Instrumented Interconnecteds Intelligent

Thomas Malone, Prof. MIT

Thomas Malone, Prof. MIT

Thomas Malone, director of the MIT Center for Collective Intelligence,  is one of the leading thinkers in the realm of anticipating how new technologies will transform the way work is done and leaders lead. His 2004 book, The Future of Work: How the New Order of Business Will Shape Your Organization, Your Management Style, and Your Life, helped thousands of executives and would-be executives see their organizations, and themselves, in startling new ways. As a result, many organizations are becoming more collaborative and democratic. Now, Malone is exploring how social business, data analytics and cognitive computing will transform organizations once again. Here, he talks about the revolution that is coming.

IBM: In your book The Future of Work, you talked about society being on the verge of a new world of work, a key element of which is decentralization of the organization. Since then, the social networking phenomenon has emerged and is sweeping not just popular culture but business organizations as well. How has this explosion of social networking affected your thinking?

Malone: Social networking is a good example of the kind of thing I was talking about in my book when I talked about how the cost of communication was decreasing. At the time I wrote the book, people were looking at e-mail and the Web. But since the book was written, there are these new ways of communicating electronically–Twitter, Facebook, et cetera. I think those are all excellent examples of the same underlying phenomena.

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As information technology reduces the cost of communication, it becomes much easier for lots more people to know lots more things and in many cases they’re able to be well enough informed to make more decisions for themselves instead of just following orders from somebody above them in a hierarchy.

Today, the vast majority of the kinds of computing that are useful to us are various forms of helping us to connect with other people. In the case of email or Facebook or Twitter, that’s more or less a direct communication. In the case of something like Google, the computational intelligence is helping to find the other people or more precisely, the information other people have created. The computing itself is still primarily as a way of connecting us to other people or things they have produced.

We’re still in the fairly early stages, but in the future computers will increasingly be able to help take actions on our behalf, not just give us information. It’s certainly possible in principle and becoming more possible in practice to have computational intelligence–to do things like what intelligent humans would do or in some cases even things that humans couldn’t do.

IBM’s Watson is the poster child now for this other way of using information technology. This new technology hasn’t yet had a profound influence in our economy and our society, but there are very intriguing possibilities for how the computational use of computing will become more important.

IBM:  In The Future of Work, one of your key concepts was decentralization of organizations. Now you’re using a different term, collective intelligence, and it looks like there’s been an evolution in your thinking.

Malone: After I finished The Future of Work and spent about two years talking about it, I decided to think about what’s coming next—what’s around the corner that we don’t see clearly yet. I became convinced that the perspective of collective intelligence was a very useful way of thinking about that. We’re no longer thinking about today’s organizations and how they’re going to change. Instead, we’re talking about the goal of having intelligent organizations and thinking about how that can occur in new ways with these new technologies. One of our core research questions at our MIT Center for Collective Intelligence is, “How can people and computers be connected so that collectively they act more intelligently than any person, group or computer has ever done before?” It’s a very provocative question that leads us in new directions—pointing to very different organizations than we have today.

IBM:   You’re saying it’s not man-versus-machine, but man working together with the machine.

Malone: Exactly right. I think man-versus-machine is in some ways the traditional way of looking at this question, but I think where we’re really headed towards man-plus-machine. In fact, just a couple of days ago, I came across a quote from J.C.R.  Licklider, the computing pioneer, from 1960. He said, “In not too many years, human brains and computing machines will be coupled together very tightly,” and “the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.” So the combination of people and computers will be able to think in a way that neither people nor computers have ever done before. I think that’s the really exciting potential and opportunity for us ahead.

IBM: What are the opportunities and challenges that this shift creates for top managers?

Malone: I think new information technologies give us opportunities to organize work in new ways, and to create new types of organizations. And I think some of the most important things that top managers can do is figure out how to take advantage of that.

In the traditional industrial organizations, one of the most important ways of measuring the effectiveness of an organization was in terms of its productivity. How much output did you produce for a given amount of input? In our fast-changing world where innovation and adaptation are more and more the critical success factors, another increasingly important measure of the effectiveness of an organization is not just how productive it is but how intelligent it is. Intelligent organizations will be better able to adapt rapidly to changes in their environment, better able to innovatively take advantage of new possibilities, better able to be flexible and sense and respond to the world and not just do more efficiently what worked yesterday.

For managers, one of the important challenges is going to be dealing with power. These shifts that are coming will in many cases diminish the traditional kinds of power for top managers. That goes back to one of the key messages of The Future of Work. In many parts of our economy, the best way to be economically successful is to give a lot more power to a lot more people throughout the organization. That means top managers will have less of the traditional kind of command and control power we used to think of as central in their jobs. For some managers, that will be a challenge.

One of the paradoxes I talk about in The Future of Work is what I call the paradox of power:  Sometimes the best way to gain power is to give it away. Think of people like Linus Torvalds (the creator and coordinator of the Linux operating system), who gave power away to programmers all over the world and in a certain sense gained a different kind of power from doing that. Or think of Pierre Omidyar, the founder of eBay, who gave power away to customers but gained another kind of power from doing so. That’s a paradox but also a real opportunity. These new technologies provide new ways of giving people the information and incentives they need to do the right things with that power.

If you have a way of telling how much everybody in the organization is contributing to the bottom line of the company, you don’t necessarily have to tell them what to do, just let them figure out how they can contribute the most to bottom line of the company. Of course, that’s not always easy to measure, but I think one opportunity is to find more and more ways to get closer and closer to doing that.

You need to create organizations where people have the right kinds of connections and the right kinds of incentives to make decisions for themselves. But the leader also has to lay out a goal and a vision of where they want the organization to end up. Then people understand the broad goal, they can interpret for themselves and in their own situation how to help the company get there—often in very interesting and innovative ways. If you try to tell them what to do more precisely, you would not give them that scope for innovation and therefore you often get less of what you ultimately want.




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Hi Steve,
In response to the Thomas Mallone interview… A question arises about the future of work in the context of what makes an organization “intelligent”? I would posit that it has a great deal to do with the ability to learn; ergo, an intelligent organization is really a learning organization at its roots. And in this regard, it’s only been recently (within the past 25-30 years) that there’s been much progress made in the machine learning category. Heretofore, all the learning that was occurring was on the human dimension. Currently, and likely well into the foreseeable future, the technologies underlying machine learning are are evolving at a rapid pace. So much so, that machines are beginning to manifest an ability to learn that mimics human learning at a very basic level. How far, how fast, and with what degree of efficacy this on-going r/evolution will proceed remains to be seen.

Based on past experiences with the evolution of intelligent systems and their subsequent integration into a viable socioeconomic context, I’m a bit leery about the pace at which this phenomenon will proceed. Here’s why… Back in the mid-80′s and early 90′s I became involved with a company that specialized in the design and development of real-time, intelligent systems (RTIS). The methods/tools/techniques involved were unique and demonstrated a capacity to perform at levels far greater than anything might be developed using state of the market programming methods of the time (i.e., C++). At the heart of each such an RTIS architecture was a distributed rules engine that operated at lightening speed. This technology was so good it could serve as fighter pilot’s “co-pilot” and assist with making real-time, mission-critical decisions – based on a continuous stream of in-coming situational data. It represented a quantum leap in man-machine integration and offered any company/organization possessing the wherewithal to make use of it a breakaway opportunity.

So, why did the company that developed this technological capability ultimately change its name and ultimately limit its market to the logistics and warehousing arena? My best guess has a great deal to do with a lack of imagination and willingness to take a risk on a commercially unproven (not undemonstrated)technology. It also might have had a great deal to do with inertia; that is the tendency of the market to continue do what it has been doing in the past until acted upon by a sufficiently counteracting force. And this adoption resistance remained steadfast in spite of the fact that in any rules-based system, the number of unidentified and uncorrected code bugs increases exponentially as the number of rules increases. And in systems where the number of rules could approach and even exceed 10K rules, the problem of control both bugs and costs increased dramatically. [Note: One of the features that this RTIS technology different/better had to do with the ability it gave to the developers to find and correct any such bugs during the development process.]

That said, it will be interesting to observe the speed with with IBM’s Watson-technology is evolved and commercialized. Also, whether this technology represents the state-of-the-market in machine learning – and machine intelligence – I can’t say. What I can say with some degree of confidence is that the greater of two challenges in realizing Mallone’s vision for the future of work is likely to be on the human side of the equation. That is, getting humans to adopt and adapt to intelligent co-working machines. Just remember what happened with the computer integrated manufacturing (CIM) challenge industry faced during the late 80′s and early 90′s. Where are the bulk of manufacturing jobs today?

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