Artificial intelligence and machine learning are two subjects in which I’ve long had interest, especially as they relate to organizational change, people’s behaviours and communication, and the future of work. This keen interest is a prime reason why I joined IBM earlier this year, and has intensified as I’ve got to know a great deal about cognitive computing and, of course, IBM Watson.
They are both areas where I have some clear views on what this means for organizational communication (including public relations), eg, automation in the workplace. So I was thrilled to be invited by Chip Griffin to join him in conversation in his latest episode of the “Chats with Chip” podcast to discuss such topics.
In “Chats with Chip,” we talk for a little over 30 minutes about the roles artificial intelligence and machine learning will have in the public relations industry. We talk about everything, from the automated creation of news stories by computers to the role that big data plays in communications, to the crucial role organizations must play in softening the social cost of such technological change, and a great deal more.
Take a listen:
If you prefer to read, here’s a transcript of our conversation.
*** UNVERIFIED TRANSCRIPT ***
Please review the audio before quoting to confirm accuracy of this unverified transcript.
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 our 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 about what you are 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 6 months ago from as we’re talking today. A bit of a pivot actually. It’s 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 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 that’s very close to a topic that I am 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 am at. A real career pivot I would add, so it’s a big change.
CG: 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 communications industry, you know, whether you are on the PR side or the media side or marketing side 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 rise of the machines 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 had a prediction from [Gartner 00:02:07] where it says that, “20 percent of business content will be authored by machines, within the next 2 years,” and you know, 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 said that they were going to automatically generate stories about Minor League Baseball games based on statistics that they were given in box scores and those sorts of things. First of all do you agree with that prediction? Do you think really that much of business content is going to come from machines in that sort of period of time?
NH: 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, some people are calling robo-journalism, where computer algorithms basically create the content and if you look at what exactly are they creating? It tends to be content that doesn’t require reasoning that doesn’t require, for want of a better word, deep cognition in terms of looking at things from different angles and presenting scenarios, they are reports largely and so you see things like the AP on sports reporting that other you mentioned recently about, I think it was baseball wasn’t it Chip?