Gini Dietrich

The Hopes and Dreams (and Concerns) of Artificial Intelligence

By: Gini Dietrich | January 21, 2020 | 
0

The Hopes and Dreams (and Concerns) of Artificial IntelligenceWhat do Popchop, Fuzzable, After Pie, Stargoon, Hanger Dan, and Princess Pow all have in common?

They’re guinea pig names that an artificial intelligence bot came up with.

A couple of years ago a research scientist named Janelle Shane collaborated with a guinea pig shelter to teach a neural network— how to name guinea pigs.

And as Gizmodo quotes her:

The neural network really picked up on the spirit of guinea pig names.

Mostly. More on that later.

When we asked the Spin Sucks community what they thought the biggest trends this year were going to be, AI topped the list.

So today we’re going to look at how big it is predicted to be, what it could do for communicators, and what we may need to be concerned about. 

How Artificial Intelligence Will Affect Our Jobs

One of the most exciting things about the growing power and accessibility of artificial intelligence is that it can scale activities that are proven to be effective for business, but that are difficult to scale sustainably when done manually.

Things such as content personalization, market research, risk assessment, and customer communication take up huge portions of budgets—and AI is beginning to change that.

Artificial Intelligence by the Numbers

Really change it. It’s going to be big…and we need to be ready.

Last year’s Forbes Insights and Quantcast research, Lessons of 21st-Century Brands Modern Brands & AI Report, found marketers who used AI:

  • Increased sales by 52% 
  • Improved customer retention by 51% 

More than 50%!

Can you imagine if your sales increased by 50% next month? I would be ecstatic! 

Of course, I would also freak out because 50% growth in 30 days means something will fall off the rails—client service, ability to deliver on time, hiring, capacity…

OK, maybe 50% growth in 30 days, at least on the service side of the business, doesn’t sound so awesome after all. 

But the ability to grow that much because of AI is there, which means you can plan for explosive growth.

More and more companies are starting to look seriously at AI-assisted tools to increase their profitability.

SalesForce determined that while only 22% of marketers are using AI-based tools, 57% plan to start in the next two years.

This is probably a train you want to catch

Let’s look at how you can use some of the new tools that are being developed.

How You Can Use Artificial Intelligence

This can all still sound pretty theoretical—and that’s fair.

Most organizations aren’t leaning on AI yet to scale, save time, or increase productivity.

But, as I proved through the power of math towards the beginning of this article, that’s likely to change—and fast. 

Here are some of the ways AI could change the way you work in the coming years. 

Analytics Enhancement

As machine learning becomes more sophisticated, it will be able to make better predictions about what the behavior of online users mean in terms of conversions, lifetime customer value, digital reputation, and more.

I’ve been paying close attention to what the online therapy world is doing with IBM Watson and am very excited about the potential for our industry.

Imagine, on the agency side, that you can have your machine accurately predict how a client will interact with your team—and be able to assign your team that way.

And, on the organization side, imagine being able to accurately predict how long a customer might be with you—and how much they’ll spend over the lifetime of the relationship.

It’s all at our fingertips—and some of you may be working with it now.

Very, very exciting!

Augmented Customer Relationship Management

Nothing sets communications pros off like debating the merits of one CRM vs another.

People have capital F feelings about how to store, organize, and track customer data.

AI and those who create it know this, and are starting to augment traditional web-based CRMs with machine learning to help compile and analyze customer feedback and even predict behavior.

One of the things we’re doing right now is collecting data from our new business meetings and enrollment calls and storing it in our CRM.

We have almost a year’s worth of data—and nearly 300 people—that will allow us to use AI to determine characteristics of an ideal client (even beyond what we innately think they are), pain points they have that create a sale, and more. 

Customer Communications

We’ve talked about chatbots before, and while a lot of them are still pretty weak, and can be spotted as a robot a mile away, that’s already changing.

Also changing is how people feel about talking to robots.

Many prefer it to making a phone call or sending an email. 

One of my favorite AI stories to date is when Martin Waxman was working on his master’s degree thesis and he asked to interview me about AI and communications.

He asked me, “Do you have a relationship with robots?”

I scoffed at him—as if I’m in the movie Her and I’m having a romantic relationship with a robot.

But he asked me a few questions that turned me on my heels.

He said, “Do you trust Waze or your own brain more when you’re going somewhere new?”

Oh.

“Do you prefer chatting with someone on their website or calling the organization.”

Oh, again.

Maybe I do have a relationship with robots.

As you think about your own website and the interaction both customers and prospects can have, chatbots are an interesting way to go, especially because they keep getting smarter and smarter.

Risk Assessment

Last week we talked about red flags, and all of the work that has to go into digging them up, looking them over, and deciding how important they are.

What if an AI could do that—or some of it—and not just for potential clients, but for new product ideas, new hires, or whole new business areas?

It would be like having a crystal ball.

One that every other professional would also have, of course, but way cool!

It’s all great so far, isn’t it?

There are, of course, some concerns and downsides, too.

Potential Concerns About Artificial Intelligence

We could all end up being ruled by our robot overlords with batteries as brains and never needing to sleep or eat (or drink wine).

That sounds like a terrible life, but there also is value to never having to sleep.

Think how much more you could get done!

That may be taking things a little far.

Hopefully, we’ll stay in control of technology, but it is likely that a lot of jobs we currently do will be done by machines in the future.

We can stop that from happening, of course, but why would we?

Artificial intelligence can be incredibly helpful and will never be quite as creative, or friendly, or empathetic as WE are.

And it can improve everyone’s quality of life rather than put it at risk.  

Getting there is going to be a challenge all on it’s own of course, and we absolutely need to be concerned with how it’s developing, who is developing it, and what we all understand about the process. 

Let’s look at some of the concerns.

Data Bias

Data bias is when an AI gets too much of one kind of data and not enough of another kind.

This is generally not done on purpose but results in some significant problems.

Artificial intelligence may be “intelligent” but it’s still a computer program that can only operate based on the information that humans provide it with.

If the people who are developing the technology provide one-sided, skewed, or prejudiced data, that is how the AI will develop and perform. 

If you watched The Good Wife while it was on the air, you’ll remember an episode that shone a light on this.

ChumHum, a search engine company, was sued for racial profiling.

In the episode, ChumHum has a new maps feature and corresponding app that warns users if a particular business is in a problematic or dangerous neighborhood.

When the restaurant in question is visited, they find that the neighborhood, though marked as dangerous, isn’t unsafe at all.

It’s just largely populated by people of color. 

This is not good—and it’s indicative of what can happen with artificial intelligence when humans have bias.

And, of course, we all have bias so it’s one massive downside of using robots.

Transparency

One of the biggest struggles communicators are going to face as AI becomes more and more popular is transparency.

When do you tell someone they’re talking to a computer?

What kind of information do you need to share about how their data is being collected and used by one?

There aren’t clear answers to these questions yet, but as Martin Waxman points out in his article last year, when Google made a voice AI so good people didn’t realize they were talking to a computer program, they were criticized pretty heavily for it.

This is something we need to develop standards and practices for—and we need to start now.

As in all good communications, transparency is key.

Err on the side of communicating the robots are helping you, and you’ll always come out ahead.

Transparency, transparency, transparency.

Misinformation

This is the big pink elephant in the room, isn’t it?

What information is real, how do we determine if it’s real and why on earth won’t Facebook ban outright lies?

It goes further than a misleading or even untrue article making the rounds of the crotchety corners of the web.

Deepfake technology allows for incredibly sophisticated and hard-to-spot image, audio, and even video fakes.

Customers, clients, and executives will ask you how their audiences are going to be able to trust that the information they provide is real.

You’ll need to have an answer. 

The first thing we can do is verify.

And then verify and verify again.

If you see a headline that either makes your blood boil or you agree vehemently with, verify it.

If a competitor or industry influencer shares something you aren’t sure is right, verify. 

Then we need to make sure that everything we create is on the up-and-up.

Nothing has changed when it comes to ethics, honesty, and transparency.

Spin Sucks exists for a reason—it’s a constant reminder of how to do the right thing, every time.

If you follow that mantra, every change that comes at us will be easy to navigate.

Your Artificial Intelligence Hopes and Concerns

What do you want robots to do in the future?

What are you afraid of robots doing in the future? 

The comments are yours.

Photo by Franck V. on Unsplash

About Gini Dietrich


Gini Dietrich is the founder, CEO, and author of Spin Sucks, host of the Spin Sucks podcast, and author of Spin Sucks (the book). She is the creator of the PESO Model and has crafted a certification for it in partnership with Syracuse University. She has run and grown an agency for the past 15 years. She is co-author of Marketing in the Round, co-host of Inside PR, and co-host of The Agency Leadership podcast.