What Enterprise Could Learn From AI Research History

By Thierry de Baillon

This might look like quite an academic title, but heaven knows how little academic I am! I was for a long time interested in AI as a way to use computers to something else than deterministically crunching data, and, as I worked on my last post, was struck by important analogies between key turn points in Artificial Intelligence history and our attempts to define and set up the early stages of the intelligent organization: the so-called Enterprise 2.0.

From processes to networks

Once the first dreams and myths vanished, AI research began to focus on two different subjects: manipulation of abstract symbols and contextual understanding (notably vision and natural language comprehension), and resolution of practical problems. That is, dealing with knowledge and information to take decisions, and ultimately act accordingly. During the late seventies, this field of research took off with the development of expert systems, which computed given information into a large set of rules (the expert knowledge) to trigger practical decisions. The main problem expert systems encountered were the necessity to deal with ever growing massive knowledge databases, and the difficulty to maintain this knowledge current. This approach reminds me a lot the way decisions are taken in our process-driven companies.

To address the enormous amount of necessary computation, researchers began to introduce computational shortcuts such as heuristics to bypass some portions of those huge knowledge trees. It is more than interesting to compare this with our attempts to introduce web 2.0 tools and practices inside business processes to give them more flexibility and efficiency.

Publication, in 1982, of Neural networks and physical systems with emergent collective computational abilities, by John Hopfield, was a breakthrough. The physicist proved that a certain form of networks was able to achieve the same results than rules-based systems. Instead of using databases, Hopfield nets stored it into weighted connections as they learned new patterns of distributed knowledge, and inferred decisions based on the output of the network.

Weights and convergence

The analogy itself between neural networks and a real community-based company is striking, and so are the similarities between the limitations of this approach and some Enterprise 2.0 concerns. Neural networks encountered two big problems: relevancy and convergence (they couldn’t ensure to converge onto the desired pattern, and sophisticated training techniques, such as back-propagation, were necessary to ensure convergence). Social media are facing the very same problems in the enterprise: how could we ensure that communities lead to the right consensus for applicable decisions to be taken? I evoked some possible trails in my last post, and this is a crucial point.

To push the analogy a bit further, the way connections were weighted inside neural networks might give us another path to follow: we might similarly “weight” conversations in social media to facilitate the rise of consensus. Such a system already exists on the Social Web, but is presently mostly a number game, people with more friends and followers are the most listened to, and the most influential. We cannot deal with the limitations of such a system in a professional context and need to look forward for better ways to weight authority and expertise there…

Further advances: micro-processes

The historical analogy stops there, as Artificial Intelligence kept on evolving from these paradigms. Most significantly, from explicit, the logical engines which process information went implicit, completed with a hybrid, “embodied”, approach, where physical captors capture perceptions from the environment: the intelligent agents.

Should, and will, the Enterprise 2.0 follow the same track as AI did? If so, next move would be to get rid of the big business processes we all know, and replace them with micro-processes applicable at individual scale. For instance, the way Japanese coworkers are able to make a consensus emerge from community-based workshops, one of the pre-requisite of Kaizen, rely on their heavy sense of “doing the right thing”. To set up such micro-processes is a radical move from where we are and where the most daring organizations try to go, and would only be possible with intensive education, and a strong commitment from HR and management. Whichever future we might predict to Enterprise 2.0, most underlying concepts are still in their infancy.

Enterprise 2.0, Social Media and the Sacred Trilogy

By Thierry de Baillon

Social Media is more about information management (links) than about knowledge (nodes). And business is neither about information nor knowledge management, but about decision taking. The absence of the decision dimension in most attempts to introduce Social Media into business might be a major cause of failure.

Information as a superstructure of knowledge

Knowledge management is a hot topic for a long time in the corporate world, and introduction of  Web 2.0 technologies have shifted the debate, merely to dynamic knowledge acquisition and retrieval. But, as social media are pollinating other activities of the enterprise, is this approach still totally relevant? And alternative would be to distinguish between knowledge management as a more or less “static” preoccupation, and information management as the way to access, qualify or propagate the knowledge. Think of information as the fluid which connects knowledge to people, and people to coworkers and clients, and you’ll get a good definition of what social media integration should be.

But, unless – or even if – you run a PR, advertising or media company, managing information is not the core of your business. Taking decisions is. Most of corporate activities are headed toward making decisions applicable, in a way or another. The processes our modern companies are ridden with were setup to facilitate and industrialize decision taking. Information, and knowledge, are harnessed to help triggering the right decision at the right moment. Enterprise 2.0 is not about letting information flows freely among happy communities, but is about re-designing businesses in order to integrate communities into every step of decision taking.

Dealing with the knowledge-information-decision trilogy

Reaching such a goal is far from obvious. I recently wrote that our processes driven businesses do not fit the necessary organic nature of Enterprise 2.0, and Paula Thornton, from FastForward blog, commented that the challenge of a communities-driven business would be raising consensus to allow for the necessary decision taking. While successful at transforming marketing and customers services, social media seem unable to help companies manage any but the smallest projects. Why?

From a trilogy (knowledge, information and decision) point of view, the way the three different “bricks” of business are arranged and dealt with may help us getting an answer.

Departments which are the most successful at Social Media integration are, by far, Marketing and Customers Service. If we take a closer look, we can see that in both case, decisions are not part of the process, and were mostly already taken. Both then use knowledge to leverage information they get or push. In the Customer Service case, decisions still to be taken are made on an individual basis, without a need for consensus or larger scale decision.

Small projects and focused communities management is usually another successful use in companies. In that case too, necessary decisions (goal, methodology) are taken before anything, and the main goal usually involves growing the knowledge through information.

Larger scale projects, which may involve a company-wide social network, or free experimentation with unfocused tools, may also work as long as nobody expects some impact on business with those. They might be seen as an evolution of Knowledge Management, but certainly not as a real move toward Enterprise 2.0, since we lack getting business decisions taken from them. In that case, decision means and only means sponsorship from the C-level.

Paving the future

As long as we are unable to deal efficiently with the “decision taking” side of the sacred trilogy through social media and communities, we won’t be able to change key departments of companies (production, manufacturing, quality, management,… ), and we will have to stick to rigid processes. To go any further, not only do we need a cultural shift, we also need new tools.

As fast as things evolve, I see two different ways the future might be brighter.

• The rise of social CRMs
  Social CRM is quite a fuzzy concept, but expect new solutions to be not only geared toward monitoring the social space, but to infer decisions from it. A logical step would be to apply to the internal world what will be available for the Social Web.
  Existing Enterprise Platforms are also beginning to implement such modules, like Telligent’s Harvest or Jive’s Insights.

• Social Media is cultural
  As I recently wrote, the way Occidental companies deal with decision taking is in essence different with Oriental approach. Our processes are born from an attempt to adapt Japanese kaizen concepts. Today, most Social platforms and services are Anglo-Saxon. With other parts of the world leveraging their online presence, we might see new tools developed with different cultural processes in mind.

This was quite a long post, with some subjects worth extra development. I would love to hear your opinion about it.