predict the tomorrow

Everyone uses Google (or search engines in general) to find something from the past: What are the soccer results from last week end, who wrote an article about surveillance, where is that “critical update” for my webbrowser? Google finds out the questions and needs of a lot of people (e.g. 50% of all US-search) and with a little extrapolation one could say: of the world. The (monthly) statistics on the psyche of the world can be inspected at the Google Zeitgeist.
The future is nothing random but created by ourselves everyday through actions that are driven exactly by these questions and needs that condense at the search interface of Google. Wouldn’t Google be able to predict the things to come?

While this is one of the stunning (at least to me) results of the Google and Borges class at Humboldt University, I developed a game concept that takes one step back and leaves prophecy to the players.

You are owning an ambitious little news company. As an editor in chief, it’s your responsibility to pick the most interesting topics for each issue. Whether your instincts were right is proven the next day with Google News producing a dossier about the most relevant news (as stated in their Help Section):

Google News relies on the collective judgment of online news organizations to determine which stories are most deserving of inclusion and prominence on the News homepage.

Your number of staff members is limited (as is real estate on the frontpage), so you can’t cover all the topics and it depends all on your selection.

For every headline you “knew in advance” and that evolves as an important one, you will not only get credits but also improve your reputation within your business community. The higher the reputation, the higher your ad-selling-revenues, so when you earn credits the next time they will get mulitplied with your reputation factor. You guessed right the

  1. top story: +1 reputation, 1000 credits
  2. top story: +1 reputation, 500 credits
  3. top story: +0.5 rep., 300 credits
  4. top story: +0.5 rep., 100 credits
  5. top story: 100 credits
  6. top story: 100 credits

You can spend the money on new staff thus being able to cover more topics per run. This will cost you 500 credits once.

If you have even 2000 credits left you may found a new department within your corporation so you can work on a field of special interest like Sports, Technology or People as well.

And once your money starts bubbling out of your pockets you may even think about buying your competitor and taking over their business, their departments and their reputation points! Promising candidates will be a challenge to your treasury as their basic price (2000 credits) will be multiplied with their reputation points and the number of their subdepartments. It might be profitable, nevertheless, as it is the only way to get reputation points except having one of the top headlines. And it sets the other player out of game, of course.

As a work in progress this game is not meant to be a best seller but rather a tool for some hands-on research. Here is what has come to my mind already:

  • of course, all the numbers are right out of my mind. For a rewarding gameplay they have to be balanced carefully
  • a forecast of news topics for several days or for in two days or more might multiply your revenue as well
  • a newsreader could be made part of the game’s interface that lets you select your personal sources of rumors and hints. The relations between sources and performance of the player could be really interesting.
  • For sure, there are applications that are closer to the idea of Google as an Oracle. Unfortunately they do not offer their statistics other than in Zeitgeist.
  • I’m always looking for a more intrinsic way of visualizing the information of the web as a kind of collective intelligence (inspired by the Google and Borges class as well) so any ideas are appreciated!

one Response to predict the tomorrow

  1. Hannes:

    Today I talked about my ideas to Matthias Ljungström who teaches Game Design at fhp.

    This is sketching what he said:
    There should be a drawback when hiring a new reporter (at least for the new ones): pay a regular salery to the reporter, so the risk rises when you can make a lot of guesses (i.e. have a lot of reporters).

    When buying your competitors it might be more interesting not to take completely but rather get a part of the profits (and losses!) of the acquisition. If they are performing extremely well they could break loose again, as well.

    The concept as a whole is a nice basis for further thinking not only about the game but also about the backgrounds. E.g. it is using the Google News only to extract the headlines, thus the events the articles are about are almost irrelevant. This might correspond to the way Google itself treats the news as it makes its selection based on algorithms and network analysis “only”.