Next week, I’ll be at the Social Business Forum. I’m looking forward to meeting up again with the innovative folks at Open Knowledge. The conference itself is focused on social learning and the social enterprise. The conference organizers have pulled together an excellent series of interviews with speakers.
After reviewing the speaker list and general details of the conference, I’m afraid I’ll be the black sheep (or idiot) of the conference. The next stages of human intelligence development will likely not be social. We have, I think, hit a type of peak social where social connectedness is diminishing as a mechanism for managing complexity and uncertainty. As detailed in my conference interview, we need to see the social enterprise in a context. Becoming social is lovely as are all the other good fuzzy feelings that are associated with the word “social”. However, if the goal of an organization is to make sense of complexity in order to act meaningfully in the pursuit of goals, then we need to look beyond social mechanisms.
As information foragers (Miller called us “informavores”), people need better tools and technologies to make sense of complexity. We need better analytics that can reveal patterns and connections in information abundance that we may have missed. We need technologies that can automatically detect and raise the profile of interesting patterns within an information stream. For example, crisis situations such as stock market crash, terrorist attacks, or nuclear meltdown provide “event centered pattern recognition”; e.g. after the event has occurred, we can see how all of the pieces fit together and wonder how we could have missed it. An event collapses the information trail into a state of patterns that seem obvious.
Given the flow of data – and that most data now produced will not be seen or processed by humans – making sense of complexity and abundance requires that we begin to think not only in social networks, but more broadly in technologically-mediated information networks where pattern and trend identification is not exclusively human-based. We are in a brief social bubble, partly driven by the desire to push back against the dehumanizing experiences many of us feel with technology, artificial intelligence, and machine learning. The real change, however, is not in the social enterprise. It’s in the human/computer sensemaking and analytics systems that allow people (and organizations) to orient themselves to complexity and gain coherence in fragmented information settings.