Yahoo is exploring an automated way of becoming a finder of talent, of top reviewers, of social network influencers. Could a search engine replace music label A and R departments, Hollywood talent agencies, publishing house manuscript readers?
I’m terrified of the idea.
Commercial exploitation of talent is traditionally a slow and subjective process, in which talent scouts would experience artistic works and discover artists, by doing such things as reading manuscripts or listening to musicians, watching movies, and viewing artistic works.
Those talent scouts would then make decisions about how likely it was that an author or performer would become popular or successful based on a subjective assessment of the performances or works in question.
The scope of media has expanded from traditional literary and musical and artistic works such as “books, articles, songs, plays, movies, fine art or photographic images” to newer forms of media, such as “weblogs, video games, music samples, ringtones, websites, descriptive terms such as tags or keywords, or digital ratings and reviews.”
There are corporate interests seeking talent in these areas, especially at an early stage in the careers of such creators and publishers. Much new media these days gets exposed to the public before ever reaching talent scouts and critics.
Yahoo has filed for a patent that would work to automatically identify talent from quality, popularity, and productivity data available on the Web.
The patent application would attempt to look at the quality and popularity of artistic works and their associated publishers:
Talent Identification System and Method
Invented by Edward Stanley Ott
Assigned to Yahoo
US Patent Application 20080077568
Published March 27, 2008
Filed: September 26, 2006
Systems and methods are disclosed for automatically identifying talent from quality and popularity data available on a computing network. The computing network is monitored and new content items and their associated publishers are identified.
In addition, quality and popularity data associated with each content item are retrieved from one or more locations on the network. The quality and popularity data are then analyzed to identify popular content items within a particular scope and create a popularity measure of each content item.
The popularity measure of each content item is then used to create a popularity measure of each publisher.
Examples of Publishers and Talent
Examples of the kinds of publishers and talent covered under this patent filing might include:
- Creators of playlists of songs within a genre (e.g., the “Greatest Bluegrass Songs to Dance To”),
- Authors of books, blogs or websites (e.g., Patently Obvious),
- Actual publishers of a book (e.g., Chivalry Bookshelf),
- Reviewers or publishers providing reviews of local interests such as restaurants (e.g., the magazine “5280” covering the Denver market for reviews local attractions),
- Producers of family-friendly movies (e.g., Pixar), or;
- Landscape photographers (e.g., Ansel Adams)
Roughly, this process of identifying talent, publishers, and content might include:
- A method for identifying publishers of content,
- Monitoring the popularity of the content over time,
- Identifying leading publishers that are likely to become more popular in the future based on the trends of popularity of the publishers’ content items.
Publishers might be identified within specific market segments, such as movie reviews, reviews specific to a geographic region, or music playlists.
Popularity might be measured by looking at metrics such as number of downloads, sales data, number of mentions in the media, mentions of a content item in the pages of a social network such as forums and chatrooms and sites such as MySpace.com.
Productivity could be another measure viewed, with someone producing a number of popular works over time being considered more likely to create new popular works in the future.
…some types of data may be leading indicators of popularity, such as mentions in MySpace listings among 8-12 year olds, reviews by certain known reviewers, number of internet searches on a specific search engine, or number of downloads to a specific type of device such as an iPod, while other metrics may be lagging indicators of popularity such as number of mentions in main stream media articles or advertising revenue.
Thus, the system may distinguish between the types of data by developing complicated metrics that incorporate different types of data in an attempt to quantify one or more characteristics.
The process described in the patent filing would identify leading talent and publishers within different categories and audiences, and allow commercial interests to uncover and contact publishers and talent.
For example, in the same way advertising words are sold by search engines, the publisher identification system could alert members to up and coming talent within specified scopes and allow the members to bid or otherwise pay to engage the talent.
Information about talent, content, and publishers could be provided as part of a paid ongoing service:
For example, a record label that is continuously on the look out for new recording artists may purchase a subscription to periodic popularity rankings within specific scopes.
A bluegrass record label may wish to see the publisher rankings for all publishers of bluegrass songs each week.
Alternatively, a third party may wish to be alerted only to new publishers with high publisher velocities or new content items with high content item velocities within a certain scope.
Other Commercial Applications
The system described could be used in other ways, such as being adopted to sales of different items:
For example, the systems and methods described could be adapted to the sale of products such as bicycles and include such data as number of racers using each brand, sales amount, results of manual interviews or random polling of consumers.
Furthermore, embodiments of the systems and methods described herein could be adapted to work with any data source associated with any commercial enterprise in order to identify consumer habits and trends in the use of resources.
For example, the usage trends of different types of cars within a car rental agency could be automatically analyzed in order to identify how best to purchase cars in the future based on popularity and quality data.
I think I like the old talent scout method better….
Popularity doesn’t equal talent.
Many artists who bring us something new and unique are often unpopular at the start of their careers, and an automated process like the one described stands a good chance of harming us as a society rather than helping us.
It rewards the loudest voices, rather than the ones that might hold the most beauty, the most innovation, the most potential to make positive changes in the world around us.