Market Efficiencies and Stock Photo Pricing

In my last blog post, Selling Stock: It's About Search Rank, Not Price, I argued that the price variability in the stock photo industry can be exploited by those who garner high search rankings. The rationale is that the direct and indirect cost (overhead) of finding an image so far exceeds typical license fees, that photo buyers are more indifferent to those license fees than sellers believe. Thus well-ranked photo sites would be able to command higher license fees, simply because they have first access to the buyer.

In fact, well-ranked photo websites are undermining their own profitability by lowering prices unnecessarily, mostly because they are following their perceived competitors, not because the customer is demanding lower prices. Their rationale would follow traditional economic theory under most market conditions, but therein lies the exception. The photo industry does not represent "normal economic conditions." Indeed, the photo industry represents a classic case of an "inefficient market."

Let me explain by starting with the definition of an "efficient market." It can be summarized as a market of buyers and sellers engaging under conditions where all information is available to parties on both sides of a transaction. (See this wikipedia link for extended definitions, examples, and citations.)

Examples of efficient markets are exchange-traded commodities like oil, orange juice and automobiles, among others. Here, producers of commodities make their wares generally available, and market-makers trade on this information. It is exceedingly difficult (if not impossible) to have inventory that the market is unaware of, or to purchase commodities without the broader market's awareness. These are the conditions that lead to the definition of an "efficient market."

While there will always be price volatility, it is almost entirely governed by predictions of how supply and demand might be affected by external events. The weather affects the price of Orange Juice; war and instability affects the price of oil; and a litany of factors affect the auto industry.

When it comes to image-licensing, most buyers and sellers do not have that much information about the "global" market of buyers or sellers, let alone access to conditions that can affect future supply and demand. This results in "market inefficiency," which results in price inconsistencies, precisely as predicted by economists. Therefore, prices vary from high to low across the spectrum, depending on the perception of the buyers in any given time/place. This is because they have limited and incomplete information about the global supply chain.

This also explains why people objected to my proposition from my prior article. They do not have access to "all information," and worse, they are unaware that their worldview is limited. That is, most pro photographers are under the illusion that the entire market of stock photos is monopolized by a small number of stock agencies.

Ironically, the other markets (non-agency buyers/sellers) don't see the other side either. These discrete and separate markets will, by definition, find different prices than buyers in other markets. Stock agencies will view one another as competitors and lower their prices, whereas websites that are unaware of stock agencies (or don't attempt to compete with them) will command higher prices.

To optimize prices and create an efficient market, the following would have to take place:

• Stock agencies would have to expand to cover a larger proportion of the image-buying market. As my prior article advised, the way to do this is to partner (or merge) with photo-centric websites, whose proportion of global internet traffic is very high. This will allow "more information to be more universally available to a greater proportion of the buyers and sellers." This now leads to market efficiency.
  
• Once the market became efficient, it could then be automated through predictive pricing algorithms, precisely the way Google automated online ad prices using an auction-based mechanism. No doubt this is not a simple algorithm, and it took years to evolve, requiring considerable data mining to determine optimal market pricing. But it was achieved to a point where it is now a highly viable (and mutually beneficial) economic model for buyers and sellers. The market of photo buying is similarly large, and there's enough economic activity that appropriate data-mining efforts could lead to similar algorithms for auction-based image license pricing.

The question is whether anyone is willing to invest enough into this untapped market.

Off-topic: Gift Cards

[ Update: The New York Times wrote this column several days after I posted this entry. It's full of detailed industry data. ]

Though I never talk about it, I had a consulting contract a very long ago with a company that wanted to do something in the credit card business. I was involved for about a year, and the while the idea itself was great, it never got off the ground because of a critical "last puzzle piece" that couldn't be solved. I eventually did (and filed a patent), but it was after the company fizzled, and I had no desire to enter into the "payment" business. So, there it stays in my history pages.

But just today, I was talking with someone that said the following:

"I've heard that prepaid debit cards are really bad gift ideas..."

This prompted me to vent a long-standing issue I've had with credit card companies.

The main reason people don't like gift cards is because when the card gets down to about $10 or less, they become virtually unusable. Although you can go to a store and say, "charge the first $7.43 on this gift card and the rest on this regular credit card," it's very rare that people do this. And you certainly can't do that online. So, your $50 gift turns out to only be worth $42.67, and Visa/MC makes a handsome15% profit.

In this sense, gift cards to visa are the victim of their own success. People see the lack of value in the cards, and don't adopt them nearly as much as the card companies would like (or had expected).

The question is, what can card companies do to raise the rate of adoption while not giving up too much on the margins? Remember, the card companies *don't* want you to use up all your credit--otherwise, they give up the margins that makes them worthwhile (to the card company). And they don't suddenly gain new customers just because someone uses a gift card.

Now, one could argue that, as long as they make the same 1-3% margins on the gift cards as they do with regular cards (this 1-3% is the rate that the merchant pays on the total cost of your order), that should be good enough. Well, administration of the gift card program is a bit more expensive, and besides, there's plenty of room to optimize margins anyway. So, don't get me wrong: I don't fault the companies for using gift cards for profit motive at much higher rates. I fault them for not being more intelligent about this in ways to service both themselves and us, the consumers who could benefit from them. Their challenge is to increase overall revenue by finding the sweet spot in the increased adoption vs. the decrease in margins.

The way to do that is by making it easier to use that unused credit in high margin products or services, such as a visa-run online store where they sell products from co-marketing partners (where the co-marketing effort yields more revenue). This would be especially useful for non-physical goods, such as downloadable products, like music, games, movies, etc.

Or, allow gift card holders to apply unused dollars to their Visa Rewards program, which is pretty good, albeit under-appreciated, largely because most people opt for other programs with their visa cards, like airline miles (see below). This would do more to raise adoption rate of the program and potentially convert users to their "real" card. (That should ultimately be one of their prime motivations, yet it's not effectively promoted that way.)

Card companies should also consider developing helpful payment services that make it easier for online retailers to accept multiple card payments, or partner with paypal or google to allow users to register these cards in exchange for a portion of the margins.

Industry research shows that most "reward" programs usually yield the consumer about 1% of his money back, but getting that value is not entirely easy, nor is it immediate. It takes time. A research study I read in the NYTimes some years ago showed that the best programs are those that simply pay you cash back--even at 1%, this was best for consumers. Ironically, airline miles yield the least return, but people opt for them because having more unused miles gives other benefits like premier status that allows access to airline clubs at airports, and advanced positions when upgrading and other things -- all these require high mileage values creating a disincentive to ever "spend" your miles. This makes the "statistic" that credit card airline programs yield low rates of return a bit murky.

The point about reward programs as anyone in the consumer business knows, it garners much more revenue and profit than the 1% you give up to attract the users. Yet, gift card programs don't even attempt to tie into this. Such programs and co-marketing efforts could be more profitable if the card company was willing to make only 5-6% margins (instead of 15%) and offset that with a 10% increase in the rate of adoption, if they were only kinder to the consumer.

Ok, that's my vent. This is not a topic (or field) I will be watching at all, unless it happens to come across the mainstream press. I'm more than happy staying out of this business.

The Economics of Controversy

There’s an old folk tale that tells of Neil Armstrong having sent a letter to the leader of the Flat Earth Society with an enclosed photo of the Earth taken from space. His one-line inscription simply read, “SEE?!” To which Armstrong got a reply saying, “We never said the Earth wasn’t circular!”

With some people, there are arguments you just can’t win, no matter how persuasive the evidence. And most of the time, such arguments aren’t worth having anyway.

Other arguments are worth having because you really believe in the cause.

Some arguments go on so long, they seem both endless and senseless. Remember the Monty Python skit about the man who pays another man to have an argument with him? The first thing they start arguing about is whether or not he even paid. “No you didn’t!” “Yes I did!” “No you didn’t!” “Well if I didn’t, why are you arguing with me?” “I could be arguing in my spare time!”

And then there are those arguments that turn into “controversies.” These are special arguments where the issues galvanize core groups of supporters on both sides, tempers flare, and before you know it, it’s no longer a Monty Python skit.

Though it may be odd to see it this way, here is where new economic ecosystems begin to form. As a controversy gains momentum, more and more people benefit in one form or another by keeping it alive. If it garners enough critical mass, real money can be made, social fabrics can be formed, and political affiliations created. All of these represent different goals and objectives for the individuals involved, which make the intertwining of motivations, methodologies and psychological dispositions fascinating for behavioral economists: those who study people’s behaviors as they pertain to market conditions and self-interest.

In the photography world, there is no better place to study behavioral economics than in the controversy surrounding the Orphan Works Act. And from these observations, one can look for known patterns of behavior that themselves help forecast where there may be investment opportunities.

The Controversy: The Orphan Works Act

The OWA happens to be the perfect controversy because its complexity involves both law and economics, each of which are beyond most people’s understanding, even the leadership. This makes it ripe for oversimplification, misinformation, disinformation, and persuasion.

In the case of the OWA, many who preach aspects about it simply aren’t educated enough on the fundamental principles involved to understand what they’re saying, and the “base” followers are not the type to ask questions—just to “believe.” Straw-man arguments are thrown up all over the place. The classic example is one that I mentioned earlier here: "someone can now steal your photo and claim it's an orphan work, and you have to spend $50,000 filing a lawsuit just to prove them wrong. No photographer can do that!" This is the galvanizing argument that's now settled into the mantra in photo discussion groups.

As my blog post points out, it's a senseless argument because someone could steal an image and claim anything, not just that it's an orphan work. The summary of that article is that it's the infringer that has to spend $50,000 in court to defend his claim that he's protected by the Orphan Works Act. The pragmatic reality is that the infringer will pay the photographer a settlement, even if he thinks he's right.

Yet, none of this very basic, standard legal information is disseminated by anyone in the artist community hierarchy, the photographer community in particular. In fact, quite the opposite. But why?

Once again, it's all about behavioral economics: there are benefits to keeping the issue a controversy, and in keeping the controversy alive.

The Players
Several unique sets of conditions converged at once that allowed the OWA to become the nuclear power station within the photographer community. The stock photo industry has been suffering from economic hardship for quite some time, which itself has threatened industry leaders and organizations, who naturally respond by finding galvanizing issues to maintain control and continuity.

At the bottom of the ecosystem are the core (“base”) believers who are told they have a stake in the game: "If the OWA passes, you will lose your rights to protect your images." The base believers buy into this, and reap psychological dividends by being part of an impassioned movement against the OWA. It’s in this ecosystem where there is a rather dogmatic and cohesive community that typically responds well to populist rhetoric, while being derisive of non-conformist views. In fact, the use of populist rhetoric is prototypical among leaders of economically distressed groups.

On the sidelines is a panoply of catalysts, eager to participate as well: reporters who objectively journal the events, investigative reporters who tell the story from behind the scenes, lawyers and media consultants who work on behalf of their clients to effect a certain outcome, analysts who churn the data to assess the likelihood of various outcomes, and the investors who seek opportunity. Everyone has a vested interest in the process. And therefore, such people become participants.

I too am a player in this eco-system. I’m an analyst, and my economic benefit is the clientele who pay me to do objective research so they can make financial decisions (investments or divestments) based on the likely outcomes of certain events. The Orphan Works Act is one such event. Since it also happens to be a hotly controversial one, at least within the photography ecosystem, the question for these investors is not whether the OWA puts the future of image licensing at risk, but where’s the opportunity for investment? Smart money goes to companies and individuals that know how to capitalize on opportunity. In this case, opportunity lies within those organizations that have a solid, realistic understanding of the state of affairs. My job is to find those opportunities.

Analyzing the Ecosystem
To understand how I do this, I talk to people. For example, I had a conversation with a lawyer who has been rather outspoken against the OWA on behalf of a trade association for a different industry. I asked, “If the OWA passes, and if a case came up that you had to prosecute an infringer who tried to hide behind it, what would your strategy be for dealing with this?” Essentially, I was given a more balanced legal analysis on why the OWA isn’t a threat to artists. The response I got was used as the basis for this blog entry, modified to address the photo space:
http://www.danheller.com/blog/posts/orphan-works-act-courts-and-law.html

So, I then asked, “Why don’t you say anything like this publicly?” The response: “Because my client doesn’t want me to. I’m paid to make these statements and support the objectives of my client.” To which I replied, “Why aren’t you telling your client to soften up on the OWA?” And then came the unsurprising answer, “Because it galvanizes their membership. Renewal rates are up, and they haven’t seen as many new members join in years.” One can only surmise the additional social and political dividends the leadership receives as a result. Short-term economic benefits clouds longer-term judgment. Text-book Behavioral Economics at its finest.

Needless to say, the companies and individuals that hired this lawyer would not be considered “worthy investments” by my clients. (There’s nothing wrong with the lawyer, of course; but that’s not who the investors are interested in.)

To illustrate a more tangible, but more complex example, recall the time when Getty was looking for a buyer to take it private. The company was public, but its share price was dropping quickly, revenue and profits were evaporating, and the nature of stock photography itself was going through a major transition.

One particular suitor asked me to look into an element they believed to be a vulnerability of the company: the economic effect of being “responsive to photographer demands.” Because the investor believed that Getty made key strategic decisions based what its photographers wanted, the question was whether photographers' demands were economically sound. That is, if Getty appeased photographers, would they make more or less money as a result?

A hint that gave them concern was Getty’s acquisition of iStockPhoto. It wasn’t the acquisition that bothered them, of course. It was a good investment. The concern was: why did it take them so long? If Getty was an innovator in the stock photo industry, they should have done this years earlier--not late in the game. The critical question was: what slowed them down? The answer is photographer objections. Because Getty defers to photographers too much, they have a record of failing to make wise, profitable and economically sound business decisions.

What might the long-term risks be? Are photographers always so wrong? Or is this just an isolated case? What does this say about the future? Would Getty lead forward, or will photographers hold the company back, causing the company to miss or delay other key strategic moves as well?

What I was asked to research had nothing to do with Getty, per se, but the effectiveness of pro photographers’ influence on their own industry. Specifically: at key turning points in the economics of the photography world, what were the “photographers’ positions” on those events, and were their forecasts right? Did they fare better or worse as a result of their collective recommendations to their community membership?

Without getting into the details of my report, the data was rather bleak for photographers. In the 1970s, after the supreme court ruled that the ASMP violated “restraint of trade” rules by publishing price lists, the union was disbanded, and a power vacuum resulted. A variety of disparate trade groups started forming, each of which differing only slightly from the others. Yet, at no time did the socio-political strategy change; the culture of the photographer community remained strongly union-oriented. The message remained “all for one” with a strong discouragement of individuality in building a career. Conformity was and always has been the social rule, which itself runs counter to open-market economic conditions.

At no time did I find any key recommendations by the pro photographer community that resulted in positive economic returns. At one point, they discouraged photographers from shooting “stock imagery” because it would “ruin the careers of assignment photographers.” They also discouraged using the internet as a place to sell photos because “people will only steal them.” They also said it would “compete with traditional stock agencies” (who themselves resisted using the internet till royalty-free images moved from CD-ROMs to internet sites). Their poor analysis and responses to matters such as royalty-free, microstock, social-networks, consumers, semi-pros and other industry trends have all been entirely off base. I’ve written extensively about each of these phenomenon at great depth on my blog.

Photography trade associations’ economic advice has also been similarly off target. Membership levels in most all groups have seen very little (if any) growth, despite the fact that hundreds of millions of more people own high-end digital camera gear and contribute larger and larger proportions of images to the stock photo base. The outright rejection of the consumer and weekend photo enthusiast has been one of the primary factors associated with their inability to grow financially, which has also weakened their political influence. (At one time, I recommended that PDN and trade associations charge a maximum of $25/year for subscription and/or membership fees and start running programs that appeal to non-pro photographers that somehow engage in monetizing their images, even at lower levels.)

An incident in my report that summarized it all was when the SAA sent a letter to Getty images strenuously objecting to their having lowered photographers’ royalty rates, seemingly unaware that the company’s sales and profits were plummeting. (This would be like auto worker unions asking General Motors for raises just before they go into bankruptcy.)

Of course, the responses from trade associations have always been akin to “we are giving advice, but no one is taking it; if photographers did what we advised, then we wouldn’t be in this mess.” The reality is, they are taking the advice, but it isn’t working. At some point, one just has to realize the Earth really isn’t flat, and it’s not worth having that argument anymore. There simply needs to be new blood. There’s too much homogeneity. There’s no tolerance for dissent. Perhaps the best quote that encapsulates this situation is one from the 9/11 Commission Report about the errors in judgment that lead up to invasion of Iraq: “When everyone around the table agrees, someone’s got it wrong.”

In general, photographers have had no true economic leadership, and this has lead to a vacuum of economic opportunity. And the evidence is as overwhelming as the Earth is spherical: extremely few stock photo agencies are profitable, and of those that are, the margins are slim and getting slimmer; “publicly traded” stock agencies have had to take themselves off the market (well before the economy turned downward); most stock photographers have reported declining incomes steadily for years; and the per-image license fees have been dropping since records were kept.

When I collect data and do analysis to generate these reports, I have no personal objective, vendetta, or an argument to settle; I don’t care. I just want to be accurate so my clients can make fiscally responsible decisions. And I’m not the only one to come to these conclusions. With the exception of a few very speculative investors, the “smart money” stays away from anything in the stock photo sector. As one of my clients put it, “so long as a company is reactive to the pro photographer community, it’s a losing investment proposition.”

The problem is, there are too few companies that deal with stock photography that don’t worry about the political fallout from discontent raised by the photographer outcry.

If this is the case, why doesn’t the photographer community leadership recognize this and adjust their message to the base? Here’s where we come full circle to behavioral economics: there’s money, politics and reputations involved. Different people seek different objectives, and without centralized leadership, you hold onto what you’ve got. As one executive at a trade association told me, “It’s the perfect controversy for us because we win whether it [the OWA] passes or fails. If it fails, we can say we won; and if it passes, then our members will benefit, and we can say it’s because of what we did. Taking a stand against it is the only position that makes sense for us. Besides, it brings everyone together.”

What Investors Look For
Smart money, smart lawyers, and smart legislators all know that there are no risks to either artists or licensors with the OWA. So, the political theater from the blogosphere is uninteresting to investors, other than to know where not to invest. Investment money looks for signs of intelligence. Any company or investor making business decisions based on photographers’ outcries would be considered a poor investment.

But don’t confuse this with an anti-photographer sentiment. Investors are not anti-anyone. They just don’t want those who don’t understand economics interfering with business. If a company were to exist that keeps photographers happy, while also pursing business goals that show profitability, then that’s great. But the catch-22 in this economic climate is the challenge: the internet and digital photography changed the game from how photographers once viewed themselves, and unless and until they change their cultural disposition, they’re not going to be part of the solution. The stock photo industry has already shifted to be a high-volume/low-margin model, which runs antithetical to how photographers want it. For so long as they don’t accept that, they will be at odds with any company that attempts it. At which point, the company has to choose which path to take: upset the pro photographer and succeed, or acquiesce and fail.

It is for this reason that I’ve predicted for several years that, barring any new disruptive innovation we haven’t seen yet, or a shift in photography-industry culture, the future of stock photography is likely to be inherited by much larger media companies that already deal with massive media distribution and licensing. They have no qualms about playing “Borg” and assimilating the photographer community into the flying cube, all the while chanting, “Resistance is futile.” Once such media behemoths realize there’s money to be made in photography, they will likely start acquiring agencies and photo-sharing sites, and building out the high-volume licensing model that is the only option left for stock anyway.

As for the controversy about the OWA, it’s just a theatrical venue for people to gain their individual advantage. Sure, there may be fine-tuning of language that industry leaders will take credit for to great fanfare, but that’s also part of the game. The Earth is not flat. But as long as there’s some benefit to people arguing about it, the controversy will continue.

The Economics of Migrating from Web 2.0 to Web 3.0

Synopsis

The Web 2.0 financial model: user-generated content attracts visitors, which boosts search rank, which attracts more visitors, which boosts advertising revenue. The traffic-to-dollars business model resulted in unintended social phenomenons: social-networks and blogs, which themselves spurred new web design goals that focus on encouraging visitor participation and contribution. The un-monetized "waste byproduct" from these websites is a stockpile of user-generated content, such as photos, videos, paintings, drawings, stories, commentary, and opinions. To make use of all that flotsam, a suite of semantic analysis tools is being developed to organize and structure them in ways that help search engines produce better results. This is called Web 3.0--or, "the semantic web." The consequence of Web 3.0 will be the unanticipated financial incentive for websites to monetize their content, rather than just host it to attract visitors. The opportunity to make money from user-generated content will give incentive to visitors to produce "better" content, and for websites to be more discerning about the content they receive, which affects both the social and economic landscape of the internet. The ways this type of transformation may evolve is the challenge for technologists and entrepreneurs, who must be both visionary in how the future may appear, but cognizant of missed opportunities of the past.

In this second installment (of three) about the consumer's role in the future of stock photography, I turn my attention to the economic effects from new developments in search technology. As I'll make clear soon, "search" is merely a spark that launches a much larger fire: the social aspects of the web. And whenever the subject of "social networks" mixes with economics, the spotlight focuses squarely on the consumer. I presented a simple example of this in part one of this series by showing that more consumers both buy and sell photos than do professional photographers or stock photo agencies, which itself has caused a dramatic shift in how licensing is done. This phenomenon is not as readily visible to the undiscerning eye, because the greatest proportion of these transactions is done on a peer-to-peer basis (directly between the photographer and the buyer). In fact, asymmetric analysis shows that approximately 80% of photo media content is acquired directly from the photographer, and images are found primarily from search engines. This mechanism creates economic incentive for those on both sides of the transaction: the buyer uses search engines to find what they want, so the seller tunes his content to conform to the kind of information that search engines look for.

The "missed opportunity" from this shift has been primarily the lack of technical infrastructure to support broad peer-to-peer licensing. Only the traditional licensing methods are available on a broad scale, which requires photos being submitted to a company (a "stock photo agency"), who then licenses them to buyers. Each individual agency operates entirely independently from others, and none of them have prominent placement in traditional search engine results, so only a small percentage of potential buyers ever end up on those sites. The majority of them go directly to the websites of the photographers themselves (because the search engines index them), but most of these photographers are unaware that they could make money licensing their content. Indeed, even social-networking sites are unaware of the financial opportunities to license the content. The net result is that few photos are actually monetized, and of those that are, the pricing is arbitrary and spurious. It's estimated the $15-20B of licensing is done on a peer-to-peer basis, and countless more dollars are simply unrealized due to this inefficiency.

I should clarify that even though my first article demonstrated this type of media growth in the photo industry, the broader market of all types of media is evolving similarly. In fact, events in online photography serves as an excellent "base case" to help forecast economic effects for other media types, such as music, video, line-art, books, and so on. What all these have in common, and which everyone has known for years, is that non-professionals create this content as well. And, people do so without necessarily intending (or expecting) make money with it. I call this class of content creators, "consumers."

By examining the photo industry, we can extrapolate what might happen with the industries of other media types. Accordingly, photography has these important characteristics:

1. Everyone does photography on a regular basis in large quantities.
2. People upload their photos the internet more frequently and in higher volumes than other media types.
3. Economically, photos are used more than any other media type in publishing of both commercial and editorial content. (Thus, economic value.)
4. More people can create "salable content" with less expertise, less effort, and greater speed than other media types.
5. The high quantity and low price per unit of licensed images equate to a lower barrier of entry for both buyers and sellers.

Forecasting the economic future of media on the internet is difficult because it isn't clear whether the same lack of awareness will plague other media types as it has with photography. There's already been a major economic shift in the photo industry as a result of the internet, and evidence suggests that similar economic changes are happening with video and music as well. As technology for creating content of any type improves, as does self-publishing of this content, the economics are likely to follow the trend set forth by the photo industry, and consumers will find themselves in a position to make money with their content.

The next phase of internet search technologies and standardized communication protocols may inadvertently help. As we've seen with the evolution of the internet to date, whose economic growth came from unintentional consequences, we can learn from how those circumstances came about, and use them to forecast how the future economics might also take shape.

The goal and challenge for media-oriented industries of all types is to build a more structured, formal, internet-wide framework that handles content licensing in general, regardless of the media type, or who the buyers and sellers are, and establish these foundations before consumers set precedents that are harder to unravel, which could deflate a content's value before it has a chance to flourish.

The good news is that some developments are already under way. But, to put them into context, we need to understand today's business model, and how it evolved into what we currently work with. What we'll find is a very tight sequence that starts with technical innovation, followed by social adaptation, which affects financial incentives, which comes full circle to innovation again. This feedback mechanism of constant reinforcement and revision is an economic truism. Since the technology is already underway, and some of the social fabric is similar taking shape, the only question that remains is how the business environment evolves with it.

Web 2.0 Business Models Setting the Stage

Most people are familiar with MySpace, FaceBook, and Flickr as common and well-known examples of social-networking sites. They are essentially places where people sign up and contribute "content" in the form of information about themselves, while also contributing photos, music, poetry, writing, and ideas of various sorts. In return, they get to socialize -- learn, teach, meet, and access.

Getting people to participate and contribute content is what is commonly called, "Web 2.0", and most sites on the internet are so enabled. You can visit most any blog, news organization, movie review site, shopping site, or cooking site, and you'll probably find a way to contribute something, whether it's as simple as voting on how much you liked a book, or as involved as contributing your own recipes, movies, photographs, short stories, or politically biased nonsense that you hope others will agree with.

While this kind of activity has always been technically possible to program into websites, these features of the web were largely ignored until there was a business incentive to use them. That incentive came in the form of Google's advertising network. If a site had good information, and it was indexed well by search engines, advertisers paid more dollars to have ads there. Consequently, for a site to get those advertising dollars (or to sell its own products or services), it needed to be indexed well, which means it needed more content. The easiest and cheapest way to get content is to encourage people to contribute their content. The incentive that sites give to consumers to contribute is the "social rewards."

By being smarter, funnier, cuter, or more ridiculous than others, people get attention, and people love that. So, websites used the "social" carrot to get people to participate, and in return, the site got its free content, and of course, traffic. These both raise the site's raking and boosts advertising revenue (or sales of their own stuff). Today, it's almost unheard of that sites don't have some way for users to contribute. Everyone wins.

What's notable about this development is that it was unintentional. Social websites had been around in earlier days of the net, but didn't really gather much attention or traffic. Even of those that did, it wasn't easy to make any money from those users. No one bought anything, and they wouldn't pay subscription fees. So, having millions of users did nothing but cost the company money in technical infrastructure (which itself was vastly more expensive than it is today). Companies that had stuff to sell typically didn't garner much traffic, except for dating sites, like match.com.

It wasn't until Google introduced its auction-based advertising model that inadvertently rewarded highly-trafficked sites with unanticipated revenue did a financial incentive exist. There was then an instant awareness that social-networks is where the money is.

Yet, it was never Google's intention to create social networks or any other kind. In fact, it didn't intend to affect the nature of the internet at all. It just wanted to create a model of analyzing the internet as it is (or was) for purposes of setting auction-based advertising rates. They did not anticipate that their very act of analyzing data actually changed the very data itself. (This is a perfect example of Heisenberg's Uncertainty Principle.) Indeed, not only has the data changed because Google observes it, they created a feedback mechanism where the more they looked at data (and thus, reported their observations by way of search rankings), the more the data itself morphed into to the kind that people thought Google wanted to see. This, in turn forced Google to change how it looked at the data, because people were manipulating the content on their sites to artificially bump their rankings higher.

And so it goes to this day: websites and search engines are in an endless cat and mouse game, where sites try to get higher search rankings, and for Google to maintain a plausible ranking system that users can trust to be objective when they search. This credibility is required for advertisers to trust it.

This underscores these basic, fundamental socio-economic principles:

1. Financial incentives promote user behaviors.
2. Examining user behaviors to calculate financial incentives causes sites to filter those behaviors that optimize financial returns.
3. The constant feedback mechanism and subtle refinement of behaviors and economics creates a state of unpredictability.
4. The unpredictability invokes the Law of Unintended Consequences, which yields a new economic model.

This begs questions: What's next after Web 2.0? And what are the potential byproducts from whatever that is? More social networks? Or something else? Our objective here is to anticipate future financial opportunities without forgetting that the feedback mechanism produces unpredictable results. Also, the Law of Unintended Consequences suggests that examining user behavior changes those very behaviors, which itself often forms the basis for new developments and incentives. (Knowing the future will affect your behavior, thereby changing the future.) But, as any good entrepreneur and venture capitalist know (er, should know), the goal isn't to predict or (worse) to control or shape the future, but rather, to anticipate the parameters that are most likely to frame that future.

Web 3.0

The answer to "What's next?" is easy: Web 3.0. In inner circles, this is called, "The Semantic Web." That is, the content on the web that was generated during the Web 2.0 era will be more intelligently analyzed than before. In essence, the data is not just indexed as it is today, but is being better understood for its semantic meaning. This very core nugget of change sparks a feedback mechanism on a very large scale, which will transform the economic foundations of the internet, much the same way the web itself changed the world.

For example, let's say you have a weird and embarrassing rash. Today, searching relies on brute-force matching of search terms, such as "weird rash" or "red rash". Type that into Google, and the results you get are pages that happen to contain both words. Though the pages themselves may be ranked according to popularity (the Mayo Clinic's site may rank higher in search results than some guy's blog), you still have to sift though more than just the first set of results to find what you're really looking for.

You could do an image search for "red rash," but search engines don't really know what's in the content of photos. If you were to do such a search on images.google.com, you'll get photos of red rashes, but this isn't because Google analyzed the photos. They match because the photos happen to have the words "red" and "rash" in the image's filename. E.g., red-rash.jpg. (Google also looks at the file's pathname as well as the filename.) If you try it, you'll see there are photos of every possible kind of red rash you can get, most of them having nothing in common with the others, nor are they sorted or ranked in any intelligible way. The results are merely arbitrary listings of all matches for images with properly-named files. Google relies on the fortunate-but-useful naming convention that some people happen to use when naming their photos: that they name their files according to their content. In practicality, this technique is spurious and nearly useless, but it's the only thing they can go on for the moment. As it is today, you have to examine each photo and see whether that looks like your rash, and then examine each of the pages that the came from to determine what the rash is.

That google relies on photos' filenames to match their content is not just unreliable, it's not even complete. Statistically, most people don't change the filenames of their photos; they leave them as they were from the camera, such as DSC1004.JPG. Photos with those names are never going to come up as a search result for any search, let alone those that could be potential (and valuable) matches for relevant searches, were the search engine to genuinely know what it was searching for. So, there's a lot of photos out there that may be of red rashes, but they aren't found because there's nothing about them that indicates that's what they are.

Pro photographers may be asking, "what about metadata? What about the keywords that I apply to photos? Why doesn't Google look at that?" They don't for the same reason Google no longer looks at the "keywords" tag on html web-pages themselves when compiling results for general searches: websites learned they can game the system by stuffing these attributes with unreliable data.

People can still game the system to some degree by naming their image files accordingly, but for the moment, doing so doesn't really reward the behavior very much. It would only yield sporadic results because Google doesn't sort or prioritize results according to any sensical pattern that matters to searchers. And there's currently no other benefit to naming a photo improperly. After all, why would someone name a photo, sexy-woman.jpg if it's just a red rash?

One reason to do so would be if there were financial incentive, say, advertising revenue if your site were to get more traffic. This would provide incentive to name photos sexy-woman.jpg, even if it's a photo of a rash. As you can imagine, this would completely ruin Google's current image search feature, which is why all search engines are sort of stuck in a corner with image search results: unless they can assure some degree of reliability of results that cannot be gamed once there was a financial incentive to do so, it's best to leave the system as it is -- nearly useless, but not so much so that people don't tinker with it. Yet, there's the very paradox: because it's still the only game in town, people tinker a lot, and it's the source of most image searching on the internet today.

So, unless one can actually, reliably determine the content of a photo, image searches will have to remain circumstantial, unscientific, and without reward.

We can envision what the economic effects would be in a Web 3.0 world, where there was a better semantic understanding of media content beyond just text. Using new algorithms that can determine the content of photos, for example, you may one day search for "red rash" and get a lot more relevant search results than before, simply because the existing content on the web is better understood.

Image-recognition algorithms are evolving in many ways, and look for very different aspects of images to determine characteristics, genres, attributes and, ultimately, content. A couple examples that I often cite in my blogs are tineye.com and picscout.com, which examine photos and find "similars" on the net based on pattern recognition by identifying photos (and portions of them) by assigning a unique "fingerprint ID." Another site, xcavator.net finds photos based on conceptual elements and can do so using specific keywords, like "train" or "window." Using this technique is even better than a text search for "red rash" or "weird rash" because the image recognition algorithm can do a better job of analysis and ordering results accordingly to proximity. Here, you could just take a picture of your rash, upload it to the web, and you'll get search results that are not only more relevant, but they can see similarities and differences that humans simply can't, or would overlook by an untrained eye.

And image-recognition is only one example -- there is also music-recognition technologies that do the same sort of thing. Shazam (www.shazam.com) is a site based on music-recogition technology that is evolving its own economic model by itself. Sing a portion of a song you like into the phone (connected to the company), and it'll tell you what song it is. That's just one application of its technology, and the company is partnering with many different, diverse businesses, many having nothing to do with the web or "search engines" directly, but it is nonetheless a search technology with widespread economic effects that are, so far, unanticipated by industry watchers. A similar-but-different development from Widisoft (www.widisoft.com) does more detailed analysis of music for conversion between music file formats that assist musicians and sound engineers to better compile and arrange musical components of a song.

The social (and, by extension, economic) ramifications of all these developments should be self-evident to anyone that works in an internet or media company. Economic predictions, on the other hand, would be premature without understanding how these technologies would evolve both technically and socially.

Problems with Deployment

The first question most people ask is why aren't these websites (or their technologies) more widely deployed, or even more usefully employed, especially by larger search engines? Several reasons.

First, these algorithms are still pretty young; recognizing patterns is a difficult and imprecise science. Of course, so is traditional text search, but the difference between the two is rather substantial. (Just matching a photo with another photo -- or a song with another song -- isn't yet sufficient for a "semantic" search.)

Second, pattern-recognition of content is only the beginning. Information about what those patterns are and what they mean still need to be seeded, and that information needs to start from humans. This isn't a major barrier, as the current Web 2.0 content on the internet has a great deal of that info already. But, its vast size and disorganization means that time is required to harness it properly. During this process, major search engines are left to guess at semantic meaning from the text on the same page as a photo, for example, which is similarly error-prone and unreliable as their current method of file-naming, though a notch better. The lesson we learned about examining data altering user behavior must be heeded strongly here: if there's incentive to "lie" or manipulate data, search engines will lose credibility.

Thus, the third problem: trustworthy information about content. Because there will eventually be a financial incentive to provide trusted and controlled data feeds about various content types, new methods need to be established to "search and rank" the sources of information. That sounds similar to traditional text search and rankings of websites, but in this case, it's not the site's credibility at stake; it's the credibility of the data found on the site. Or rather, the information about the content. (That is, the description of the rash in the photo may need to be ranked, which may be independent of the site that hosts the photo.) Unlike the text on a site that can be interpreted and ranked -- which is closely linked to the site -- photos and other media types on that same website can be sourced from anywhere, and the data about that media may have well come from an entirely different source. In the Web 3.0 world, it will be much more common for crowd-sourced content to be annotated by someone other than the content's creator. (Wiki-based sites are good examples of this today.)

And lastly, the three problems noted above will be difficult to do by any one entity, since the ingredients in this recipe require participation from many different organizations. Getting that participation is difficult, especially since each is intimately focused on their own small views of the world. (This is the very problem that every player in the photo licensing industry exhibited, which is the primary cause for its slow demise.) Having an entity that sits on top of the trees and sees the broader economic opportunities that it can use to direct which direction the tribe goes in hatching through the forest is not easy, and no one is currently poised to accept such a role. It will unlikely be a small organization, and larger companies tend not to have entrepreneurial spirit or vision.

Yet, these technologies continue to develop. Just as Web 2.0 evolved relatively slowly, so too are Web 3.0 capabilities, and with them will be leading industries that pave the way for the others by establishing standards and protocols that set the economic wheel in motion. The economic wheel for Web 2.0 was advertising dollars and traffic, so people looked to Google for the parameters to design sites and user experiences that lead to traffic, so money can be made. In the 3.0 world, there is currently no such leader, since it isn't yet clear where the incentives are. Nor will such a model exist without having experienced the iterative social feedback mechanisms that are part of every economic development.

What might that social environment look like? Let's consider your rash again: You take a picture of it, upload it to an image-recognition site, which matches it to a set of potential candidates, and each one checked against a medical website that has information about the rashes, which are then fed into a pharmaceutical website, which may list potential remedies. If it turns out you just went camping over the weekend, you can assume it's likely to be poison ivy and choose the appropriate remedy. If, on the other hand, you recently visited the red light district in Bangkok, then your spouse will be alerted, and your lawyer will be notified to accept the divorce papers being prepared for you.

Such possibilities would be objectionable to many, so limitations would be naturally put into place to protect privacy. And that's just one example. As technologies develop and new capabilities are evident, people react, and social acceptance or rejection alters future developments. These must take place before effective and long-standing economic models can form.

Personalized Search

A critical component of this social evolution of Web 3.0 is found in a very old technology that hasn't been exploited to its potential: that of "predictive preferences." That is, search results being ordered according to what might be appropriate or relevant to the searcher. While many may not be aware of it, the vast amount of raw content from the Web 2.0 world is being analyzed by "crowd-analysis algorithms", which look at data that people have voted on or expressed some kind of opinion about. This data is then examined for patterns to predict how individuals might like something, which can then be used to determine whether any given search results should rise or fall in "relevance" ranking.

In the music industry, there are two applications of this technology that you may be aware of. Amazon.com has been using predictive preferences for years, and I rely on it almost exclusively when I buy music. I let amazon choose new albums for me based on what it knows about me: the things that I've bought in the past, searched for, and/or rated my preferences for as it tracks my behaviors on its site. It even looks at preferences that aren't music related. when it offers suggestions for what I'd like, I'm always shockingly surprised at its accuracy. (Porcupine Tree is my latest miraculous find.)

Another example is Pandora (www.pandora.com). People with an iPhone were recently introduced to it this way: name a song, a band, or a genre, and the site will stream music to you in radio-station format, all comprised of songs that you are likely to enjoy.

Part of how pandora does this is by applying conceptual attributes to songs, such as "acoustic guitar solo." There are over 400 such attributes, which the site calls "the music genome project." This requires humans to assign such attributes to songs manually at the moment, but music analysis isn't that hard. It isn't a stretch to envision combining these two technologies, so that an algorithm determines attributes based on digitized sound waves, which it can then assess and assign to other songs in real-time.

Hypothetically, I could rent a car in a city I've never been to and program the radio's stations by singing a song that I happen to like. The radio can be instantly programmed to assign stations to the preset buttons. No more "scan button!"

A similar "genome sequence" of photography or video has never been done (or proposed as far as I know), but it seems as one would be inevitable, and would lead to another step in the semantic understanding of media on the web. When you combine the semantic understanding of content with predictive preferences, you have a readily monetized network of resources that, currently, no one is capitalizing on.

Web 3.0 Business Model: It's the Content, Stupid

This scenario presents the potential for a pivotal economic shift of focus for where value is: from the website to content. As my earlier research in the photography realm revealed, the less time it takes for a searcher to find a relevant photo from a search, the more likely it is that the searcher will license it. There's every reason to believe that photos are not unique to this human behavior and economic need. The semantic web will make it easier to find content of any sort, and if the searcher's results are also tuned to their particular preferences, it raises the likelihood that such content would be purchased beyond the ratio we see today. Thus, the value of content on a site goes up because it has a higher chance of being monetized.

Remember all those photos named, DSC1004.JPG? That's content that is currently next to useless because it carries no semantic meaning, and is therefore not seen or understood by current search engines. The semantic web will eventually find all those abstract media objects and make sense of them, adding them to the set of possible search results. Such data exists in all media types, not just photos, making the economic possibilities far greater than anyone has anticipated. So, once all the "useless raw content" from Web 2.0 is semantically analyzed, it is likely to emerge in the Web 3.0 world as "invaluable data assets" that contribute even more to the Long Tail of internet economics.

As the perception of content's value continues to increase, Web 3.0 sites will have more incentive to attract those who create quality content.

An example illustrating this socio-economic development can be found in this story from the New York Times. Joel Moss Levinson, "a college dropout with dozens of failed jobs on his resume," has earned more than $200,000 by creating homemade movies that major corporations are now using in their mainstream commercials. Where'd they find them? YouTube. The article goes on to mention many companies getting content directly from common consumers, rather than through traditional ad agencies, and how this trend is reshaping many aspects of the Marketing and Advertising industries.

The beneficiaries of this are obviously not just limited to individuals. While Levinson created his own content, there's quite a bit of mainstream content from traditional media companies that can be applied to the same business model that benefits them: make the content available for a fee. More and more consumers are actually paying for movies and videos over the web, which is a trend that was once predicted, but failed to materialize for years. In fact, there was doubt that it would ever happen, because users just got used to the net being "free." Many early sites that tried to charge for membership found they couldn't make the numbers work. But as users are learning that good content is harder to come by, this model is finally becoming economically stable. And, it has a twist: users are not just getting content for pay, but are also given further incentives to contribute as well, such as feedback or other information about the content they're paying for. These incentives come in the form of reduced fees, or in the reduction of advertisements the visitor otherwise has to see before getting to see the content. An example is found in this article in the New York Times, where Hulu (www.hulu.com) allows visitors to view programming with fewer ads, and encourages visitors to vote on shows with thumbs-up and thumbs-down buttons.

As new and different kinds of websites are built to respond to that economic incentive, websites will continue to reinforce this behavior by adjusting compensation and other reward systems. They'll also want "semantic information" about that content, not just raw data, which changes the user experience, which changes the nature of how and why people go to websites in the first place.

Evidence of this is already making headlines: YouTube's recent announcement that they will now begin to enable users to purchase songs and other content found on the site -- whereas, before, such content was only used to attract more visitors. Similarly, Flickr's relationship with Getty Images is one where a company is cherry-picking user-generated content from a social network and selling that very same content on a professional photography site. Still another example is the growing basket of online discussion forums that are converting from "free access" to paid-for access, which is the most overt illustration where a site is changing its business model from using user-generated content to attract visitors, to one where that same content is used to generate subscription fees.

All this is part of the feedback mechanism that perpetuates unpredictable change. As users themselves are ranked and "scored" for the various content types they create and contribute, a phenomenon that already exists in many forms on social networks and discussion boards, there would be an amplification of this if there were financial incentive to raise your rankings. Or, to lower others' rankings. This type of human behavior has not yet been put to the test in a broad scale on the internet yet, so its economic effects cannot be predicted.

New Frontier for Web Design and User Participation

The economic models I described above have all been on insular sites that host content. That is, people realize that content has value, so they are using Web 2.0 world to find it. However, in the Web 3.0 world, content may very well exist on websites that don't yet have an ecommerce infrastructure. It's not just about taking credit cards or other forms of payment, it's about pricing models and legal licensing terms. This is the very inefficiency of peer-to-peer licensing that I focused on in part one of this series.

New internet-wide methods and protocols must be established to enable any website that carries licensible content. As more and better content is produced, and as search engines are better able to analyze it semantically and produce search results sorted by personalized preferences, more of the content must be licensed through a universally available infrastructure, thereby transforming the way websites are designed, further affecting the visitor behaviors and incentives.

So what about that licensing mechanism? One such development in this area is ACAP, which is found at http://www.the-acap.org/. ACAP stands for the Automated Content Access Protocol, and its main initial purpose is for communicating access and usage permissions (about the content on any given site) to web crawlers (also known as 'spiders' or 'robots'). Just as you currently accept (and need) Google and other search engines to crawl your site to index it so it will come up in search results, an ACAP search engine will do the same thing, but it looks for other details about your content besides its semantic meaning. It is used to specify license terms and conditions that the owner stipulates, should someone want to license something from your site.

Of course, this a huge and complicated effort, since mechanisms need to be put into place to track and verify content ownership. But, waving the magic wand about that for the moment, if it were to exist, this then paves the way for a content licensing protocol to sit on top of the entire stack of media and search data about it, to complete the puzzle: any content crawler could assess market conditions for any given type of media type and estimate a market value. Plug that into an existing auction-based system like Google's adwords program, and the financial models are in place for the new economic model where a series of automated analytical robots crawl the web, analyze content, rate and rank its information and its creators, and come up with a high/low range for pricing, which can be used to see a more fine-tuned auction-based mechanism.

As futuristic as this may sounds, all of the technologies that do these tasks exist today in one form or another. It's merely applying them in a generalized way to arbitrary and abstract data types that makes it an inevitable development. What's more, it's self-regulating and self-perpetuating. Taken out of the equation is the inefficiencies of peer-to-peer licensing models, where prices are arbitrary, and the transaction itself is costly and time-consuming.

Just as Web 2.0 created a feedback mechanism (where social networks yielded financial returns, which stimulated the growth of social networks), the Web 3.0 world will have a similar feedback mechanism, where content creators are given incentives to create good content, describe it well, and allow third-party, automated market-makers to handle transactions. Though the content itself may still be exchanged between creators and publishers, the transaction will more likely be officiated through market-makers.

It's also a more efficient system in that incentives to cheat are reduced. This comes in two forms. First, because everyone's search may not necessarily yield the same results, attempting to manipulate content to match what someone might think search engines are looking for may actually diminish the content's value. Searchers looking for a photo of a "woman" aren't always looking for porn -- they may genuinely be looking for a photo to be used in legitimate mainstream media. If the content creator tries to "lie" to manipulate search engine results for the photo, he may inadvertently eliminate as many buyers as he would attract if he were just honest about the content in the first place. That's not to say that all content is equally valued, but that brings up the second aspect to semantic awareness by search engines: the content itself would be ranked, not just the site it came from. If a particular set of photos were manipulated with "keyword pollution" (where the photographer adds a huge amount of keywords in the hopes of being indexed to match a large number of search parameters), then that image would be reduced in its credibility ranking, irrespective of what the photo's content actually depicted, or what site the photo came from. Being a bad actor in the economic game has penalties, and being a good actor has rewards.

The Spoiler

So, what can disrupt this potential future? The elephant in the middle of the room that I haven't mentioned is Copyright. That is, user-generated content is copyrighted material, owned by the creators of content, and that creator has rights. The ability for a website to sell content that visitors submit is restricted in ways that aren't entirely easy for everyone to quickly understand, and navigating around this restriction involves an exercise in skills in three disciplines: political, legal and socio-economic. I'll tackle all that and more in part three of this series. Stay Tuned.

Non-commercial uses of images: do non-profits need model releases?

In the spirit of my recent accouncement of my latest book on model releases, I thought it apropos to post a blog entry I have had in the queue for a while: whether non-profit organizations are immune from the need for model releases for whatever they publish: promotions, newsletters, fund-raisers, etc. At the heart of this question is what is meant by "commercial vs. non-commercial use."

It started when I read a blog entry from a site that caters to non-profits. It had this text:

"...if you are publishing a photo for information or educational purposes, not commercial purposes like product advertising, you can typically print it without a model release. The majority of non-profit publications fall into this category."

The premise here is erroneous: that non-profits fall into the category of "non-commercial users." This is not the case, and this misunderstanding lies in what is meant by "commercial use." Most people associate this expression with advertising and promotion of for-profit products and services. Yet, those are not the only uses covered by the law surrounding privacy and publicity laws. And it's those laws that stipulate whether consent is required from a person to publish a photo of them. (A model release is what grants that consent.)

These laws are not based on "commerce" as people traditionally think of it, but around how people are represented, regardless of the kind of business the publisher (user of the photo) happens to be. Whether a person's likeness is being used to advance a cause, an agenda, or any number of things, these are really the core of the intent of the law.

Federal statutes exist that protect people's rights of publicity, and about half the states in the US have additional statutes that go beyond those basic principles. A good example of this is found in the California Code 3344, which can be viewed here.

You'll note that there is no text in any of this language that talks about whether money is made, or the status of the publisher of the image, such as whether it is a for-profit or non-profit. This is not what is meant by "commercial"... Instead, it really refers to "in the course of business," and to differentiate the use from news reporting and other uses protected by the First Amendment.

For purposes of model releases, it's the use of the image that matters, and non-profits are businesses, like any other: they have staff, letterhead, advertising and marketing budgets. This is all part of "normal course of business," otherwise known as "commerce." Accordingly, when they publish photos of people, there may be a need for model releases that applies no differently than for for-profit companies.

Further supporting the notion that the law is not intended to exempt non-profits is the fact that the statute does not define what "services" are. A non-profit that delivers food to the homeless is providing a service, as is a non-profit that advocates humane treatment of animals, or that provides assistance to war veterans, or religious groups that teach reading, or HIV/AIDS groups that provide support services, or gay and lesbian organizations, and so on. If the assumption made by the quote on the non-profit blog mentioned above were true, it would be that these organizations would be exempt from requiring a release from using a photo of someone because they are non-profits. As you can imagine, any one of these organizations may or may not be supported by everyone in the country, so could it really be that they could use photos of anyone they wanted for any reason, without their consent? That's an easy "no." Imagine how upset you would be if a non-profit that advocated a cause you don't support were to use a photo of you in an ad.

This is what federal and state statutes are there for: to prevent this sort of unfettered use of people's likenesses. Nowhere does any statute state whether "money" as anything to do with any of these transactions or companies.

But, don't let this reality jolt make you think that all non-profits have to get releases for all photos they use. And since non-profits are treated identically to for-profits, it may even be more surprising to learn that for-profit companies don't necessarily need releases for all the photos they use in ads either. And this potential lack of a need for a release lies in an infrequently-read subsection (e) of the same California Code 3344, which reads:

The use of a (...) photograph, or likeness in a commercial medium shall not constitute a use for which consent is required (...) solely because the material containing such use is commercially sponsored or contains paid advertising. Rather it shall be a question of fact whether or not the photograph or likeness was so directly connected with the commercial sponsorship (...) as to constitute a use for which consent is required (...)

In other words, the person has to look like they are somehow advocates or sponsors of the underlying product or service. In the simplest case, just because a website, magazine, newspaper, or newsletter may have ads in it does not suddenly trigger the need for a release from the people who may happen to be in photos on the same page. Just having a photo of someone is not the test -- it's whether there is an implied association (or affiliation) between the person/people in the photo and the "user" (publisher) of the photo, or the advertiser. (Hint: you see ads on the same page as articles in newspapers. That's no different than ads on a web page that happens to have editorial content and photos of people. Readers know the difference between an ad and an article, at least in most mainstream publications.)

Obviously, this is highly subjective, as well as highly-dependent on the given photo and the given use. All of this is entirely (and somewhat arbitrarily) up to the whims and opinions of judges. Not that there's anything wrong with that. But, it's this lack of specificity that allows people's assumptions to lead them astray.

In effect, this new understanding of subsection (e) introduces a brand new view that you probably didn't expect: just because someone is recognizable in a photo and that photo is used in an ad, it does not necessarily trigger the need for a release. Subsection (e) states that the person in the photo must appear to be "directly connected with the sponsorship." If you were to have a close-up photo of a person looking directly into the camera with text over his face saying, "I have AIDS," the implied between the person in the photo and the organization is pretty strong. However, a photo of a local band that happened to be playing at an outdoor event that happened to benefit the non-profit could show up in a newsletter to members with a far less likely need for a release. Is there an implied association? Perhaps, but it's far more benign and less likely to be objectionable to the band members (or they wouldn't have played the gig in the first place).

Between those two endpoints is an infinitely large number of possibilities for how someone might look as to determine whether they are "directly connected" to the published use of the photo, and whether that person would be likely to object.

And it's that analysis that leads us to real-world events and how they often don't reflect academic discussion, or even the laws themselves. This is why most non-profits don't think or care about having releases: most of the time, nothing happens and no one cares. But it's still important to mention, because the law is the law, after all.

In conclusion, despite the fact that this was about non-profits, it turns out that they aren't different than any other organization. What this topic is really about is what is meant by "commercial use." It's not what people think -- that money is made or has changed hands because someone's likeness was used. Privacy and publicity laws are written to address people's rights as to how they are represented, and whom they can be implicitly associated with, regardless of whether money plays a role. If a company violates those rights by publishing an unreleased photo that can imply an association, _then_ it becomes all about money. Theirs.