📚 Book Notes: Who Owns the Future?

Here are my notes from Who Owns the Future?:

  1. Here’s a current example of the challenge we face. At the height of its power, the photography company Kodak employed more than 140,000 people and was worth $28 billion. They even invented the first digital camera. But today Kodak is bankrupt, and the new face of digital photography has become Instagram. When Instagram was sold to Facebook for a billion dollars in 2012, it employed only thirteen people.
  2. Pay people for information gleaned from them if that information turns out to be valuable. If observation of you yields data that makes it easier for a robot to seem like a natural conversationalist, or for a political campaign to target voters with its message, then you ought to be owed money for the use of that valuable data. It wouldn’t exist without you, after all. This is such a simple starting point that I find it credible, and I hope to persuade you about that as well.
  3. Musical recording was a mechanical process until it wasn’t, and became a network service. At one time, a factory stamped out musical discs and trucks delivered them to retail stores where salespeople sold them. While that system has not been entirely destroyed, it is certainly more common to simply receive music instantly over a network. There used to be a substantial middle-class population supported by the recording industry, but no more. The principal beneficiaries of the digital music business are the operators of network services that mostly give away the music in exchange for gathering data to improve those dossiers and software models of each person.
  4. Picture this: It’s sometime later in the 21st century, and you’re at the beach. A neuro-interfaced seagull perches and seems to speak, telling you that you might want to know that nanobots are repairing your heart valve at the moment (who knew you had a looming heart problem?) and the sponsor is the casino up the road, which paid for this avian message and the automatic cardiology through Google or whatever company is running that sort of switchboard decades hence.
  5. In the event that something a person says or does contributes even minutely to a database that allows, say, a machine language translation algorithm, or a market prediction algorithm, to perform a task, then a nanopayment, proportional both to the degree of contribution and the resultant value, will be due to the person.
  6. To me this false trade-off, which was often stated in the 1990s, foreshadowed what we hear today about free Internet services. Tech companies have played similar games, said similar things, and pale in the same harsh light. “Sure there might be fewer jobs, but people are getting so much stuff for free. You can now find strangers’ couches to crash on when you travel instead of dealing with traditional hotels!” The claim is as wrong today as it was back then. No amount of cost lowering can foster economic dignity when it also means that there are fewer good jobs.
  7. The initial benefits don’t remotely balance the long-term degradations. Initially you made some money day trading or getting an insanely easy loan, or saved some money couch-surfing or by using coupons from an Internet site, but then came the pink slip, the eviction notice, and the halving of your savings when the market drooped. Or you loved getting music for free, but then realized that you couldn’t pursue a music career yourself because there were hardly any middle-class, secure jobs left in what was once the music industry. Maybe you loved the supercheap prices at your favorite store, but then noticed that the factory you might have worked for closed up for good.
  8. The spread of a flu outbreak can be tracked online faster than it can be tracked through the traditional medical system. A research project at Google found that flu outbreaks could be tracked well by noting relevant searches in geographical zones. If there’s a sudden lift in concern about flu symptoms in a particular place, for instance, there is probably flu there. The signal is observable even before doctors receive the first wave of complaints.
    Tracking the flu online is science. That means it isn’t automatic. Scientists must scrutinize the analysis. Maybe a rise in flu-related queries is actually in response to a popular movie in which the lead character has a bad flu. Without scrutiny, data isn’t trusted.

If you liked the above content, I’d definitely recommend reading the whole book. 💯



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