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Advocates of Mass Media often express alarm that Individuated Media could lead to billions of people becoming isolated from each other, from their communities, and from the world at large. The advocates of Mass Media argue that if Individuated Media provides only contents that specifically fit an individual’s unique needs, interests, and tastes, then that individual won’t be exposed to contrary opinions or to any subjects that that he didn’t decided upon in advance. If that is true, they claim, Individuated Media won’t be good for society and might very well be harmful. How then, they ask, can anyone create a ‘common agenda’ for a community?
There is a bit of validity to their worry. They are however creating a false dichotomy that ignores both technology and aspects of human nature.
The false dichotomy they’re creating is that the choice is between people being integrated into or isolated from society; that the choice is between entire Mass Media or entirely Individuated Media.
It is true that by delivering a mix of contents that better match each person’s own unique mix of needs, interests, and tastes, rather than just delivering contents that are based upon a mass or group demographic, Individuated Media does provide significantly less extraneous contents that don’t match that individual’s needs, interests, and tastes, thereby contains significantly less contents that don’t match his needs, interests, and tastes. Thereby lowering that chances that he might consume some contents that don’t match those needs, interests, and tastes, and possibly including some contents than serendipitously might awake new interests and tastes in him. That is the quantitative ‘price’ of delivering a more efficient match of contents to that individual. It is inevitable that as contents deliver gets ever more articulate as technologies progress, then this will happen.
However, while some individual consumers might request no extraneous or serendipitous contents be delivered to them, it is unlikely that most consumers will want their content services absolutely that way. Nor is there any technological reason why the content provider themselves must deliver it that way.
Most people want to be individuals yet want to share, compare, and find others like themselves. Each of us possesses this inherent duality of individual and multitude. Nobody likes to not know what everyone else knows. That is human nature. Was there a disaster? Has there been a crime? Who is this latest celebrity, and what is she all about? People naturally want to know what they don’t know; else journalism would have expired long ago. Most people will want some unusual or serendipitous stories, topics, and issues added to their content feeds, and will want someone (their friends, plus professional editors) to decide what.
Nor does Individuated Media shackle media professionals from providing them with stories that might be outside their known or explicit needs, interests, and tastes. Individuated Media are about more precise matching of contents to those needs, interests, and tastes, and not about automatically excluding all extraneous or serendipitous contents.
Decades of readership studies of by the newspaper industry have noted that the average reader only reads two to five stories in the average edition that might contain 20 to 50 stories. That indicates that form of Mass Media has a 4 percent to 24 percent rate of possibly having matched stories to the average reader’s needs, interests, and tastes. Individuated Media editions of newspapers would aim to increase that to 50 percent or more, still leaving plenty of space to include stories that the editor wants all readers to know, plus some stories that have the best probabilities of serendipitously interesting that specific reader.
[Note: an individuated edition is created using a high-speed digital press, basically a giant inkjet printer into which newsprint is fed, which uses a data base containing records of each individual consumer’s needs, interests, and tastes, matching those to a data base of available stories from the newspaper’s own journalists, news syndicates, and newswire services. A computer matches a selection of stories to each individual, uses pre-designated layout templates to instruct the digital press to print an edition custom-tailor each individual’s needs, interests, and tastes. Digital presses aren’t a new technology, but have been used for decades by commercial printers to produce utility company and credit card invoices – readily available examples of Individuated contents produced on mass scale. The European newspaper industry had been experimenting with digital presses prior to the Great Recession.]
The editor can pick and choose what stories he wants all readers to know, provided those are either bulletin or urgent stories likely to be of universal interest. There will always be a market for Mass Media contents about universal interests and always a sizable market for Mass Media contents about group interests. However, that story about the record wheat harvest in Nebraska, a story fitted around the supermarket advertisement on page 3 of the printed edition, is unlikely to be included in Individuated Media unless the consumer has an active specific interest in wheat or lives in Nebraska.
If that is how within Individuated Media an editor can possibly still create a ‘common agenda’ for his community, how can he provide serendipitous stories with that media? He still can by including some stories the serendipity reaches that same threshold of nearly universal interest (i.e., ‘Local Woman Wins Billion Dollar Lottery’). Otherwise, the editor might be better served relying on information technology. There currently are four different methods being used to attempt introducing individuals to serendipitous matches of contents or products:
- The first is Demographic Matching, which uses the individual’s demographics (mainly gender, age, and location) to suggests contents or products. Demographic Matching has been used for decades and isn’t very efficient when compared to more modern means.
- During the 1970’s, some marketing companies experimented with a second method, Personality Type. This method endeavors to identify an individual’s psychological Personality Type (often using the Myers-Briggs system). However, Personality Type analysis has proven better for use in psychiatry than in marketing or media industries, and is rarely anymore by those industries.
- The third means is Computer Heuristics, in which a computer constantly learns and refines its understanding of an individual’s needs, interests, and tastes. This method can deal with people’s changing needs (marriage, divorce, births, illnesses, graduations, etc.) but is hampered because computer technologies haven’t practically reached the level of the HAL 9000 computer in Stanley Kubrick’s 2001: A Space Odyssey. Perhaps in the imminent Web 3 future?
- The most practical and widely used method today is Collaborative Filtering. This is the technological method used by companies such as Amazon.com to recommend physical products, books, and films to its customers. The method record’s the individual’s previous active choices (such as his purchases at Amazon.com). It searches its data base of all its customers’ choices, looking for those customers who made the same choices. It then takes the choices those other customers made but that the individual didn’t and suggests those new choices to the individual. The more choices an individual has made, the smaller will be the number of other customers who also made those choices, yet the resulting number will be those most likely to have the same needs, interests, and tastes as that individual, and thereby can be used to provide more precise choices of what might be of serendipitous interest to that individual. Some Collaborative Filtering systems also use Fuzzy Logic to further widen the possibility of serendipitous matches.
The Collaborative Filtering method for generate serendipitous matches is likely to become widely used once Web 3 becomes the predominant way in which people obtains news, entertainment, and other information.
Next webpage: Preparing for Web 3