Fuzzy Logic and the New Membership Model

Fuzzy Logic and the New Membership Model

Earlier this year, Google featured a doodle on its homepage commemorating Lofti Zadeh, the creator of ‘Fuzzy Logic’, and his contributions to improvements in the ability of computer-generated solutions to solve real-world problems. Fuzzy logic is an approach to computing based on “degrees of truth” rather than the usual “true or false” (1 or 0) Boolean logic, which took its name from George Boolean, the mathematician, best known for creating the algebra which laid the foundations for computing and the information age.

Professor Zadeh first advanced his theory at the University of California at Berkeley in the 1960s. He was working on the problem of computer understanding of ‘natural’ language, the type of reasoning we commonly use as we consider and ‘solve’ problems, which is not easily translated into the absolute terms of 0 and 1. Fuzzy Logic is a way of approximating the way our human reasoning really works, while Boolean, or binary logic, is a more artificial categorization of individual choices we make as part of a sequence or series of decision-making steps.

Applying Fuzzy Logic

Fuzzy Logic was, and has been, applied to a wide variety of solutions, which have revolutionized and improved any number of applications, conditions and experiences. Take the example of a computer-controlled public transportation system, such as a subway. Prior to the application of Fuzzy Logic, computer-controlled systems were notoriously awkward in terms of how the cars would be programmed to accelerate, decelerate and stop – often lurching passengers each time one of these actions was initiated.

By using Fuzzy Logic, programmers were able to more closely recreate the ability of human operators (who had learned, through experience, various tactics) to ease the vehicles into and out of acceleration and to brake more evenly. Very simplistically stated, this may have simply recreated the fact that the human operator, at times, might have engaged, both the accelerator, and the brake (very lightly), at the same time, to begin deceleration, rather than suddenly releasing the accelerator and abruptly engaging the brake, as one would, in a binary condition of a 0 – 1 (accelerator off – brake on).

How does this relate to Membership?

Well, at this point, we have to ‘remember’ that the word ‘membership’, while we think of it usually as referring to a person, simply means to be a part of something. In that sense, while people can be part of a group, of course, so too, numbers can be part of a set.  This is generally expressed as follows A = { 1 , 2 , 3 , 4 } which means the numbers 1 through 4 are all part of (or members of) the set, or group A.

Professor Zadeh approached the limitations of Boolean logic (on-off, or 0-1) which would suggest either something is right or wrong, or true or not-true, by working out a way of thinking and computing that allowed for the notion of degrees of ‘truth’ or degrees of ‘correctness’. Another way of thinking about this, in human terms, is to say, instead of things simply being black or white, that there are areas of grey, in between, and considering all the members of the set Grey, bounded by the absolutes Black and White, at either end of the spectrum.

Degrees of Membership

Here’s where we can begin to see the application of ‘fuzzy’, as in something that is not clearly perceived or understood, but rather, more vague, and imprecise, and yet, still related to the set of things under examination or consideration.

In human terms, and in the context of Association Membership, for example, we may, in the past, have fallen into the practice of either considering a person to be a Member (1) or Non-Member (0). Fuzzy Logic encourages us, or allows us at least, to consider ‘degrees’ of membership, or conversely, degrees of non-membership.

Here’s how I work that out. Let’s say, for sake of argument, that we accept that Membership, in our set, or frame of reference, is bounded by 0 and 1. Using a fuzzier approach, we then stop to consider the question, can someone be a 0.1 member, or a 0.5 member, or a 0.9 member, before they become a full-fledged 1.0 member? The answer is Yes.

Thinking about Membership in a newer way

These days, we appreciate, in the Membership – Association world, the value of engagement. That is, if someone ‘engages’ with us, in some (small) way, we see that as positive. For example, if someone simply lands on your home page and stays there for a number of seconds, or minutes, and, perhaps, clicks on something, that represents some aspect of engagement.

If we broaden our sense of Membership to include degrees of Engagement, we may be able to take a different approach to Membership Development. Staying with the example above, we might call someone who simply landed on our homepage and clicked through a link to an article, as a 0.1 member. They are definitely not a 1.0 member, but they are also, by virtue of their activity, not a 0.0 member either. They have interacted with us.

The example continues. What if the person, having come to the page, or back to the home page, and, having clicked through again, either in the same or different place, then filled out a subscription form, provided their email address, and was automatically included in our notification list. Could we call that person a 0.5 member? Not quite a member, but certainly on their road to possible full-fledged (1.0) Membership?

We might even imagine a scenario, where we broaden our fuzzy membership set to include the numbers 1.5 and 2.0. How so? Well, let’s say someone has officially joined our Association (1.0) perhaps as defined by paying a fee, and then responded to a favourable (member-only) offer to a service or services, available to 1.0 (paying) members, say for access to an insider briefing or exclusive seminar. We could then categorize that membership at 1.5. In other words, a higher value than simply 1.0, given that, not only are they a member, but that they are actually something more than a member, an exclusive-service member eligible for exclusive benefits above and beyond that of a 1.0 member.

Using a Fuzzy Membership Model to Generate Income and Membership

Using our imagination, and new ways of thinking about monetizing engagement, as part of our membership model, we can certainly see the opportunity to generate ‘audience’ ratings for use with sponsors and advertisers on our site, for example. So, a 0.1 member, that is a person who simply landed on, and engaged with, your site, provides a value to your organization. A 0.5 member, one who actually subscribed for notifications, is more engaged than the 0.1 member, and provides, correspondingly, more value to your audience engagement and development. And so on.

Perhaps, most importantly, the ability to recognize degrees of membership, encourages our own creativity in monetizing engagement, and, eventually, attracting people to increasing degrees of membership, with the goal of reaching our highest measures (and whatever value we assign to that score) of membership.

With ‘Engagement’, as in the ability to attract and hold attention, and then dialogue with, if not influence, a person, so incredibly valuable in today’s distracted and disengaged universe, we owe it to ourselves to think of, and through, the possibilities, that Fuzzy Logic, and Fuzzy Membership Models, might lend to our goal of Association Development.

Paul McKay

Paul McKay is Senior Advisor with McKay Associates. Feel free to get in touch with Paul through LinkedIn

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