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CWC 10: Neville Hobson on AI and machine learning in PR

Neville Hobson talks about the role artificial intelligence and machine learning will have in the public relations industry.

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On the latest episode of Chats with Chip, I’m joined by Neville Hobson to talk about the role artificial intelligence and machine learning will have in the public relations industry. Neville is the co-founder of the FIR Podcast Network and currently works for IBM — home of Watson. We talk about everything from the automated creation of news stories by computers to the role that big data plays in communications — with a digression or two along the way, of course. The post CWC #10: Neville Hobson on AI and Machine Learning in PR appeared first on FIR…

Click to read the full article: CWC #10: Neville Hobson on AI and Machine Learning in PR

The following is a computer-generated transcript. Please listen to the audio to confirm accuracy.

You’re listening to Chats with Chip on the FIR Podcast Network.

Chip Griffin: Hi, this is Chip Griffin, and welcome to another episode of Chats with Chip. I am very pleased to have as my guest today, Neville Hobson. Neville, of course, for long time listeners, is the co founder of the FIR Podcast Network, along with Shel Holtz, and now he’s left the routine, podcasting world behind and, simply appears as a guest, but he’s also working for IBM.

So welcome Neville. And why don’t you tell us a little bit about what you’re doing with IBM?

Neville Hobson: yes, I will Chip. Thanks very much. Indeed. A pleasure to be chatting with you on this podcast. I joined IBM in January, 2016. That’s about six months ago from, as we’re talking today, a bit Pivot actually, it’s not, not much to do with organizational communication in the sense of what I was doing before.

It’s a lot to do with business transformation and a lot of corporate words like that, that clients of IBM would go through. So I tend to have conversations with people looking at the social elements of all of that in terms of sentiment analysis, in terms of how that, enables people to. make better decisions, I suppose.

And, and that’s very close to a topic that I’m very keenly interested in. One of the reasons I went to IBM, which is this whole huge area of artificial intelligence, machine learning and so forth and so on epitomized in IBM Watson. and so that’s basically where I’m at a real career pivot, I would add.

So it’s a, it’s a big change.

Chip Griffin: Well, it sounds very interesting, and I think it gives us a lot of fodder for things to talk about on this show because, artificial intelligence, machine learning, obviously Watson is at the pinnacle of that, I think, when people think of, you know, smart machines, but, you know, as we look at the, the communications industry, you know, whether you’re on the PR side or the media side or marketing side, there’s a, there’s a lot of change that’s going to be happening I think in the coming years and really already has a little bit because of the the rise of the machine as it were and what it can do for you and you know one of the things I was struck by was a blog post you wrote earlier this year and it it had a prediction from Gartner where it says that 20 percent of business content will be authored by machines Yeah.

Within the next two years. And, you know, we we’ve certainly seen some stories. There’s a company that produces for the Associated Press automated, financial report stories, and now just recently came out and said that they were going to automatically generate stories about minor league baseball games based on statistics that, that, that they were given and box scores and those sorts of things.

you know, I mean, is this, first of all, do you agree with that prediction? Do you think that Really that much of business content is going to come from machines in that short of period of time.

Neville Hobson: I’m not sure about most. I would say that the trend is quite clear. And if we look at what machines, for want of a better word, are doing in this area, the AP is a very good example with the automated, what some people are calling robo journalism, where computer algorithms basically create the content.

And if you look at, well, what exactly are they creating? It tends to be content that doesn’t require reasoning, it doesn’t require, for want of a better word, deep cognition in, in terms of looking at things from different angles and presenting, scenarios that reports largely. And so you see things like the AP on sports reporting, that other one you mentioned, recently about, I think it was baseball, wasn’t it, Chip?

Yes. That, sport, major, not major league, I think it’s the other league of baseball, that, that, this sort of reporting that recounts a factual event, you know, this happened, it started, so forth, he did that, he did that, and so forth, yet it’s adding some interesting elements to it, which are suppositions, almost philosophical, opinions, but this is still relatively simple, for, for that technology to, to handle.

And if you look at that kind of content, we have tons of it in the communication business ranging from, press releases, through to white papers, and that kind of factual content that is simply stating facts in a certain format. And so that, that lends itself, I believe, very, very nicely, to clever technology to take that burden away from people and be able to, churn out this kind of content far more rapidly, far more quickly.

Now that’s a dead simple comment. There are all sorts of issues surrounding all of this as, as most people, would agree. and that’s just looking at the simple level. Wait till we get to talk about the, the real cognitive, aspects that are coming down the line that, that I think will have a dramatic impact on society at large, much of which we’re seeing already people discussing, often in rather, scary kind of terms, you know, the robots are coming, it’s going to get rid of all our jobs and we won’t have work, et cetera, et cetera.

So it’s a huge topic as you noted, Chip. So, lots to talk about without any questions.

Chip Griffin: Yeah, you know, look, I mean, I, I think, and I’m a huge fan of AI machine learning technology in general. I’m, I’m a complete geek. you know, but I guess I look at it and say, you know, I, I think the real value of it, lies in informing your decisions, in making, your jobs easier, but.

You know, I’m not a huge fan of the, the robo journalism, approach. I mean, to me, what they’re doing is they’re taking data that doesn’t even necessarily need to be in paragraph form and turning it into a paragraph, right? So it’s almost just adding useless text to call it a story. And so I’m curious whether that’s actually beneficial or whether that just, you know, sort of contributes to the, the dumbing down of the media industry that.

I think it’s been occurring now for some time.

Neville Hobson: Well, you know, that’s an interesting observation. I hadn’t looked at it like that. I don’t necessarily agree that it’s dumbing it down because if you read some of the content, and again, I go back to the AP, because they are now, an interesting use case, if you will, in the sense that they started doing what they were doing, i.

e., an algorithm writing the sports reports. And they’d been doing it for about a year before So I’m not sure it’s dumbing it down. It’s taking on a responsibility to do something that previously had been done by a human being. And now, of course, therein lies the problem. The issue, for instance, yesterday, I saw a news story here in the UK about Sky News, the, the satellite TV company and Sky Sports, which is a huge sports broadcaster and a news broadcaster that they are eliminating 50, job roles in the UK and reporting These are camera men.

Replacing them with robotic cameras. So automated cameras. So these are the things you see already on, notably on the BBC News here because they tend to show you these kind of sweeping views of the newsroom and there’s the newsreader sitting at this larger, this really large table, quite an attractive setup, surrounded by machines that are moving of their own volition.

These are the cameras. So that’s what’s happening. And you think, wow, here’s an example of how automation is replacing human beings. yet. The other part of the story is equally interesting in that that change has also resulted in 30 new jobs that wouldn’t have existed if they hadn’t made this change. So the net loss is still, you know, 20 or so people.

But I think that’s an inevitability that there are going to be, situations where, The technology is more efficient and more cost effective, all those words that are not human friendly to fulfill a certain function, meaning that the human beings did that are going to have to be redeployed, find something else, retrain or not work there anymore.

And that’s as blunt as I can put it. That, in my view, is part of the new reality that is coming. So it will be. to a certain extent, disruptive in, in our society, it will have a social cost, but look at any change, over the last couple of hundred years, starting with the industrial revolution that, that led to this, that’s not to say therefore it’s all okay, far from it.

But the reality is that, these sorts of changes in, in democracy, certainly which are not, you know, market forces control things, if you will, are going to happen. It’s up to others, notably governments, to try and, and see how this, the social cost of this is as minimal as possible with whatever they need to do to participate in these changes.

So that’s a bigger picture view of what’s coming, I think, Chip.

Chip Griffin: Yeah, well, and as you know, this is not, this is not something new. It is something that every time technology has advanced, there have been these switches. I mean, you know, there, there used to be more farmers than there were more factory workers.

There used to be more postal workers. Now there are more people working on email, you know, so there is a, there is a, A constant evolutionary process that’s going on, you know, within the, the working economy. and, and I think that, you know, yes, is, is, is it going to be painful for some individual people who are out of jobs?

No doubt about it. And I certainly feel for, you know, the, the camera people who, have lost their jobs with the BBC, but at the same time, as you note, it’s created new job opportunities and it’s also, you know, probably, you know, increased some of the, the capabilities of, not just the BBC, but other, TV production companies to have these things and, and make it, I mean, you know, for example, a lot of people who appear on, you know, CNN here in the States actually have a robotic camera in their homes if they’re regular guests.

and so, you know, they no longer have to go to a studio in order to appear live on TV. and so that’s a huge benefit both to the network, as far as the quality of content they can get. But also to the guests so that they’re not constantly traveling back and forth to a studio. So, you know, look, I, I mean, I, it, it certainly can create pain, but I think the, the amount of opportunity that technology is creating, you know, far surpasses it.

Neville Hobson: Yeah, I agree. And in fact, if we, if we kind of bring the focus to, to the communicator. I tend to see it, you noted what, what, what I wrote in my blog about Gartner’s prediction and how this is coming at a pace, and I agree it is coming at a pace, but it’s not uniform. This is not like suddenly tomorrow everything will change and, and we’re all under threat of losing our jobs.

It’s not that. It’s not quite like that. I see significant opportunities all around us, for communicators, whether it’s, in whatever branch of communication you happen to be working. I, I would add, though, that if you’re, if you’re, you know, 100 percent job is writing press releases, that’s probably a good, Place to start in evolving your career into something that that is not going to be, the target of, of, robotic journalism for want of a better way of putting it because that to me is a classic example.

so, what I see happening, is, the, the computer algorithms, the technology behind it all, taking on the job, if you will, of, taking data that it is able. to repurpose in a sense to extract insights in a way that, we can also do that, but it takes us a very long time.

It’s, it’s, at the whim of human behaviors, and all that stuff that you could think of. And here, instead, you have a machine doing this stuff that then presents us with that analyzed data that lets us then, write something real smart or, again, putting it in a simpler sense, the algorithm will write the first draft for you.

And it stops, it then lets you focus on adding your own reasoning, adding your own insight, your own take on a particular story. And I would argue that’s not really any different to how things have been done like that for a long time with, with research assistance and other people. Now the question comes, cause I’ve been asked the question, does that mean they’re gonna lose their jobs?

I don’t know. I would imagine that, that, that, that The focus on job loss and serious changes in circumstances of human beings working assumes that, that robots come and nothing else changes. I certainly don’t see it like that at all. I could see this as part of the broader evolution, in business structures, in the workplace, in how people, see their jobs, in the sort of, of things that, people want to do, that they can do, that they’re encouraged to do, that they’re unable to do.

And that’s not to say that, therefore, it’s this nice rosy utopia we’re all heading towards. I think it will be tough and there will be a high social cost with these changes, yet is it inevitable? I believe it is. Equally, I know lots of people who argue very strongly that that is not an inevitability because of the social cost.

So this is the kind of, you know, ongoing discussion that there isn’t an easy, simple answer reality in the communication business. I believe that before too long, it will be commonplace that things like white paper, things like the kind of documentation that we create for our clients or our employers, ranging from white papers, as I’ve mentioned, through the press releases, other, content like that will be better.

done by computer algorithms that leave us to, to concentrate on more valuable activity on the one hand, or use that, computer generated content, to enhance our own cognition, if you will. It, it, it kind of reinforces us. It helps us, be more effective in what we do and how we, identify, topics that we want to write about or, get zero in on the important facts in a document.

The machine can do that more effectively and quicker than we can. So I think of it as a very useful research assistant on the one hand. So you, there are lots of people with different views on all this Chip, but in, in this profession, I see that as one example of the beneficial change that, that is coming our way very soon.

Chip Griffin: Yeah, I think you used a key word there and that word is helps, you know, the, I don’t think ultimately that, you know, AI machine learning, smart machines, whatever you want to call it, replaces the jobs that communicators do. And you know, I, I am a huge data nerd. you know, I, I founded a company in, in custom scoop that is, you know, really focused on mining data and providing insights.

you know, nowadays I would call it media intelligence rather than simply media monitoring, but it’s, it. You know, at the end of the day, even though I talk about what I would call data driven communications, it’s really, you know, data informed or data assisted communications. Because ultimately, we all need to bring to bear our own expertise, our own experiences, and our own judgment.

And so I think even, even in the case of a white paper or a press release, I can’t imagine a day where you would have that go out automatically without a human review. you know, I, I, Computers will do a very good job of a first draft, but it’s still, to me, is a first draft and you still want to go through it and, you know, make sure that there, that the computer didn’t make a misjudgment anywhere because ultimately computers are just a reflection of the people who created them.

and the, the intelligence that goes into them is, is based on the judgments that the coders made and the business analysts made, you know, at the start of the process.

Neville Hobson: Yeah, broadly, I’d agree. I’d also add that since I joined IBM, I’ve been playing a lot, playing around a lot with what Watson can do.

and that’s, in my opinion, that’s way beyond anything I’ve currently seen elsewhere out in the public domain. I’m not thinking of, you know, Other companies like Google and Microsoft and their, and even Apple for that matter, their own efforts with developing artificial intelligence. But in the case of Watson, it is truly streets ahead of any, anything else that I’ve seen.

in, in that it gives me certainly confidence in some of the little experiments I’ve played with of, that tool creating something for me that I don’t need to check. that I’m confident after four or five goes at it That yeah, okay, I can trust it, that it isn’t suddenly going to insert a random sentence that is completely off the wall or it signifies it had a headache or something like that.

And boom, there’s, there’s a blip, a paragraph that makes zero sense in the middle of a text. I’ve not seen that. So it’s already quite clever yet. I would add as well that this is a bit like, you know, automated driving in cars, autonomous cars. And what happened with Tesla recently, where this is definitely not.

perfect yet. This is still very much. We’re trying to figure this out territory. and not everything is going at an equal pace. Look at the huge interest right now in chatbots. look at, recently the Microsoft experiment with tay and how wrong that went. I would argue very much that that wasn’t about the tech.

That was about the human beings, both the coders and how they approached it. Plus, you know, the reality of People’s behavior on the social network like Twitter. So, that reflected a dark side of human behavior that they had anticipated. And that’s nothing to do with the technology, in my view. So, it, it, we are at, the beginning of all of this.

And so, I see, literally anything I see going on is still a threat. We’re trying to figure this out and some of it’s very good, but generally, I wouldn’t disagree with you at all chip that if I were, you know, in a, in a, a real world situation, relying on my cognitive assistant, let’s call it, to generate content for me.

How comfortable would I really be if I were presenting the reports and papers to someone else in my employer or a client, for instance, that I’d be okay with that without checking it? Well, I’d probably apply the 80 20 rule in that I’d be comfortable most of the time, but now and again, I’d probably want to check it.

And indeed, I definitely want to do that if it was something I felt was seriously critical until such time as it evolves into something. that I can feel confident in and have trust in that it isn’t going to screw it up a bit like that autonomous car that isn’t going to crash or misread a situation and cause either cause an accident or itself be in one.

So we’re still in the early days of all this, I think.

Chip Griffin: Absolutely. Look, I think it will change too as, you know, as more and more people, start using automated, technology to create content, right? Because, you know, one of the challenges you have today is that, you know, you probably wouldn’t go out and broadcast, Hey, I didn’t actually write this white paper.

It was done by computer. you know, I mean, maybe IBM would, right? Because it’s beneficial to, to, you know, to the company to do that. But I mean, certainly if I’m creating a white paper, I’m going to pretend as if it’s, it’s human generated because right now people value that more than computers. Right. And so, you know, that puts you in the awkward position of if there is a mistake, having to not only confess to the mistake, but also confess to how it was made, whereas, you know, in three or four or five or ten years time, whenever it is, if a lot of people are doing it, then it becomes less significant.

Look, I think, you know, it goes to the, the automated, driving example, you know, the self driving cars, which I think is a great development because personally, I hate driving. And if something can get me from point A to point B without, you know, my engagement, that’s fantastic. But, you know, today, You know, if a Tesla car gets in a, a single fatal accident, that makes national headlines, you know, but over time, as more cars are, are being driven by computers, you still will have accidents, but they won’t be as newsworthy because it’s just, you know, it’s sort of, A common behavior at that point.

Neville Hobson: Yeah, it is. It is. And in fact, let’s look at one other thing, too, that things like automated press or whatever it is that people tend to focus on is simply it’s just one element of all of this. To me, it’s not the most important element. I could I see way more value activity coming from automation of repetitive tasks in the workplace.

And again, looking from the communications point of view that we look at the amount of of information we have to sift through the amount of, of content we have to read and absorb in order to make judgments in order to come to decisions on the next stage we take that to, in that particular bit of research.

We often tend to call it research. We read documents, read reports. We look at the newspapers, the radio, the TV, social media, all that stuff. And we take. key, key elements of all of that to make our own decisions. So much of that is still, utterly manual. Yeah, we might use some, you know, proprietary services we subscribe to, which give us the filtered information, all that kind of stuff.

Yet, that’s still not good enough. I’ve seen some fabulous statistics recently, Chip, about the amount of data that’s coming. You know, we’re at a stage now where we’ve got, you know, whatever the word is, is it petabytes or zettabytes? I’m not sure. But I saw a great slide the other day that talked about in four years time, 2020, we’re, we’re expecting to be exposed to something like 45 zettabytes of data every single day.

And you think that sounds fab. What on earth does it mean? How much is that? And the creator of that translated it into, into a format we can understand that’s equal to 600 volumes of the complete Harry Potter series. Every day, 600 billion, sorry, I missed off the important number, 600 billion copies of Harry Potter every single day.

That’s what’s out there, and the reality is we cannot, hope, to, to, to, to grab even a, even a, you know, a 0. 001 percent of what we ought to be looking at. And that’s where machines can help us. Machines, I’m using that in the accepted term, people to, computer algorithms, or whatever it might be. That will, will, will be.

Analyze that structured and unstructured data. And this is something I’ve learned recently, that unstructured data is the key one. And that’s data you cannot anticipate what it is. News reports, for instance. events, even. geospatial data, weather data, social media, all those things. You cannot predict what is going to be said in three days.

Let’s say, whereas structured data are things like the records you keep, predictive modeling that you might conduct, your expertise and thought leadership in your own organization. You’ve got a record of all of that. You know, that data and this in a database somewhere. So you’ve got all that stuff, but all that other stuff you don’t have.

And then look at data that’s coming. in this scenario model that I mentioned about what’s coming by 2020, the, the so called internet of things, everyone agrees. This is big data writ large, but no one agrees exactly what it looks like. You’ve got so many different views. Something is clear though. This is coming, whether it’s 2020 or 2025 or whatever, it is on the way.

We’ve got images, the growth of video and all this stuff that is hard to search. That’s changing. You have tools. Indeed, Watson has some of this capability of analyzing videos. Through, hey, really unscientific way of describing it, Chip, but I call it number crunching on a mega scale. It looks at pixels, it looks at light and darkness densities, and a whole ton of things to come up with.

it, this picture is X, or this picture shows this person in this situation. And we can’t do that. Right now, as human beings, I liken it a bit, although the scale is hugely different to, the ad, the, the, the dawn of social media when, when things started going ranging from blogging, through to podcasting and then, then Facebook and then social networks start developing where we had tools, like.

That’s the one that comes readily to mind because I used to use it. That was how we would, analyze this and, and draw insights, from what the analytic, the analyzed data was telling us. But that now is, is not really capable of doing what we really need to do, where you do need something that we currently call artificial intelligence.

I think a more, appropriate way is a cognitive, enhancement, I suppose that, that this, this information enables us to perform our jobs far more effectively. And I see this as something that we should not fear at all. We should look at this as a, as a hugely beneficial evolution. but tempered with the reality that there is a social cost to this.

I believe very clearly that there will be a social cost and we have to plan for that in organizations and, and figure out, you know, what do we do if we decide to go down this route that brings in this technology that means that we can have a computer algorithm performing the tasks that we had 10 people doing before.

What happens to those 10 people? How do we evolve their role to take, to take advantage of this? These are huge challenges for the HR folks in every organization Chip, I reckon.

Chip Griffin: You know, you very smartly note the difference between structured and unstructured data and, you know, the huge potential in dealing with unstructured data and, of course, you know, with CustomScoop, that’s basically what we’ve dealt with for 16 years and, you know, we don’t do it in an artificial intelligence kind of way.

We simply try to impose some degree of structure on unstructured content and, and that’s, you know, beneficial. But, you know, clearly artificial intelligence and machine learning will help us do those kinds of things more effectively. But. Frankly, even on the structured data side, there is so much of it that I, that I think machines can do a, a, a better job of, of helping us to understand it.

And I, I think even if something simple that, that almost every communicator is familiar with to one degree or another, and that’s Google analytics and, you know, Google analytics, you can go in and slice and dice the data in a lot of different ways. And, you know, if you, but if you read someone like Christopher Penn, who I think, you know, probably.

Knows Google analytics better perhaps than the creators of Google analytics. and, and does all sorts of tremendous blog posts explaining you how to get the most out of it. And, but, but even he’s, you know, sort of, it’s almost a game of twister where he’s, you know, you got to bend around backwards and guess and do all these things in order to get the most out of it.

To get the best insights possible out of it. I mean, if we had, you know, really smart computers that could simply look at that and say, okay, here’s the important nugget for you. And it’s not necessarily which piece of content was the top on your list, or it may not be the most important. even the page that converted best.

But here’s something that we’ve gleaned from this data that, you know, is actionable intelligence for you. And when computers are able to start doing that on a routine basis for people, I mean, that’s just, that would be huge for not just for communicators, but for anybody.

Neville Hobson: I totally agree with you, and therein I think lies the reality of what we can expect to see.

That will happen on a very uneven scale, where some organizations will be at it, others won’t. But that’s just the nature of human society, I think. We’re not all the same. Our needs are very different, and we will, See the, the early adopters and the leaders, doing things we can learn from. and I, I think, you know, that those organizations who, who will be at the vanguard, will be out at the front there would, would be, would be wonderful if they were able to, openly share their learnings from all these things.

We are in a, I think, in a time in, in society, generally speaking, where sharing, is a common activity these days, and I could see that. fitting in with the, the other shifts we’re seeing in organizations, the, the very structure of organizations, what I tend to call, and I’ve not invented this phrase, by the way, the gig economy, where people, are, are taking, temporary relationships.

They’re building bridges with people inside and outside the organization. So those, those organizational borders are becoming ever more porous. So we are able to connect with others in, in ways that we couldn’t imagine doing, 10 years ago, nevermind a generation ago. So a lot. Is fluid a huge amount is changing is is shifting sands in front of our very eyes we need maps to navigate this and a lot of it we need to figure out ourselves luckily we have the internet to help us but I see organizations needed to do a lot more to help us navigate these things by helping us create those maps so there’s an opportunity and I say communicators have that opportunity as much as anyone else does.

Chip Griffin: We’ve only got a couple of minutes left but something you’ve touched on. A few times in this podcast that I’d like to just circle back to is our final bit is you’ve talked about the social cost and the need for both organizations and government and others to really be mindful of this. I mean, do you have particular ideas of things that we should be all thinking about as far as, you know, how to address the social costs of these advances?

Or is it, is it really just the sort of an evolution of the same kinds of things that organizations have to look at, you know, in the past? You know, 80 years, job training, you know, employee education, all those kinds of things. What do you have in mind?

Neville Hobson: It’s all of those things, Chip, without any question, because not everyone works at, you know, internet speed, let’s call it that.

Not everyone is comfortable with this online world in every society, in fact. They need hand holding, they need help. So there’s a great opportunity for social advancement in all of this, in the original sense of the word social. I don’t see it in political terms by any means. I think governments have a duty, a responsibility to enable things to happen.

Chip. And by that I don’t necessarily mean funding or whatever, it’s just making things available, opening up doors, lessening barriers, getting rid of all the red tape that we have all around us all the time, and I think organizations need to set their stall out there in terms of what they are going to do with all of this, so we could see the evolution of more collaborative, activities, between organizations, including governments than we have seen in the past.

I have a glass half full approach to all this, Chip. I’m very optimistic. I believe we will see things like that happening. I don’t believe it’ll be uniform. I think there will be some, parts of, of, governments in particular that have to be drag kicking and screaming into this. So we need strong voices, people who are confident.

people who we look up to now finding, if you will, heroes in our environments that we can look up to who can take the lead in helping us understand this and navigate the changes that are coming. Otherwise, I think the pain will be great. So in a sense, it’s minimizing the pain on the one hand, but it is enabling us to be confident in these changes and not be too fearful, understanding, yes, putting in the place of retraining and new job opportunities, totally enabling.

Companies to make all that sort of thing happen. So it’s an, it’s an interesting time coming. I think it presents communicators as well as many others for that matter. But let’s, let me focus on communicators with great opportunities to help communicate this for understanding and also to find out, you know, What the issues are in organizations that need, need, need to focus on where communicators can play a key role in this.

So it’s an interesting time, another interesting time we’re about to embark on, I believe.

Chip Griffin: It certainly is, and the opportunities are great. There are tons more things we could talk about on this topic. Unfortunately, we have reached the end of our allotted time. But it’s, hopefully, our listeners are sitting here hoping that we could talk more, because that’s all always the way I like to leave people wanting more as opposed to saying, you’re still going.

But, in any case, Neville, I really appreciate you joining me today. Perhaps you could tell listeners where they can find you online.

Neville Hobson: Sure. Yes. My pleasure. It’s been great fun having this conversation. So, I write a blog, www.nevillehobson. com. I’m on Twitter @jangles and indeed I’m all over the social web, but Twitter is the primary place where you can find me.

Chip Griffin: Fantastic. Thanks, Neville, and thank you all for listening.

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