Artificial Intelligence Intersects with Social Media
In his fifteenth post in the series, Marshall Kirkpatrick focuses on the intersection between artificial intelligence and social media. By way of reminder, Marshall launched a 30 day series that explores the intersection between AI and the various innovation components on my emerging futures visual.
As he has in each post, Marshall identifies the key subject matter experts that sit at the intersection of AI and the visual component in question. In the case of social media, the key influencers are: Marshall Kirkpatrick, Tamara McCleary, and Amber Armstrong. Here is the foresight and related future scenarios identified at the intersection of Artificial Intelligence and social media (taken straight from Marshall’s post):
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 receive 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 wondrous, 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.
My Take: I focused on the social component of the emerging third platform in a transformation series which you can find Here. My view then and now is that Social is the most misunderstood member of the digital family, and could explain why Marshall had trouble finding thought leaders focused on this intersection. There is still too much emphasis on Facebook, Twitter, LinkedIn, and other social networks, as opposed to viewing social as a critical component of future systems of engagement. As these systems emerge, they will do so across three ecosystems: customer, employee and external stakeholder. Social technology — not social media — represents the most effective communication, collaboration, and coordination platform available to us. When you consider the collective intelligence that is spawned by these platforms, it is easy to see how impactful the intersection with artificial intelligence will be. We are evolving from a focus on customer experience to one of life experience. The interaction that occurs at the edge of these emerging platforms enable those experiences. Edge effectiveness is therefore critical to every future interaction. So the most impactful scenario that I see at the intersection of artificial intelligence and Social is the enabling of edge effectiveness.
The intersection analysis that Marshall pursues via his posts is a great example of deriving the foresight required to navigate in this emerging future. Future thinking — the rehearsal of our emerging future — is increasingly a critical but complex piece of the equation going forward. The other posts in the series on AI and intersections can be found via the links below:
Originally published at frankdiana.net on September 1, 2016.