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Comms In Question is a quarterly podcast from Curious Public, a strategic communications and narrative firm. Each episode examines a timely issue through a communications lens, bringing together diverse perspectives to challenge assumptions and clarify what it means for leaders and organizations. Expect thoughtful debate and practical takeaways you can use right away.
It deleted their entire email inbox. That's the kind of risk that every company is facing when an employee uses a technology that is unsanctioned
Shannon Currie:Welcome to Comms In Question by Curious Public, where we bring experts together to explore what's happening in communications right now and what it means for our teams and leaders. Today's episode is guest hosted by Canadian journalist and host of the Paken podcast, Steve Paken, with panelists Angela Adam of eStructure, Levan Avancour of Reimagine Labs, and our own Jordan Way. Enjoy the show.
Steve Paikin:Hi, everybody. I'm Steve Paikin. For nineteen years, I hosted a program on TVO called the agenda, and these days, I am keeping the conversation going on a new weekly show called The Pagan Podcast. Yes. I stayed up all night long to think of that name.
Steve Paikin:It's on YouTube and all those other social media platforms. Happy to be back as your guest host for this latest edition of Curious Public's Comms In Question, the first episode of the new year in fact, and we are kicking things off with a very topical issue, artificial intelligence and the data economy. We hear about it. We talk about it. We interact with it every day even if some of us don't even realize it.
Steve Paikin:Every email, every text we send, every search we make, every time we open up an app or take and store a picture, we are tapping into massive international data center infrastructure on an industrial scale. Just like factories changed the landscape during the industrial revolution, transmission lines, generating plants, data centers are changing the landscape in the data economy. And more and more of that compute power is reserved for AI, which love it or loathe it is here to stay. So now what? How will the changing data economy be different from the one that came before it?
Steve Paikin:And how will Canada's small to medium sized businesses that make up the majority of our economic activity protect themselves while propelling their growth? And how do they communicate differently in this new economy? We've got three guests on hand today who are going to get into this for you. So let's introduce Angela Adam, senior vice president of sales, marketing, and government affairs at eStructured Data Centers, the largest and fastest growing data center platform in Canada. She's on the front lines of the country's digital infrastructure build out, helping position Canada to compete in the AI and data economy.
Steve Paikin:Angela is also an advocate for building the policy and regulatory frameworks needed to secure support, sustainable, and sovereign digital growth. Angela, where do we find you today?
Angela Adam:Steve, thank you so much for having me. I am based out of Montreal.
Steve Paikin:You're based out of Montreal, but where are you hanging out right now?
Angela Adam:Right now, I'm hanging out in New York City as I am waiting for a fly flight back home.
Steve Paikin:Right. Indeed. Okay. Well, we wish you luck getting home. Thank you.
Steve Paikin:Lidane Abokor is a prominent voice at the intersection of artificial intelligence, social impact, and the future of work. Lidane is the founder and CEO of Reimagine Labs, where he helps organizations in the charitable sector use AI and data to strengthen their impact. He also cofounded a $250,000,000 impact fund supporting community led organizations across Canada and brings a strong perspective on how this growing data economy could reshape power, access, and opportunity. LeBen, it's great to have you here. Where do we find you today?
Liban Abokor:Hey, Steve. Great to be here. I'm in Scarborough. For anyone who's interested, it has the best food scene in all of Toronto, maybe the GTA, so I thought I'd give it a plug. Anyone wanna grab a try sometime, find me at Lawrence East.
Liban Abokor:Okay.
Steve Paikin:A great food scene, but but no rails. No LRT. No subway. Not for another ten years. We wish you well getting that going.
Steve Paikin:And he says nothing. He's gonna just give me the head nod, and on we go. Let's interview let's introduce rather one last guy here. Jordan Ray, principal and senior narrative lead at Curious Public, the hosting firm for today's discussion. Jordan works with leaders across the public and private sectors to understand how emerging technologies, especially AI, are reshaping audience behavior, reputational risk, and narrative control.
Steve Paikin:He's known for helping organizations turn complex technological shifts into clear communications strategies. Jordan, good to see you again. Where do we find you today?
Jordan Ray:Thanks, Steve. I'm excited to be here. I'm coming to you from Downtown Toronto, so hopefully, my bias won't show too much.
Steve Paikin:Downtown TO is a good place. Okay. Thanks to the three of you. I'm really looking forward to our conversation today, and we want to remind those of you who are watching this to please feel free to put some questions or comments in the chat forum. And throughout the course of today's event, I will sprinkle some of those questions or comments in for our guests to comment on as we go along.
Steve Paikin:Angela, I'm tempted to ask the first question as follows. Is it data or data? But I got a feeling you're gonna say it's either or or either or either, so let's go on from there. Put some flesh on the bone here. When we talk about the data or data economy, what are we talking about?
Angela Adam:Right. So I call it data economy, but either one works. First of all, I just wanna give thanks to Jordan and the Korea's public team for helping us actually go go through this narrative and formulate our opinion. So, of course, when we talk about the data economy, we mean the part of the economy that really depends on data being stored and moved and secured and and processed and now increasingly turn into intelligence. Right?
Angela Adam:So, yeah, that includes cloud. That includes digital services, the transactions that we all do, like a banking transactions, the content that we put out there that we consume, your TikTok, your Netflix, and all of the communications. So, but today, obviously, it also includes AI, which is raising the stakes dramatically because it required so much more compute, more power, more secure infrastructure, and last but not least, more deliberate policy choices. So for us, what matters is that the daily economy is not just a technology story. It's an economic story and an infrastructure story, just like you said before in the same manner that the past generations would build rails and and power grids and telecom networks.
Angela Adam:This generation is building the digital foundation that the modern businesses and public services now depend on. So that's why we use this term. It and I I really think it helps people understand that it's it's not niche. It's not really that new. It is the operating system, if you will, of this, kind of modern economy.
Angela Adam:Data economy is simply the real economy but in digital form.
Steve Paikin:That's a great scene, Senator, and a a place from which we can dive in deeper. Liebhens, so a lot of the things that were just mentioned there, be it social media or online banking, cloud storage, I mean, that kind of stuff has been around for a decade. Organizations are all over that. So what is it about the conversation that is particularly new these days, and what's the significance of it?
Liban Abokor:Yeah. I think Angela sent me pretty well. And so data's always been driving our economy decisions. That's not new. If we think about I before everyone joined, we talked about the weather.
Liban Abokor:So I'm I I feel like I wanna make a comment on the farmer's almanac built on centuries of weather pattern and observation, and that now helps us predict weather, farming decisions, and so much more in the agri tech space. You know, similarly, you know, you mentioned earlier in your opening comments just where we're seeing AI, whether, you know, in some case, my wife and I are trying to find a new show on Netflix, and I'm not enjoying the recommendations that are coming forward. So that's a pain point in my life. But the point is we're getting recommendations based on what millions of other viewers have watched like us in Scarborough, around our age group, and others. So in other words, data's always been used to drive economic, social, and political decisions.
Liban Abokor:But what's different now is really that they're no longer algorithmic in the way they once were. The things I described previously was a human made the rules, and the machine had to follow it rigidly. Really, really, like, simply put. It's kind of like a chef being given a recipe at a restaurant that you've gotta cook that same thing every single day. What we now have are chefs that are going into kitchens with a set of ingredients and deciding what to cook based on the hundreds of hours they've spent in their own kitchens or eating at restaurants.
Liban Abokor:In other words, there are now different capabilities that, this data can provide, for businesses, for governments, and others. And so maybe one quick example that I can provide you is that Reimagine Labs, we're now using massive data to help tackle big complex public policy questions such as not where do we put a health center or a food bank, but what who will actually use that food bank, when will they use that food bank, and why will they use that food bank, and how do we reduce their utilization of that service. In other words, we're not just giving people you know, telling them what to read or insights from 10 public policy reports, but almost anything public available, and they're able to synthesize that synthesize that in, like, really, really important ways on any subject really in matter of moments and seconds when that was taking months or years. To give one more example of that, in the health care space, how many of you are familiar with what happened with the AlphaFold, AlphaFold breakout the breakthrough? So Nope.
Liban Abokor:AlphaFold, did something very similar to what I'm describing at Reimagine Labs in the biology space. It was able to map the entire structure of over 200,000,000 proteins. Just to put that in perspective, they did that in one year. That used to take our entire research lab years to unfold one protein, and we've now mapped out 200,000,000 of them. The significance of this is now it's gonna provide breakthroughs in therapies, in medications, and so much more.
Liban Abokor:So what I'm really pointing to is the difference here isn't that data collection extraction utilization is new, but the way the scale and speed at which we're able to utilize that data and then the insights to be able to solve problems we probably thought were science fiction before is now a significant opportunity. You know? And what's also changing is how we care about our data, and this is to your point, Angela, where I think we're more mindful of who sees our data, where our data is stored, and what governs it. So I know a lot of discussion, especially on the recent election federally, talked about data sovereignty and having making sure that just like Angela, we bring our data right back here to Canada.
Steve Paikin:Okay. Since you're raised in, I'm doing a quick follow-up. You and your wife have been watching some TV. You got any shows you wanna recommend while we're here?
Liban Abokor:Well, I have a five month year old, so everything I'm about to recommend is probably gonna be child related. I think that might not be what the crowd wants to hear. But I have been watching a lot of cooking videos because I'm trying to figure out what kind of meals to make this newborn. So as soon as I figure those out, I'll share with you, Steven.
Steve Paikin:That's a that's a deal. And, of course, we're all coming to Scarborough to hang out with you anyway so you can show us your culinary skills at that time. Jordan, I it will not come as news to anybody watching this that we have a productivity problem in Canada. McKinsey tells us that compared to our American counterparts, Canadians have gone from being 90 as productive as Americans in the year 2010, 90%, to 75% as productive in 2025. That is an increasing delta that represents significant economic loss for us.
Steve Paikin:So I guess the obvious question is, is AI gonna make us more productive?
Jordan Ray:Yeah. Thanks, Steve. And I think the what Lieben was talking about shows how, in some ways, AI is already making us more productive. It's enabling us to tackle larger problems with larger quantities of data than we ever have before. I think the big question for people in terms of AI making you more productive is is how you're using it, and are you already good at what you do?
Jordan Ray:Because in my experience working with clients who are starting to dig into AI tools, if you're already an expert at what you do, AI will be just a huge exponential multiplier for what you're able to produce. But if you're coming in and relying on AI to be that lead and that expert, then you're gonna find yourself falling short. So the big question is, are you already good in your field? And do you know how to use the AI tools that are out there to enhance what you're already doing? And so the the knock on of that is that you you have to keep your own skills sharp.
Jordan Ray:Because if you don't, then you're gonna be replaced by someone who already knows what they're good at, and they're an expert. They're just good at doing it with AI.
Steve Paikin:Well, we know again, follow-up for you. We know you're good at what you do. Does AI make you better at what you do?
Jordan Ray:Yes. It does. So I would say we we really take a research driven process to a lot of our projects, and that often involves hours and hours of talking to people and getting transcripts. So when we go back to those projects, we could rewatch the tape as we would in the past, or now we can take all those transcripts, put them into a large language model, and say, okay. What are all of the themes about what we talked about?
Jordan Ray:And then, of course, we have a human to confirm, yes. That is something we talked about and, no. You just made that up. So it that has saved me hundreds of hours already, and and it really helps us in that way. It's also useful as a brainstorming tool.
Jordan Ray:You know, if you're having trouble figuring out where to start with something, what an AI tool may give you may not be what you end up with, but it can give you a really good starting point in terms of what's that communication strategy for this particular campaign. What should we put in this press release on this particular issue? You know, what should we have as the content calendar or the social media caption for these next few weeks? So so it is enhancing what we do, but only because we know how to use it.
Steve Paikin:Let me remind the people watching this that they are certainly welcome to share their stories in the chat feed about how artificial intelligence is making you more productive, and then we can get our guests to comment on that. Angela, how about you? Is it making you more productive?
Angela Adam:Well, I think it can. I resonate with everything Jordan said. I think it can. But from an organizational perspective, I'm thinking we need to go beyond just experimenting. A lot of organizations still experiment right now.
Angela Adam:So productivity doesn't really come from just handing out tools to people and just go nuts. It comes from, you know, the need to redesign the workflows, setting real governance, and training teams properly on the tools, and frankly, being clear about where AI where we think AI adds value versus where human judgment still matters. So, yeah, the the upside is very, very real. And but, again, productivity is not automatic. It has to be operationalized.
Angela Adam:And, you know, does it make me more productive? I say yes in very practical ways just like Jordan said to you know, research is faster. You get the summaries that you need fast. The first drafts, like Jordan said, but I think it does raise the premium on human judgment. Right?
Angela Adam:The faster these tools get and smarter, then the more important it is to have people who actually know what good good looks like. Right? But AI is not gonna tell you that.
Steve Paikin:Well, Lieben, you must be using AI to help you become the chef that you were destined to become. Right?
Liban Abokor:I I have used clutter chatty PT a time or two to find out the best avocado recipe. That is for sure. Even if I could piggyback, Steven, on something that Jordan said, you know, you you raised such a really important point in your earlier question around productivity. You know, the there's this you know, there's a data point that says that three out of four employees currently are using artificial intelligence in unsanctioned ways to boost the productivity in their own jobs. A part of that is so that they can end the day a little bit earlier so they can feed their kids like I want.
Liban Abokor:Right? And so there's tons of motivations as to why they're using this this new technology, Steve. But there's genuine concerns, and and if I could, I'd love to maybe remark on them.
Steve Paikin:Please? Well, may can you tell me what do you mean by unsanctioned ways? What does that mean?
Liban Abokor:So the there there is there's a report earlier that from IBM that says that 25% of employees are using tools that have not been supplied by their workplace. That means they're using, whether it's ChatGPT or Claude or one of these other tools, note taking app as they do their their work on company time using company data. And and while there's genuine enthusiasm about what these tools can do for productivity more broadly, some of which Jordan spoke to, whether it's, you know, drafting correspondence or building marketing material or even monitoring, like, operational expenditure, there's there's some dread that employers have been experiencing. And this is not hypothetical. These are really like, recently, we saw the explosion of this, new tool called, OpenClaw, if any of you have been sort of monitoring.
Liban Abokor:And there's this really interesting story where the director of AI, alignment at Meta used OpenClaw to be able to get their inbox under control. Here's a specific incident that happened. They said, I want you to look at my inbox, read, and help me understand what I should archive, what I should keep, or what I should delete. But I don't want you to do anything. I just want you to make that determination.
Liban Abokor:OpenCloud, of course, did all three of those things, but then went out and said, I'm the chef in that new kitchen. I don't follow the rules. Remember what I said earlier? I think what I actually need to do is to go ahead and just delete the things I think aren't important. And without cropped, it deleted their entire email inbox.
Liban Abokor:So, you know, here's an artificial intelligence tool that could potentially have helped you catch up with critical emails and boost productivity that now ended up literally wiping out your entire personal inbox. That's the kind of risk that every company is facing when an employee uses a technology that is unsanctioned. Why? Because we don't have the governance guardrails in place. You know, I I'm I'm looking at Angela and Jordan nodding and the micro expressions.
Liban Abokor:Tell me you wanna jump in on this. So maybe I'll conclude here, and I'll say, what I just noted was not a technology failure. Right? It was actually a governance gap. And what works what we're seeing around companies everywhere at the moment is they're trying to figure out how to make sure that they benefit from the productivity gains while also making sure they limit the liabilities, from their employees possibly pasting critical information on a board decision internal memo that is training a model that, they have no control over.
Liban Abokor:There's a lot of lot of risks on, that that that emerge from this. And how do we make sure we address that without blunting the productivity opportunities that Jordan so articulate so well articulated as the benefit?
Steve Paikin:Jordan, you wanna jump in on that?
Jordan Ray:Yeah. I'll just kind of building on what Liban was saying and what Angela was saying is that, you know, you can't just say, hey, employees. Go use these AI tools and become more productive. You have to set them up for success, and help them, you know, decide and learn how to use these tools within their existing workflows, and you may end up changing some of your workflows within the company to as a result of that. I wanna add as well that, you know, we're talking about the the personal adoption of AI tools, which is quite high, but the the business adoption of the tools is rather low.
Jordan Ray:And I think it's a bit of a uniquely Canadian problem. Canadian companies historically are a little bit slower to invest in r and d and things that aren't already proven, certainly slower than our American counterparts or even our UK counterparts. It brings to mind something Peter C. Newman wrote in the Canadian establishment. He said in in The US, it's fast money.
Jordan Ray:In The UK, it's it's quiet money. And in Canada, it's careful money. And we're just not able we're we're not ready to get in until it's working for someone else. So I think there's a call to action for companies to say, okay. These tools are out there.
Jordan Ray:Our employees are using them already. Let's put some processes and trainings in place so that they're actually using them in a cohesive, well realized way that's gonna be good for everyone.
Steve Paikin:Angela, where do you wanna take that?
Angela Adam:I I listen. I resonate with both Jordan and Levan. You asked risk and reward. Well, reward, we talked about it. Speed and its accuracy and ability to process so much data so fast.
Angela Adam:Risk remains unmanaged exposure, just like Levan said. You know? Employees adopting these tools faster than the leaders set the policy, well, then organization may be creating some risks around anything between confidentiality and, you know, security of our data and IP and reputational consistency without even realizing it. Like, how would we know? And the answer is obviously not to dissuade the employees from an organization from adopting AI because it's here to stay, but it is to create this very safe and approved and well governed, pathways to adoptions that people trust it and use it appropriately and productively.
Angela Adam:I don't think the risk is adoption. I think, we're generally quite enthusiastic about it, but, adopting it without governance is could be a major major issue.
Steve Paikin:K. Liban, can I just get you to follow-up on that in as much as and and, you know, give us some advice here in as in as much as should if it hasn't been sanctioned by, you know, the protocols department of whatever company you're working for, is it is it your position that people should not be using unsanctioned AI tools in the workplace?
Liban Abokor:No. Not at all. I I think I think unmanaged exposure is a threat, but we've found ways to mitigate this in a whole host of other areas when we're introducing a new tool technology or process. And so what does that mean? That means making sure that there is a responsible AI framework for your company.
Liban Abokor:In the midst in the absence of a internationally recognized AI strategy or governance framework, there's the EU's leading that work, The United States is leading that work. To Jordan's point, Canada is doing a bit of catch up. But one of the things that I feel really confident about in Canada is that under minister Solomon as well as under prime minister Kearney, they have committed at least to make this a priority. Right? And so I think what we will see as an emergence of more broader governance that we can follow around responsible utilization.
Liban Abokor:But at the individual company level, there are things like everyone should be rushing to create an acceptable use policy. So what tools are approved by IT? What for what tasks and with what data? And you need to be thinking a lot about data classification. For example, your everyone and your employees should know what can and cannot go into an AI tool because we all have to be very candid that we currently don't have any control about the data that we input into these models.
Liban Abokor:We don't own it. It does go on to train the tool. And then finally, there has to be an unquestionable requirement that a human in the loop has to be the final decision. Right? It's and that's the risk.
Liban Abokor:Right? When you want to make a decision quickly and you wanna get on to the next thousand items on your to do list, you probably want to outsource a bit of that decision fatigue, but you can't afford to make that decision. And the risks that I just pointed out was one made by someone with significant experience in AI at a leading technology company. Can you imagine what we're doing at mom and pop small and medium sized business across Canada? And so What do you do?
Liban Abokor:That's my recommendation.
Steve Paikin:Okay. Speaking of being in the advice giving business, I'm gonna put you to task one more time. What do you do when every single one of your emails has been inadvertently or accidentally erased by an AI program that you gave the responsibilities to you just described? What do you do? The cycle farticles?
Liban Abokor:Yeah. I I mean, the the truth is you cry a little bit, Then you quickly try to remember that you should have memorized everyone's emails like we used to remember if he was telephone numbers. But the truth is you apologize, and you evangelize the experience as best as you can so that everyone is aware that these are the real risks that we're facing. And we ensure that sometimes we use those lessons to deter other experiences because that was an email inbox. Now imagine if it was deleting leading research, and that has also happened.
Liban Abokor:There was a researcher at a university recently used OpenCLaw or was had been actually using, forgive me, one of the larger LLMs that might have been ChatGPT as a part of their research. And then somehow, they sought to import or export that information, and it all ended up getting deleted. So the I think the lessons are back up your information, be very clear about the task, and ensure that you're using a tool that's been approved. And as best as we can I don't even know if there's as best as we can? I think I think we should be very I think we should be very, very honest about understanding what the limitations of those tools are and not, as I said, advocating responsibility so much as we had.
Liban Abokor:So maybe the lesson is read your emails, folks.
Steve Paikin:Good advice. Okay. That's a good segue to get me back to Angela here because I wanna cite another study. This one's from KPMG, which finds that most Canadians they say eighty percent of Canadians. I'm actually surprised the number isn't higher, but they've got a study saying 80% of Canadians are concerned about the impact and consequences of artificial intelligence from data security, intellectual property theft, spread of misinformation, decline in human connection.
Steve Paikin:We are worried about these things. So, again, I'm putting all of you to task here as being in the advice giving business. How can organizations earn trust as they adapt to this new reality of all these things we're worried about?
Angela Adam:Yeah. Thanks for the question, Steve. And I'm I'm not surprised at the numbers. Listen. I think trust has to be built in from the start.
Angela Adam:We can't just add it later as a Comms exercise. Right? So then when organizations, like any one of our organization, is adapting to AI, that means be clear about, I would say, three or four things. What data is being used? Where is it being processed?
Angela Adam:What rules and safeguards are being put in place? And then where human accountability still sits. We talked about this. This is still very important. And maybe I should add a fifth a fifth point, which is so increasingly important in Canada, sovereignty.
Angela Adam:We touched on it. People want to know where their data lives and and who governs it and whose legal framework, you know, applies in one case or another. And those those I see those not being as abstract questions anymore. They go directly to the issue of trust. People are educated enough, and they want to know these answers.
Angela Adam:So for me, if you ask how organizations can earn trust, well, by pairing all this innovation and speed with discipline. Be transparent. Put governance in place. Continue to keep humans accountable. Right?
Angela Adam:You don't want your email database to be deleted. Somebody has to be accountable for that. Then make sure that the infrastructure underneath it because I come from the infrastructure world, and that's what I know and, like, talk about. Make sure that the infrastructure that's supporting your AI strategy is also trustworthy, and it's also reliable, and people understand that it has to be part of the strategy. And in this era, trust is not it's it's no longer a soft issue.
Angela Adam:Right? It has to be part of the AI stack, part of the infrastructure. I I can't see how it cannot be.
Steve Paikin:Jordan, you wanna add to that notion of building trust and how you achieve it?
Jordan Ray:Yeah. I think I think Angela has laid out really well kind of the the important criteria of, like, how you build that trust. One concrete tactic that that we use at Curious Public is we have an AI policy, and we have a clause in every contract with every client. Like, this is how we use AI, and we have the entire policy available upon request. So anyone who wants to see how we use it, we can immediately produce that and say, here are the rules that we follow.
Jordan Ray:So, you know, being proactive like that and showing to and and really what Angela had mentioned about have keeping humans at the center of the process and keeping AI in the human enhancement box instead of the human replacement box, I think, is really key to addressing people's anxieties.
Steve Paikin:Nice. Li Bin, coming back to you for this next one. Beyond the issues of trust and productivity, the data economy has, as we know, social and environmental impacts. And here is one little factoid I learned in getting ready for today. Generating just one AI image uses the same amount of energy as charging your phone.
Steve Paikin:Now multiply that, of course, by multiple billions every day, and, you know, you get a sense about what we're talking about here. So tell us about how you think organizations should be balancing adoption with their social or environmental commitments.
Liban Abokor:I I think that the social impact conversation about the impact of AI and what's happening in Canada have been has been underreported, frankly, particularly when it comes to the impact it's having on Canadian workers. It's it's a conversation that we need to be far more frank and honest about. I I I can share an encounter I had in Halifax a while ago that I that I always come back every time I get some kind of version of this question. I I met someone that I'm gonna call Penny the paralegal. She worked fifteen years in her job.
Liban Abokor:She was really good at it by all accounts, and her expertise is now being called out by a new tool that her firm is using. Now the truth is she's not gonna lose her job imminently, but what will happen is that this tool becomes so good at replacing what Penny can do is that when she retires in a couple of years, that firm will not replace her. They will simply have now figured out a way to utilize that tool. And this isn't a, a make believe. In fact, we have Canadian companies that we should be applauding for their ingenuity, like Bluejay Legal that are that are gonna be, doing this kind of work in the legal the legal research space.
Liban Abokor:And so the point I'm making there is, once she eventually retires, her position won't be posted, and the job will quietly disappear. And why is that important? Because if we look at recent stats can data, we just saw us as a country lose almost a 100,000 jobs this past February. And while that is stunning and actually higher than our expected predictions, what those numbers didn't capture was the full picture, which includes the number of young Canadians who were finishing school and simply can't find entry level work. And as I mentioned, it doesn't speak to the jobs that we're gonna lose as a part of attrition.
Liban Abokor:So why am I bringing that up? Because the the pennies of the world are the new reality. Right? This technology by boosting productivity will certainly and naturally reduce our labor cost needs. And so as a country in, like, Canada, as we come up with an AI strategy, we can't only have it focused on innovation and adoption and productivity.
Liban Abokor:We need to actually make sure it contains a real and comprehensive discussion and consideration on the import and the input and the impact it's gonna have on workforce development. And that seems to be a central strategy. And the reason for this is it's not just a social impact. It's economic, impact as well. For every penny we lose and for every young person we don't employ, that means that we're not gonna be able to generate income for them that we use as a basis for our revenue.
Liban Abokor:And that income of the hundreds of thousands of workers I just talked about and millions to come is what our tax base relies on. Right? Our hospitals, our schools, our social services. So, again, when we talk about productivity gains, we're also needing to talk and talk about, like, the value that we are seeing accrued in organizations and shareholders. We all seem to talk about job losses.
Liban Abokor:We need to talk about the revenue base that pays for the services we all depend on, and that is the foundation of the fabric of Canada. And that's why I'm hoping that, we see these issues of gay productivity gains and workforce destabilization as two sides of the same coin, and the social implications it has downstream are, I think, have been pretty well documented from food insecurity, homelessness, mental health, you know, drug addiction, violence, crime, and more importantly, the various destabilization of our democracy.
Steve Paikin:And I do fast follow-up with you there, Lee Ben. The Penny the paralegal, they are I just wanna confirm this detail. They are allowing her to finish her career over the next couple of years even though they really don't need her services right now because they are already replaceable by AI. Is that right?
Liban Abokor:Steve, that's exactly right. I mean, for those of us who are interested, and and I know that I know that through the course of this conversation, we've all kind of referenced some research. I'm happy to share it with the audience in the mail out later if there is one. But MIT actually released a report, earlier, I think late in 2025, that showed that in The United States I'm referencing The US research because we don't have anything comparable here, but is there is a correlation. That 12% of existing jobs in The US right now could be replaced by AI.
Liban Abokor:The challenge is we don't have the social, political, or maybe economic license to do this just yet. Right? Because the question is where are we gonna what are we gonna do with 30,000,000 unemployed people all at once? Right? What can bear the stress of that supporting that population?
Liban Abokor:And so as the as the social political license for mass structure unemployment or deemployment occurs, I think that there is to your point around the same around the comments I made earlier, we don't have the policies to catch up with our utilization of these technologies in the job force. I think we're trying to think about what is the implications on the broader society. And so but it's not a foregone it's not something in the in the far distance. We just saw Block, commit that they're gonna be reducing their their, employee base by nearly 50%. Block being, the recent company by the former founder of Twitter, right, who just let go half their employee base.
Liban Abokor:Why? Because technology can resolve it. We're seeing that Meta and Facebook and IBM are reducing their per their hiring of, of folks in the, development space as, and the same thing that we told everyone to go learn to code. Now AI is coding, and I don't need these engineers for that same purpose. So it's it's a real issue, and so I think it's one that we should be concerned about, and I hope Canada's AI strategy that should be coming out eminently addresses that.
Steve Paikin:Angela, let me get you on that. How far along the continuum do you think we are in terms of understanding what our social responsibility ought to be to people whose jobs are about to disappear? You're on mute. There we go.
Angela Adam:Steve, I don't know that we have a full understanding right now. I think we're going through the motions. I I I believe that AI changes tasks much faster than it changes human value. So I I I don't know that, we're going to see a type of kind of redundancy as fast as we are fearing right now. We will go through the motions.
Angela Adam:We will upscale. We will develop, new areas of business, you know, areas of interest, and we'll adapt. People always have.
Steve Paikin:Jordan, I mean, is a fact that we have to adapt or die as the expression goes. And do you but, of course, everybody says this time it's different. This is not going to be like the previous ages that we have lived through. This one could be cataclysmic in terms of the impact that it has on society. Have we really thought through the implications of massive unemployment because AI is going to take over so many of the jobs that we have depended on doing ourselves?
Jordan Ray:Yeah. It's it's a really good question. And I think, to Angela's point, we're kind of if you think about think thinking about the analogy of social media, and, you know, Facebook kinda came on the scene in late two thousand and four and then reached kinda widespread adoption around 2007. And now, of course, looking back enter at social media, we have many other thoughts about where it was taking us, where it is leading led us today, and we're still very much at the base of that mountain for AI. We we don't really know where it's going to end up.
Jordan Ray:I think that there are some some noticeable trends that I've seen in terms of just where people are spending their time. Because at the same time that you have this incredible technology on the rise, you have this post pandemic sort of swing back towards a desire for in person connection and a desire to go back to concerts and to see people in person. And and in some ways, try to spend less time on our devices and our computers and go back to being in a place where you can talk to someone face to face because you don't know when you see that piece of information on TikTok if it's real and generated by you know, in the case of news, by a respected, trusted journalist or if it's misinformation. But if you can go to somewhere in person and see someone give a speech, whether it's a political rally or some kind of panel on current events like this one, then you get more of a sense of, okay. Like, this is this is real, and I have more trust in that.
Jordan Ray:So it's it's a really it's a really difficult Gordian nod to untangle, I think.
Steve Paikin:But let me make it tougher on you. I'm gonna ask a follow-up here and see if we can make it even more complicated. I'd like to think, but I'm probably wrong about this, but I'd like to think that the business I'm in is one of these businesses that is certainly not immune to being replaced by AI. But, you know, given the way you just put this, you'd like to think that people still are gonna want somebody sort of trusted with experience in front of a camera to kind of explain the day's events to people as they tune in. What about for marketing and communications?
Steve Paikin:We know right now that that artificial intelligence can summarize and can advise in a way, you know, that was unimaginable even a decade ago. What does the future look like for market you know, marketing and communications professionals as we enter this era where AI may simply render obsolete so many jobs?
Jordan Ray:That's a really interesting question. And I think the the most exciting thing about it and perhaps uncertain thing about it is that communicators, have a brand new audience to communicate to, which is AI agents. You know, when you go and search for any company or organization now on Google, the first thing you're gonna see is that AI summary. And if you're, you know, asking ChatGPT about something, people are now experiencing the world through this middleman that's an AI agent. So what are the things that you have to do to communicate with the AI agent so that it shows your intended audience the content that you wanted to show them?
Jordan Ray:And there's a number of ways to do that. And the good news for communicators is that it's a lot like traditional marketing and PR. It's about having a consistent brand and message across all the properties where you can be found. It's about having and it's about having validation from trusted, vetted, experienced sources like established journalists like you, Steve, that can then that are that look the same everywhere they can be found. And there are some technical aspects to it as well.
Jordan Ray:For example, is your website hosted locally in the country where your audience is? Because AI puts a a premium on that fast connection speed so that your website can be easily found. So so it's you have we have a new audience as communicators to tailor our content to, but the rules for that new audience is very similar to the way that we've done things for a long time.
Steve Paikin:You know, you've raised an intriguing question there, which is I mean, I've got a website like I'm sure everybody here does. I haven't a clue whether it's hosted in Canada or not. I have no idea if I'm contributing to digital sovereignty or if I'm a digital trader. How do I find that out?
Angela Adam:Steve, I can probably help you with that offline.
Steve Paikin:Please. Oh, okay, Angela. I'm gonna follow-up with you later on that because I do need to know. But, okay, Angela, while you've got the floor, you know, there are things for centuries that humans have felt they needed to do to really feel human, and we are having the most existential debates in our society these days about whether we are actually creating the tools for our own redundancy and demise. And, you know, I'm not smart enough to be able to figure out where that's going, but I guess it's your job, Angela, among others, to figure all that out.
Steve Paikin:Do you have any answers for us yet?
Angela Adam:I'll answer as best as I can because we're all in this experience together. I don't think we're creating our own redundancy. Why? I I don't want to believe that. I think we're in a in the middle of a major shift.
Angela Adam:And like every major shift, creating anxiety. Right? But also so much there's so much incredible opportunity. And I like this question a lot because I answer it periodically at home. I have a 14 year old daughter.
Angela Adam:She's a digital artist, and she often worries, you know, that her art's not gonna be valued or relevant in a world where AI can generate emails in seconds, can enter artist contests, or sometime when. And I always tell her, like, the same thing. Tools are going to replicate your style, but they're not really going to replace real artistry. They can't
Steve Paikin:I'm with you. I think that human connection's gotta be significant. Right? That's what that's part of what you're buying, is the connection to an actual person.
Angela Adam:The lived experience and the taste and the intent and the emotion. That's a very human perspective that gives any work that comes from us, you know, meaning. So if you take this a bit broad broader in in the economy, yeah, AI is absolutely going to automate certain tasks, but that's very different from replacing the human talent. Right? And companies that get it right will use AI to remove a lot of the friction that we now have and and free up people for, you know, more creative, more higher value work, and then the work that depends on judgment and empathy.
Angela Adam:Right?
Steve Paikin:Mhmm.
Angela Adam:Trust, original thinking. So, yeah, to go back to the question, no. I don't think the future is going to make people in our skills irrelevant. I think about being a lot more we need to be a lot more intentional about where our human value truly sits, and and we need to protect that, and we need to recognize it.
Steve Paikin:Well, this sage panel has decided, I guess, if I've heard properly, that arts, culture, and journalism are things where the human touch and the human connection are still important to maintain. Li Bin, what else would you add to that list? What else should be I don't say you can make it immune from artificial intelligence, but certainly that can compete with artificial intelligence.
Liban Abokor:Yeah. I think I think in this conversation, there's a significant demonstration of Canadian politeness. Right? And not to disagree or to, you know, counter what others have said, and so I wanna make sure I maintain that vein. But I would say that if we if you look around my house, I have a number of pieces of works apart that I bought from Marshall's.
Liban Abokor:It's not real. Right? It's someone has generated some copy of it. The same thing is true for the printing, you know, the printing press where it wasn't we no longer had the original text. We now had some iteration or version of it.
Liban Abokor:And, and if you look at movies and television today, much of those scripts are now written by human beings, are written by or supported and amplified by artificial intelligence. And that's exact same way that it took some time for us to go from riding horses to trusting the vehicle. Right? And so I think what we're talking about is a lag effect. I think what we're finding comfort in is normalcy and what we see as, like, familiarity.
Liban Abokor:But the truth is the horse has left the barn. I think that those who can afford to buy original pieces of art will do so, but I don't think the average person in the future will care whether or not a piece of art has been generated by an artist or by a computer, particularly when their prompt will be the one able to generate that piece of art, that song in a way that's actually emotionally connected to them. So what you're gonna find is the ability to make your own art, the ability to make your own music. Right? And so I don't think it's gonna destroy the desire for human beings to build these, these things, but I think it's gonna become a lot more, cons concentrated around building it on your own.
Liban Abokor:So that would be my my polite way of saying. I probably have a very different view about, about where we're going because I think it's a bit of a Halley's Comet moment. We're seeing the tail. Instead, we should be looking to see where the comet is going, and where it's going is a little bit more predictable than we might have led on.
Steve Paikin:Well, on behalf of Angela's daughter, I hope you're wrong about the part about the artists. I'd still like to think that yeah. I I mean, it's wonderful that I think at some point, I'd like to have the skill to be able to create something using artificial intelligence that I can put on my wall, but that's not gonna be as meaningful to me as that picture of Queen's Park over my shoulder, which a real guy did, and I know who the guy is. And and and having that connection to him, I think I mean, it's important to me. But, Jordan, let's let's figure this out if we can a little bit.
Steve Paikin:I know we probably all saw on on the news, oh, I don't know, about a month ago, somebody managed to create a a truly fantastic AI generated scene as if it were in a real movie. It wasn't, but it looked like it was of Brad Pitt and Tom Cruise having a fight. And, I mean, it was pretty good. And if you think about it, it's the first shot out of the gate, and, you know, you could see where it was not quite a 100%, but it was pretty darn good. Almost immediately, Hollywood reacted and said, we need some new rules and regulations around this because they need to be able to preserve their images.
Steve Paikin:And and, you know, the fact that we can do it doesn't mean we ought to be allowed to do Can you imagine some other areas of our world where we're gonna have to put up some tall fences or build some, you know, build some protections in place, either to maintain our humanity or our images or our whatever. Over to you.
Jordan Ray:Absolutely. And and what we saw when during the writers' strike and the actors' strike a couple of years ago was that this was a major issue. Right? The that was a big part of the negotiations between actors and writers and the big studios. And those unions actually won big protections within Hollywood for protecting the value of human IP and human creativity.
Jordan Ray:If you look at the way that the European Union has put in a lot of these regulations, they have this kind of sliding scale of restrictions that gets more and more strict when you sort of move up the the danger chain as it is. So for example, in the EU, it you cannot use AI for facial recognition unless you're a law enforcement agency. So I think we'll be and I imagine that the the strategy that minister Solomon is coming out with is gonna be looking at the European Union, looking at what they're doing in The US, and looking what they're doing around the world to see, okay, what are the best practices? What's working? What's not working?
Jordan Ray:Another thing that the EU is doing is saying to the AI companies there, you need to submit your model to us so that it's not a black box for the public so that we can look inside, see how your models are trained, and we can make sure that it's safe for everyone. So and I'll make one last point in terms of the you know, we've talked a lot about our anxiety around AI. The fundamentally, it's important to remember that, and I should have mentioned this earlier, these AI tools are only prediction machines. And what that means is that they're trained on large sets of data. And they're trained to say, okay.
Jordan Ray:If my user is entering, why did the chicken cross the road? I think it's a 70% chance that it's gonna end with to get to the other side. So every time you enter one of these prompts, it's looking through all that vast amount of data to say, okay. What do I think is the most likely next response to this based on all of the data I currently have? The big limitation of that is that it can't create new things because if it's predicting what is coming next based on what has already happened, then it cannot predict something new, which leaves us in a good place if we're in the creative business.
Steve Paikin:Right. With just a couple of minutes left here, let me read a couple of things that people have put into the chat here. I know when I mentioned the Brad Pitt, Tom Cruise thing, somebody put into the chat here, Val Kilmer's estate. You know, Val Kilmer played Batman. Jim Morrison in the Doors movie died not too long ago.
Steve Paikin:Val Kilmer's estate just approved the use of his likeness in a film. Okay. We've not heard the last of this, have we? Here's somebody. Okay.
Steve Paikin:Angela, your daughter's gonna like this poster. There should be a policy to protect these areas, art, music, cultural commentary, and news. I think we can all get aboard on that one. From AI or at minimum regulate its use. Okay?
Steve Paikin:That's a perspective. Here's also from an environmental perspective. Why degrade our environment to replace people in the creative artistic space? That's a very nice rhetorical question that we shall just leave out there in the for us all to soak in. Can I just ask each of you to give our viewers and listeners one little piece of advice for the road?
Steve Paikin:Running short on time, so maybe just thirty seconds from each of you on one takeaway from today's discussion, and why don't we go in inverse order from the way we started? So, Jordan, you first.
Jordan Ray:Yeah. Absolutely. I would say if I was to advise particularly organizations out there looking for how to use AI, try to go with companies that have done the work to earn the social license to make their AI and their AI infrastructure reliable and sustainable for the communities that host them long term because, you know, we're seeing pushback against this stuff across the board. And the companies that are gonna go the distance will be the ones that have put in the work to consult and work with communities to make sure that the future works for all of us.
Steve Paikin:Good. Lieben.
Liban Abokor:I'm gonna try to answer that question slightly differently, if I may, Steven. I'm gonna take you back to your your days at at TVO where you talked about our democracy and how important it was to protect it. One of the things that I would leave this group with is, trust in our institutions is eroding. It's something that we discussed earlier. And now we have tools that can generate disinformation at an industrial scale, convincing texts, images, even videos at, and the barrier for manipulating public opinion has become really low.
Liban Abokor:So I it's not a doomsday comment I wanna leave with, but it's one that I think is important to communicate. Today, we're able to people are attempting to use tools that simulate public opinion using AI. Right? So think about polling. We have a few upcoming elections, by elections that are upcoming.
Liban Abokor:And what we're seeing here, folks are using the models to say, how would a 35 year old black woman in Toronto feel about this housing policy? Or how would a rural voter in Saskatchewan respond to a carbon tax? We're now doing that. And, my reminder to folks is just to ensure to say, democracy is not about outcomes. It is about participation, and we cannot permit artificial intelligence to replace human voice with data.
Liban Abokor:It's something that we need to be thinking about deeply, and, that would be the thing that I'd say if any of you are walking away with, you should be holding your decision makers or policymakers to account to ensure that it does not erode our our democratic participation and really the foundation of what I think makes Canada great.
Steve Paikin:Well said. And just as you were speaking, somebody put here in our chat, it's going to boil down to trust. AI will erode our trust in what we see, read, and hear. We may end up going back to face to face meetings, discussions, negotiations. Over the Internet, Zoom, and other platforms will end up with leaving most of us with a suspicious sense of what is real.
Steve Paikin:And I know we've all had the experience. It happened to me earlier today. Somebody sent an email saying, look at this amazing speech. Bill Clinton is defending our position on tariffs. And I had to email the guy back and say, I hate to tell you, that's all fake.
Steve Paikin:That is not Bill Clinton. That is really good AI fakery, but it's not the real deal. Okay, Angela. You're batting cleanup. Your last word, if you would.
Angela Adam:Yeah. Well, listen. I'll echo what was said. Stay informed and stay educated. But if I take a bit of a broader look, I think listen.
Angela Adam:We have a real opportunity here. Canada, we don't we have all of the ingredients to be a really great leader in the in this data economy. We have the talent. We certainly have the geography and the and the abundant and clean power. We have so many advantages.
Angela Adam:Strong very strong case for for good trusted infrastructure. But this opportunity really only matters if we move with enough speeds and discipline. And like I said, we stay educated and that we all stay coordinated on it.
Steve Paikin:Marvelous. Everybody watching, indulge me for thirty seconds while I wrap this up by thanking you, for starters, for joining us on today's presentation. And, of course, to Angela Adam, Leban Abacore, and Jordan Ray for sharing their insights. If you missed any of this, Curious Public will be sharing the recording as both a video and audio file, so keep your eyes open in your inboxes, and don't delete all your emails, particularly this one when it comes in. Thanks again to the folks at Curious Public.
Steve Paikin:You're a delight to deal with. I'm Steve Paken. Until next time. So long, everybody.
Shannon Currie:Comms In Question is presented by Curious Public and produced by Emma Earley and me, Shannon Currie. Want to learn more? Visit our website at curiouspublic.com, or get in touch at info@curiouspublic.com.