Martin Waxman

How to Put AI in PR and Demonstrate the Value of Communicators

By: Martin Waxman | April 17, 2019 | 
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AI in PRAccording to a designer friend of mine, putting the AI in PR is easy.

You do it like this:

P AI R

OK, it might take a few minutes for that to sink in.

But it’s a good visual model of how to integrate public relations and artificial intelligence.

Now, if only I could think like that!

The reality is, communications professionals aren’t yet sure about our role in companies driven by artificial intelligence.

And we need to get a handle on that.

I think a good first step is gaining a basic understanding of what AI is and does.

Then we need to examine some the issues, and figure out how communications pros can add value.

Data Bias

Data bias and a lack of data diversity are among the biggest issues in AI.

It’s why Alexa and Google Assistant have trouble understanding questions in accented English.

Or why Amazon’s facial recognition software matched 28 members of Congress to the mug shots of felons.

We have to get this right, because facial recognition mistakes could change an innocent person’s life.

Of course, ethical communications are a big part of PR.

What About Transparency?

Google recently announced the public launch of its Google Duplex voice assistant, which can call restaurants and hair salons to book reservations or appointments.

And if you haven’t seen the demo, watch it.

Duplex sounds real—complete with the umms and uhhs we associate with humans.

Google’s AI was so good people didn’t realize they were talking to a machine, and the company was criticized for that—and rightly so.

Now Duplex identifies itself as a digital assistant.

They made it more transparent.

And transparency in communications falls under the purview of PR.

Are You in a Relationship with a Machine?

Three of the factors that help engender trust in a relationship are speed, consistency, and accuracy.

And machines have two of those down, and are getting better at the third (accuracy), because of the data we willingly provide.

Your chatbot texts back with an answer right away—your BFF, not so much.

As machines start to look and sound more like us and give us the answers we need, we could start to trust bots more than people.

Just think about it, if a passenger in your car contradicts your Google map directions, who do you believe?

Now, do we teach children to be polite to machines?

And if so, are we bringing up a generation that can’t tell the difference between a human and a smart blender?

I’ve just completed some research on human AI agent relationships and how they might affect communications nad trust.

And, one of my findings was that virtually all participants thought people should be polite to AI agents.

Because that’s part of our humanity—who we are, and how we relate to people.

Managing relationships—again, that sounds a lot like PR.

Informed, Misinformed, or Disinformed?

Then, there’s the matter of media credibility and authenticity.

Can we believe the things we read and see?

False news or disinformation shared on social media has shown us how difficult that can be.

And now we have DeepFake videos, where a person’s face and voice could be made to do or say whatever we want.

Or OpenAI’s new GPT-2 natural language processing system.

Give it a prompt, and it can turn out pretty decent story or article because it can predict what word or phrases should come next.

You can see how, in the wrong hands, it could automate the creation of fake news.

Because of that, OpenAI did not release its full model.

And, even if it’s used for good, it could take away even more jobs from journalists and communications professionals.

Your Boss, the Bot

Which brings us to the matter of work and all the disruption we’ll face when machines replace humans on a wide scale.

Even with all the studies, there’s no real consistency with how bad—or how positive—the upheaval will be.

But right now, IBM Watson’s HR app can predict with 95% accuracy when someone’s thinking of leaving their job.

Paul Daugherty and James Wilson are two Accenture consultants.

They fall on the optimistic side of the perspective, and envision a kind of human/machine collaboration.

People will be responsible for training machines in empathy, communicating how AI decisions are made, ensuring data quality and security, and ethical behavior.

Yet, if you work in a job made up of repetitive tasks, including factory workers, taxi and truck drivers, accountants, human resources, stock brokers, financial advisors, legal researchers, radiologists, and marketers and communicators, you’re at risk of being replaced for no reason other than machines are cheaper and more efficient.

How do we communicate that, and develop and deliver employee training programs in an empathetic, people-centric way?

Another job for PR?

The Times They Are a Changing—Again!

In many ways, the speed and scope of the changes are like the early days of social media; a combination of excitement, enthusiasm, and trepidation.

However, Christopher Penn observed there’s a deeper knowledge gap between what marketers and communicators know about digital media and need to know about machine learning technology.

And that, coupled with our fear of mathematics could pose a barrier to adoption.

I believe there are many opportunities for communicators to take a leadership role in the wider enterprise adoption of AI, and demonstrate our relevance and value.

Four Strategic Recommendations

Here are four places to start:

  1. The AI knowledge gap is an opportunity to break down barriers between academia and the industry, and spark a dialogue and partnership. Researchers could produce new theories around the effects of AI on communications, relationships, and trust. And industry could test these in a real-world setting. For instance, the government of Finland realized they didn’t have the resources to conduct breakthrough AI research. So they partnered with industry and educational institutions to create a free online course designed to help its workers become best in class AI implementers. That implementer role fits well with PR.
  2. And speaking of training, we need to reimagine the public relations curriculum and integrate data science, fundamentals of coding, and statistical analysis into marketing and communications programs.
  3. Right now, we can lead an organization-wide AI audit that identifies potential issues, opportunities, gaps, and challenges, and positions the communications team as a strategic integrator. Senior communicators can start the conversation by meeting with the heads of all the other departments. We could ask tough questions around how they’re currently using AI, which jobs could benefit from automation, how that might affect the workforce, and what new skills and resources are required. We should also consider how to cultivate new relationships, and maintain the ones we have. And we must proactively discuss data privacy and the ethical use of AI.
  4. Finally, we need to redefine our roles, whether as explainers of AI, writers of conversational interactions, chief ethics and privacy officers, and guardians on an organization’s reputation and culture. All of these are strategic roles. This is especially important amid the coming job upheaval, and underscores the importance of training.

The AI in PR Challenge

Unless we gain an understanding of AI, and the opportunities, risks and challenges, we won’t be prepared for the next onslaught of change.

That’s why we can’t remain complacent about the adoption of AI in PR, but must work diligently to reshape, retrain, and reinvigorate the industry.

We must be curious, not shy away from statistical analyses, and consider the consequences of our decisions on AI—both good and bad.

Do you use AI in your organization? What role does communications play in its implementation? Please share your thoughts in the comments.

Photo by Jan Antonin Kolar on Unsplash

About Martin Waxman


Martin Waxman, MCM, APR, is CMO of Spin Sucks and runs a consultancy, Martin Waxman Communications. He leads digital and social media training workshops, conducts AI research, and is a Lynda.com and LinkedIn Learning author, and one of the hosts of the Inside PR podcast. Martin teaches social media at McMaster University, UToronto SCS and Seneca College and regularly speaks at conferences and events across North America. Find him on Twitter @martinwaxman.