Part of a 30 day series on the intersection of AI and 30 other exponential technologies, as explored by cross-over influencers and experts.
These "combinatorial exponential" technologies, as Frank Diana calls them, could have exponential impacts on the world in isolation - but when they combine, things will get really interesting.
Social media is one of the best sources of meaningful data in the world, when you can get access to it. LinkedIn didn't hold their data close for no reason, for example: they sold it to Microsoft for $26 Billion.
Other companies, and no one more than Twitter, are taking a different approach: building an ecosystem of value around their data by allowing 3rd parties access to it. (Here at Little Bird, we analyze a lot of Twitter data. And both LinkedIn and Microsoft are our customers.)
Almost No One in "Social Media" Paying Attention to AI
Where there is a lot of data, there is a lot of opportunity for Artificial Intelligence to analyze that data. So why aren't more "Social Media Influencers" paying attention to AI? I don't know, but it's a real shame. Perhaps as a result, there's a drought of imagination regarding what AI and Social Media could do together in the future. Maybe it's a power law, and for most of us AI feels too hard to pay attention to the specifics of.
Many engineers are paying attention of course. Hootsuite recently did a great round-up of the AI technology strategies at each of the major US social media platforms. And IBM is an exception to the rule. (Also a customer.)
But our analysis of the connection data between more than 1,000 "social media influencers" and the world of AI thought leadership suggests that most social media people just aren't paying attention.
In this series on 30 different industries and their thought leaders' intersections with AI, we've looked at Food Tech, Genomics, Renewalbe Energy, Fintech and more. Every one of those sectors has more meaningful intersection with AI thought leadership than Social Media does.
Who’s paying the most attention to both social media and AI?
We used Little Bird’s influencer discovery and research technology to find out, (as you can use it to find key people in your industry).
In today’s edition of our 30 Days of AI series, we’ll share a few people to watch - and a few potential scenarios for the future. Subscribe via the form on the right side of this page to recieve the whole series as it's published and notification when the series is available as an ebook.
We'll take a look at a few possible scenarios being discussed among experts at the intersection of these fields.
Here are some scenarios identified by subject matter experts in the intersection of these two fields that could unfold over the next 5 to 10 years of social media + AI.
Better recommendations - of content, people, and offers. Much of AI today is focused on recommendations. (Why don’t we call it facilitating discovery?) A cynic might say that content and people recommendations are ultimately intended to keep you around on social media long enough to recieve ever-more optimized product recommendations.
On the up-side, this can increase the value on social platforms for all of us - however we define value. You like political things, I like funny things, we all get excited about filling our needs in particular ways. With more time, we’ll have far, far more data to analyze, and both optimization and personalization should improve dramatically. "The recommendation engines that emerge will enable choices, accelerate decision making, and ultimately provide filters that deliver situational awareness," writes analyst Ray Wang in a really good general B2B overview of the opportunity in AI, not social media specific.
One down-side of these recommendations are that human relationships are far more complex than most quantified systems can capture, at least today. See, for example, people-recommendation systems that build on a therapist’s phone contact list and accidentally disclose professional relationships between confidential clients. Another down side is that perfect recommendations may make a perfect filter-bubble and replace democracy with safe, thoughtless, convenience.
More Humanity: If AI can analyze the heck out of social media data and recommend truly wonderous, beautiful, surprising, fabulous things to end users, that's great. Perhaps it will also optimize commercial promotions so effectively that it will be a huge business boon. But there may be diminishing returns there. Deloitte's John Hagel penned a beautiful piece this week that says any business process built on the industrial model's focus on efficiency will (1) be taken over by machines and AI soon, and (2) see diminishing returns over time. You can only get so efficient. If, however, all the work that can be done by machines is done by machines, and the rest of us are freed to do human, creative work - then that kind of creativity and humanity and connection is a kind of work that does not have diminishing returns, it has increasing returns! On social media? Sure! That sounds incredible. Let's get to work on that - let's be thinking about both the freedom of automating efficiencies and the wide world of creativity thus enabled.
- Customer service - In five to ten years, it will probably be customary to have AI deployed against your concerns raised on social media. That's already begun. It sounds like it would have diminishing returns at a certain point as well.
Who to Watch
By analyzing tens of thousands of connections between subject matter experts and thought leaders in both AI and social media, on Twiter, we attempted to find a list of respected social media thought leaders who appear to be paying particularly close attention to AI thought leaders online. Watch them and you may be one of the first to know about new developments and opportunities at this very important intersection.
Unfortunately, the data here is really light. Here are four people that stand out above the rest of the 1000 social media thought leaders we analyzed.
Marshall KirkpatrickThat's me. I'm paying attention to more AI specialists than any of the other social media influencers we analyzed. I was as surprised to see that as you are. Maybe that's why I started this blog post series. I watch AI specialists and I stretch my non-technical brain to try to see what new developments in AI might mean. I find it very inspiring.
IBM omni-channel marketer Amber Armstrong is paying attention to the field. Not just to Watson, either. In fact, in January 2015 she said she didn't think of Watson as AI. ("It's cognitive learning - not AI in my perspective. It learns, not remembers," she told IT curmudgeon Ben Tremblay.)
Tamara McCleary (right) is a speaker and brand consultant focused on B2B technology. She's very accessible. She's very active online. She works with companies like IBM, Verizon, Dynamic Signal and more. She's following a number of deep AI influencers - and not just the type who everybody follows and follow everyone back. She follows people like Stanford professor and Coursera co-founder Daphne Koller and Singularity Hub, for example.
That's about it.
All the other "social media influencers" who are following a handful of AI specialists seem to just be doing mass follow-unfollow campaigns, and there's not much there there.
And how about the rest of the social media world starts paying more attention to AI? There's a world of potential there.
Our industry's thinkers run the risk of being left out in the cold.
This intersection of technologies is just one of 30 different intersections with AI that we're analyzing in our 30 days of AI series. The future is coming on fast and one of the best ways to be prepared is to watch the intersections!