategy, that it may be a tiny part may be a big part.

But it has to factor into the big picture, because I don’t think people are seeing the big picture, I think they’re, they’re seeing the shiny object, right? And not what the object does.

Katie Robbert 20:43

I mean, that is a whole different show, because you’re talking about changing behaviors, changing people, getting them to see, I mean, it’s going to be different for everybody is going to be different for every company, because artificial intelligence isn’t a one size fits all solution.

For we’re going to use it differently from a company who is similar to us, but doesn’t do exactly the same thing, or have the same set of skills within their team members.

And so it’s, there’s a lot of work to be done up front of really understanding the business inside and out, and sort of what you want the goals to be and where there are deficiencies and where things are working well.

And so there’s, you know, there’s no one answer to that.

And I do think that that is probably a different conversation.

Because it also comes down to the personality of the decision makers have, you know, are they even open to hearing about the people? Or are they just looking at the bottom line, if they’re just looking at the bottom line, there’s no point in having the conversation because you’re not going to convince them otherwise.

Christopher Penn 21:50

So for managers who are concerned that their employees are going to become just sort of lazy drones with AI, what, what guidance you give those managers?

Katie Robbert 22:06

That might be okay.

If you have a bunch of C and D players, it might be okay for artificial intelligence to come in and take over some of their responsibilities, because one of two things will happen.

One is it will light a fire under the people who need that motivation or two, you will have the attrition that happens with bringing in that new technology to take over responsibilities.

And both are okay.

And so it, you, as a manager have to decide, can I take the risk of losing half my team to artificial intelligence? If the answer is yes, then go for it? If the answer is no, then you need to figure out why that is before introducing the technology.

Christopher Penn 22:53

What if the answer is I don’t know.

Katie Robbert 22:56

Then I think again, there’s more homework to do.

Artificial Intelligence isn’t a decision that you should be taking lightly in terms of replacing humans.

So if the answer is I don’t know, then you need to dig deeper is I don’t know, because you’re afraid of losing people? Is it because you’re worried about cost, then you need to start doing some proof of concepts instead, instead of going full in? So figure out like one task, one responsibility, one full time employee figure out what that looks like? And, you know, is it going to work?

Christopher Penn 23:32

What about on the on the customer side? So let’s say I’m a patient have a medical practice? Right? And I have I don’t know a resident that’s that’s treating it’s called it’s a it’s a teaching hospital? How should I be thinking about the use of AI? Because I can see a couple of different angles to this right.

On the one hand, you have the Oh, the, you know, people naturally will take the lazy route, the person will simply consult the machine and right or wrong, that’s, you know, the answers I get.

On the other hand, I think for folks who are going to say nuance more, there could be a well, this could provide a useful second opinion.

Right, but without you having to rope in a second human doctor, that could perhaps add something to the conversation.

How do we think about this as customers?

Katie Robbert 24:21

Well, you know, and I do think we’re going down a little bit of a rabbit hole.

But, you know, I, as I’ve mentioned, you know, numerous times I’ve done the clinical trial research, and one of the clinical trials we were running was, Are people more honest to a computer than then than they are to a human in a healthcare setting? And the answer was overwhelmingly Yes.

And so there are ways to introduce the technology, where it’s not taking away from that human interaction, but the computers can be gathering the information can be sort of putting together you know, It’s recommendations to give to the physical healthcare provider to say, this is what I got from, you know, your intake, or this is what I got from the assessment.

Let’s now talk about what this means for you as the patient.

So there’s ways to introduce it to make healthcare more efficient without taking away from that one on one experience.

Christopher Penn 25:19

That’s interesting.

I thought about it, he’s using as an intake mechanism, so that you get different answers than you would from as a nurse taking the same information.

Katie Robbert 25:30

You got to read my clinical trial research, Chris, this is what I did for a decade.

Literally that exact thing.

Christopher Penn 25:37

We have to put it up on the Trust Insights website, somewhere.

And maybe, perhaps maybe do an episode about AI in healthcare because I think there’s there’s, there’d be some interesting rattles to go down.

If you’ve got things that you’d like to share about concerns you have a deployment of AI, and how it’s going to affect you or your team or your customers.

And you want to talk about it pop on by our free slack.

Go to trust insights.ai/analytics For markers, where you have over 3000 other human marketers are asking and answering each other’s questions every single day.

We have not yet deployed an AI chatbot in there yet, but perhaps someday we will.

And wherever it is, you’re watching or listening to the show.

If there’s a place you’d rather have instead, go to a TrustInsights.ai AI slash T AI podcast where you can find the show on most major platforms.

Thanks for tuning in.

I will talk to you next time.

Need help with your marketing AI and analytics?