ICC Continued

Read this first: ICC

Motivating theory

The base concept motivating the creation of ICC is that data alone has almost no value. It can be trivially copied and distributed at almost no cost. Where the value comes from is the fact that someone organized it, whether by writing, debugging, maintaining, sketching, inking, coloring, modeling, posing, animating, designing, etc. The work comes not in generating the bits that define the file on your computer, but rather by making the decisions that refine those bits into something meaningful.

Donor Reliability Coefficient

In my opinion, the most obvious concern is: if a donor can withhold their donation, what's preventing them from making a very large pledge and not paying after the work is published?

My proposed solution to this is to assign each donor a "reliability coefficient". This metric would roughly predict how likely it is that a given donor will fulfill their pledge based on their past donations.

Lets consider an example: A fraudulent donor made a large pledge for proposal A that they don't intend to pay. I, as an artist, am choosing what to work on, and I see that proposal A has a much higher payout estimate than proposal B, and work on A as a result. Once I release my work, I end up not getting paid nearly as much as I would have for B, which, in this example, has mostly genuine pledges (though I cannot know that at this point in time).

This is where the "donor reliability coefficient" comes in.

One potential formula for this metric is $${C_0 = \frac{D}{P}}$$ where ${C_0}$ is the coefficient, ${D}$ is the sum of a donor's past donations, and ${P}$ is the sum of a donor's past pledges. But alas! If the fraudulent funder has previously fulfilled their pledge with a donation of $0.01, then they have a maximum reliability coefficient, and we're back to square one.

To fix this, let's scale the coefficient by the amount paid: $${C_1 = P\frac{D}{P} = \frac{D^2}{P}}$$ Now, while the fraudulent funder still has an coefficient of 1, a genuine funder who has paid $120 of their proposed $200 over the past 2 years has a coefficient of 72, greatly outshining the fraudulent funder. 72 is a really big number though, and over the course of many years, it could be reasonable for a third donor to spend thousands of dollars total, making their "influence" many orders of magnitude higher than even the donor who has spent $120.

Let's try adding a time scaling factor. $${C_2 = \sum_i e^{-t_i} \frac{D_i^2}{P_i}}$$ where each payment/offering pair is scaled by how recent it was, ${t_i}$ being the amount of time that has passed since payment ${i}$ in months (an arbitrary time unit). Doing some napkin math, it seems like this helps with balancing the influence of long-term donors vs medium-term donors. We could add a few scaling and offset factors here and there, but for the most part, this seems to solve the problem at hand.

It's worth noting that this is definitely not the only solution to the stated problems, and almost certainly not the best! Perhaps it would be worth allowing artists to mess with these formulae and coefficients in order to let them use whatever they believe best predicts payouts.

One last potential issue I want to address is how fund offering amounts scale the coefficient. Someone who has paid $120 over the course of a year suddenly declaring a $2000 fund offering is a bit suspicious, so we should incorporate that into our final calculation somehow. However, I think it's fine to leave the coefficient as it is for now, and figure that out later if it actually becomes a problem.

As it stands now, the donor reliability coefficient roughly maps to the amount of money a donor is likely to provide based on all of their past donations.

The calulation of this coefficient is critical to the functionality of converse crowdfunding, as it is what allows ICC to still work even though donors are allowed to retract their entire pledge after the work is published.

sidenote

As an exercise for the reader, consider the following: a fraudulent artist makes a proposal that they do not plan on fulfilling, and some donors declare pledges. In this example, the artist fraudulently "publishes" a trivial or low-quality work (say, a blank white image file rather than a page of a comic) just to claim the pledges. How can the system be built to minimally punish these donors? It's easy to say that the donors should have been smarter, and should either pay the amount they offered or retract their entire pledge and just take the hit to their reliability coefficient, but ideally, the system should try its best to nullify any incentive that would make the donors want to pay the fraudulent artist. In the long run, this type of fraudulent artist wouldn't last long, but one could easily imagine a washed-up one-hit-wonder artist making one last grand proposal, to which many donors offer pledges, just to run into the above situation where the work is low-quality or nonexistent, intended only to trigger the donation invoice.

Could the donor reliability coefficient be adjusted to mitigate these scenarios? Would it require a totally separate mechanism?

conditional offering

In some cases, it may make sense to offer additional funds if some conditions are met. For example, for a chapter of a comic, there could be bonuses for translation to a different language, or for some color panels.

sub-deliverables

A primary component of incremental converse crowdfunding is for a product offering to be split up into as many smaller parts as reasonably possible. In order to simplify pledging, it should also be possible to donate to a higher-level task, in which case its sub-tasks should trigger a partial donation for the pledge, perhaps weighted based on the significance of each sub-task.

acknowledgement

There should be some way to prove that you helped make a feature happen. Maybe also a percentile metric comparing you to other donors.