Getting Past Uncertainty
The Fair Use analysis in Field v. Google was an
excellent synthesis of the analyses that had preceded it.
In fact, the heuristics have been so well developed and articulated, that one may optimisitically
posit that we are on the way to achieving mathematical certainty in fair use analyses.
Why is this a cool thing? Because fair use has been such a minefield of subjectivity,
it has had a chilling effect on its use. People are wary of undertaking ventures based
on the invocation of an unquantifiable defense. In an effort to break through the fog of
uncertainty, we have attempted to capture Field in code. The
Fair Use Visualizer was constructed from the heuristics articulated in Field.
The image above shows the analysis of the four factors as a linear equation. However, as we look to Field, we see that
the weighting of the factors is much more nuanced. Consequently, we'll go through each factor and determine which rules
and weight should be applied given the heuristic we get from Field.
The Factors -
Extracting the Rules
The 1st heuristic is that no one factor is dispositive.
In accord with the 1st rule, the analyzer will be constrained so that no one factor can determine the outcome without some inputs,
however weighted, from the other factors.
Given that we have four factors, the first impulse is to add the four up and divide by four. But are certain factors more
important than others? In the Naked Gun case, the Court found that the
first factor was the most important. In the 2 Live Crew case, the Court decided that
the first factor, and whether the use was transformative or not, are the most important issues. In another case involving the
publication of a portion of Gerald Ford's memior in the Nation before the book was release, the Court found that the fourth
factor was the most important.
The 2nd heuristic is that the first and fourth factors have the greatest weight.
In accord with the 2nd rule, each of the four factors will be weighted as follows:
- Factor 1 - 35%
- Factor 2 - 10%
- Factor 3 - 10%
- Factor 4 - 35%
Factor 1 consists of three subfactors:
- Subfactor 1 - Use
- Subfactor 2 - Purpose
- Subfactor 3 - Transformation
The Court noted that when a use is found to be transformative, Subfactor 1 pertaining to the context of the
use of the copyrighted work (non-profit use traditionally being favored over commercial for-profit use) becomes
less important in analyzing the first fair use factor.
The 3rd heuristic is that when a use is found to be transformative, the "commercial" nature of the
use is of less importance in analyzing the first fair use factor.
In accord with the 3rd rule, if Transform > 50% then Use = Use/2.
The 4th heuristic is that the more transformative the work, the less important will be the other factors.
In accord with the 4th rule, if Transform > 50% then (F2, F3, F4 = (F2, F3, F4) / (Transform*2/100)
The 5th heuristic is that if the use is transformative, Factor 2 is not terribly significant in the overall fair use balancing.
In accord with the 5th rule, if Transform > 50% then Factor2 = Factor2/2
The Court noted that copying entire works will not weigh against a fair use finding where the new use serves a different function
from the original, and the original can be veiwed free (like TV). The extent of permissible copying varies with the purpose
and character of use. If the secondary user only copies as much as is necessary for his or her intended use, the this factor
will not weigh against the use.
The sixth heuristic is that when a use is transformative, and can otherwise be viewed free of charge,
Factor 3 will be neutral even if all of work is copied.
Factor 5 -
In addition to the four part test, the Court threw in a ‘Good Faith’ fifth factor.
The Court noted that the Copyright Act authorizes courts to consider other factors than the
four non-exclusive factors typically referenced. In this case, the Court considered whether
Google operated its cache in good faith, and finding that it did, awarded Google bonus fair use points.
Here is the Source Code that was generated from extracting the heuristics from the Field case
and mapping them to an interactive visualizer.