I have recently been developing our Intention Broadcasting (IB) concept into something approaching a more fully-fledged theory. My first objective was to come up with a model of how an intention broadcasting system (IBS) should work in a general sense. The second was to identify existing and future implementations of IBS-based services.
I initially studied some Situated Cognition theory to see if there were useful correlations and, out of the key principles, the following were of particular interest: affordances, problem solving, goals and intentions. And The Young-Barab Model (1998) of Dynamics of Intentions and Intentional Dynamics.
In any environment there are different kinds of affordances (possibilities for action) that allow us to carry out intentions to achieve certain goals. However, the process of reaching these goals is hindered by contextual problems that can only be solved on the fly and through interaction with the real world.
Intention Broadcast Systems – Key Phases
The key phases that I have identified in the dynamics of an IBS are as follows:
Intention: the agent has an intention to do something
Goal Adoption: agent sets out on a particular path to achieve the intended goal
Affordances: agent adopts an IBS as the best method of achieving intended goal
Broadcast Transmission*: agent passively broadcasts intention to target audience (avoiding multiple intrusive communications)
Reception: the target audiences tune into to receive relevant intention via streams (channels, groups, etc)
Censorship: a collaborative rating system is often required to help protect both the broadcaster and audience from bad intentions.
Coordination: systems for involved parties to overcome contextual problems though interaction and collaboration.
Outcome: Goal accomplished
*Ideally the target audience would all be actively using the service and receive the message passively or through system-based notifications; however, in the real world some people will need to be contacted via more conventional methods, eg – SMS & email; however, the IBS can at least automate the sending and collating of the messages and their responses.
First Sketch Comparing Conventional Strategies with the Dynamics of an Intention Broadcasting Model
The sketch above shows an example of how intention broadcasting is much better at solving some real-world problems. In this instance I have chosen to use organizing a get-together as an example, however, I will later go on to explain how it can work in other situations.
Agents A & B both intend to have a party and they adopt this as their Goal:
Agent A goes conventional and uses a combination of affordances (calling, SMSing and emailing) to let the audience (friends) know that he is planning (intends) to have a party. All these methods are intrusive and can make the receiver feel under pressure. The replies have to be manually collated, adjustments made, and updates sent multiple times. This is a laborious process and Agent A will eventually succeed in concluding the situation or the frustration will become overwhelming and the goal abandoned.
Agent B, however, opts to use the Zipiko intention broadcasting system. Agent B broadcasts the intention to have a party and her Zipiko friends can passively see the plan on the listings page and click to join. Friends can also be sent free SMS invites, even if they are not registered on the system. The system then automatically and instantly updates attendees on who is coming, sends reminders and informs about cancellations. Using the Event Messaging Board collaborative adjustments can be made right up to the last-minute.
So the benefits are clear, however, if a theory is to be successful it has to be proven to work in many different contexts.
INTENTION BROADCASTING IN THE REAL WORLD
IB systems can utilize any method of one-to-many combined with one-to-one ICT broadcasting strategies and almost any situation where you can define a clean intent/desire/need you can build an IBS to help out. And already aspects of intention broadcasting are appearing on the web. Here are some current examples:
Travel: Dopplr allows you to broadcast your intention to travel to a particular destination so that friends and colleagues can know where you are and 'serendipitously' meet up with you.
Real Estate: Igglo enables potential customers to broadcast their intention to live in a particular neighbourhood or even block and attempts to match the desire. Also, potential sellers can advertise their intention to sell their property (secret selling) in order to gauge the real market value; and if they see an offer then can’t refuse then all the better.
By shear chance both these services have also been developed in Finland. Finns are famous for not talking so maybe this more passive way of communicating is appealing to them ; )
Micro-lending and Peer-to-Peer Banking: Kiva.org is an organization that provides micro-lending to entrepreneurs around the globe. The entrepreneur will post (broadcast) how much they need and what the loan is for (generally from $250 to $500); you can select (tune into) the person, gender, country, type of business and elect to assist this person. Could this phenomomen could spread to conventional banking.
(Note: I am aware that there is a Finnish organization also involved in micro-lending but can't remember the name. If you know please add it to the comments).
In light of our open attitude (see previous entry) you will now be privileged to read, for the first time, about some complete IB-systems currently being concepted during Zipipop's 10% time. We reserve all rights to implement any of these ideas and if any financiers are interested in helping us we are all ears:
Buying/Selling (project codename: Share Swap): The customer broadcasts an intention to buy a product (either new or second-hand). Sellers see this intention and make direct offers. Buyers benefit in having to do no legwork, can see and compare offers in one place, and get more open independent expert advice.
Sellers benefit from the direct contact to active customers, a better understanding of customer needs, and save money on inefficient, and often unwelcome, general marketing. Both benefit from the collaborative feedback censorship system that rates people (as in Ebay); and transactions can easily be resolved in the coordination phase.
This can also be used to buy/sell trade or consultancy freelance work, eg – people always need skilled labour and organizations often need freelance work, but it is not always clear who to contact or what is a fair price. So they could broadcast their need for some freelance work. Freelancers could then tune into (via channels, groups, etc) the offers that are best suited to them. And the censorship filter helps customers avoid the cowboys (British slang for incompetent workers).
(13/09/08 - Check out for freecycle.org)
Personal Opinion Polls (codenamed: POPs): You intend to do something but you want feedback before doing so, eg – you want your friends to advise on which wedding dress you should buy; or which guy you should date.
The need for this kind of service is just starting to express itself on micro-blogging services. See here for an example.
Baby-sitting (codename Baby-sitting Project): Broadcast your need (intention for finding) a babysitter. Use the collaborative censorship rating to evaluate trustworthiness.
In fact, I have been playing with the concept of an Intention Exchange System that could encompass many IB needs in one service: like a stock exchange but with the trading based on intentions. Interested bodies could tune into all the different kinds of broadcasted intentions that are relevant to them and make offers. The exchange could be facilitated by swapping items/services of similar value, system credits (that could be exchangeable for real money), or via real world credit systems, eg – Paypal, etc.
(Relevant Off-Topic Sidetrack: Many years ago, when I was in the film business, I remember reading about a young filmmaker who had been touring his award-winning film around the world for a year. He consider the period his reward for all the hard work, but, just when he was getting all the attention and offers of more financing, he suddenly realized he could not answer the "What next?" questions that were flying at him. We are sure that Zipiko is going to be a big hit, and, therefore, we are already preparing to make the most of the opportunities this will bring our way; however, we are fully aware of the tremendous concentration of will and effort still required for many years to come to take Zipiko to where we want it to be.)
FINE TUNING THE WEB
So we can see a familiar pattern arising that can affect huge sections of web activity. IB essentially farms out (crowdsources) the work of searching for things on the web by matching needs with solutions in a much more efficient manner.
As I have demonstrated, aspects of intention broadcasting have been developing in a fragmented way for a while, however, with this new model it is now easier to identify and develop fully functioning IB systems. The next stage is to see how IB fits into the bigger picture regarding the emerging practices related to the semantic and pragmatic web.
And then that little question of making sure that 'ordinary' everyday people see the benefits and make the switch to such systems.
Zipiko will be the first full-on 'proof of the pudding'.