Finding the Perfect Match
Summary: In order to promote more efficient licensing systems for content, the industry needs to encourage the development of standardized contracting languages, as well as experimentation with code-based smart contracts.
There’s a moment in the new play Privacy, written by James Graham and currently running at the Public Theater in New York, when the main character, played by Daniel Radcliffe, sits down at a restaurant with the founder of an online dating service, who mentions casually that nearly nine-tenths of the single adults in the United States have tried online dating.
This number surprised me. If correct, this means that a majority of single people in this country now use computer algorithms, operating on data input from each of the individuals who use the service, to find matches. It is by no means a perfect process, of course. What the online dating services really provide is initial matching between candidates who appear compatible — it’s then up to the humans to negotiate the rest. Sometimes it leads to a really awkward few hours in a restaurant, but sometimes it leads to a long-term relationship or even marriage.
Before online dating, finding a match typically required either (a) having friends and relations introduce you to someone you knew you wanted to meet, or to a new person they believed might be a good fit; and/or (b) putting yourself “out there” — mingling a lot, at bars, parties, and other events. It was less efficient and messier (I won’t comment on which approach is more fun).
That’s basically the way business deals have always happened, too: you either identify potential transactional partners and arrange an introduction, or you make it known in the market that you have something to sell or to buy.
The Internet, digitization, and structured databases have made the process of searching out potential business partners easier and more efficient as well. For consumers, eBay is a perfect example of a more efficient network for buying and selling between individuals and small business. For corporations, a good, recent example is Amazon Business.
For Content, A Good Match Remains Hard to Find
In the content industries, however, even with digitization it often remains difficult to identify the owners of rights (this is especially true in the music industry). As we’ve discussed many times on this blog, blockchain technologies may offer solutions for the issue of murky ownership information, which in the context of digital rights is for the most part a metadata issue (although that description oversimplifies things, because in many cases we’ve still got to solve the problem of the underlying bad data, at least for older works, before we can really put this tech to work).
Today, though, I’d like to jump ahead and assume that good systems exist to surface content to people who are looking to license it, and also to surface information about the owners of that content. That is, let’s assume that if I want to secure the rights in a particular song for use in my documentary film, I can do a simple search to find it and identify who owns it and can license rights in it. (In this context, I’m not addressing consumer uses such as streaming, but rather B-to-B and other more complex licensing situations.)
So here’s where it gets interesting. What if the rights holder also could specify certain terms for potential transactions in advance, and make those available as well? And what if the person looking to license the content could specify the kinds of terms that would be acceptable, also in advance?
The term “smart contracts” comes up a lot in this context. As we discussed yesterday, that term has several meanings, depending on who is using it.Here, let’s use the definition of smart contracts that encompasses legal contracts between parties, with some parts of the contract reduced to code. Then let’s further assume that the coded provisions are incorporated onto a blockchain-based system like Ethereum, so that they can essentially become self-executing.
In this scenario, automated systems would determine whether there was an initial match. In some cases, maybe the terms match up so well that there’s complete agreement and a binding contract could self-execute. For others, where there is agreement on key terms, but the need for further negotiation on others, the system would kick out the rest of the transaction to the parties and they could continue to negotiate open terms in the traditional manner.
It gets even more interesting if you imagine that each side could have a range of dynamic options: For instance, if the offered price for use of the song exceeds $X, the term of the license could be an additional 3 months. Someday soon we may even have artificial intelligence agents that we can deputize to negotiate some of these flexible details.
Where We Are Right Now
For the most part, we don’t have these types of systems yet in the content fields. Any automated processes for licensing between arms-length parties typically consist of a take-it-or-leave-it set of terms from the licensor; otherwise, individualized negotiations are the norm.
There are three basic steps needed to take us down this road.
First, we need to standardize and modularize our legal contracts, to enable basic licensing formulations to be reduced to code.
Second, we need the systems that will help find those “initial matches” between licensors and licensees who are set up to engage in (at least partially) automated transactions.
Third, we need to continue to develop and test automated transaction scripts for digital assets, built on distributed ledgers.
The third step actually maybe the easiest, because there are companies already doing this, as we’ve discussed many times on this blog. But I would also suggest that the content industries need to watch very closely, and learn from, the experiences of financial companies that are embracing smart contracts. Data is data, whether it represents monetary value or creative value, and the principals that apply here are similar if not identical. Today, the R3 CEV consortium announced two successful prototypes of smart contract solutions for trade finance — those of us focused on content should be studying results like these intensely.
The second step is also underway, to some extent. There are companies developing systems that will make metadata about content more searchable and available. One trick here, though, is creating interoperability rather than independent platforms that don’t talk to each other.
The first step actually may be the most difficult, because it requires lawyers and business people to rethink how we create contracts, from the ground up. To some extent, it will require lawyers to think more like developers.
For instance, it will require law firms to come up with integrated strategies across practice groups for how to deal with contract drafting. But if we can do so, we can set the table for better coding of transactions that will be backed up by a valid legal framework.
We’re aware of a few efforts to try to enable this type of change by actually building code-friendly approaches to contracts. One effort was summarized recently in a terrific article by Joe Dewey. Another is being advanced by Jim Hazard and others at CommonAccord. There may be others with which we’re not yet familiar.
These are all steps in the right direction. For the content industries, encouraging the development of more standardized and modular contracts will be key. Companies will also need to take stock of their own digital asset management systems and data (for more on this, you might take a look at this video from Ed Klaris), in order to make sure that they have robust platforms that will ultimately allow connecting their own data with the data of others.