User surveillance is a next business generation
Human behavior is highly predictable. We talk and act in the same manners, read the same kind of books or news, make same styles of friends, shop in the same malls, and commute and travel in the same pattern.
In a big picture, a shop serves more or less same kind of customers, a newspaper attracts more or less the same styles of audience, etc. In addition, modern technologies provide a rich comprehensive data that reveals information before experienced experts can tell. For example, information from smart watches can tell a person being going to get sick before the best doctors can diagnose. Human behaviors, in fact, can be easily predicted.
Many companies have advanced in applying AI systems to predict users behavior to their business. Google uses many methods to predict users’ next move to serve the best advertisers. They can learn from users’ email a booking flight to suggest other services (e.g., renting cars, or accommodations). They would also know if users are businessmen with large sum budgets or students with limited spending to recommend appropriate solutions. Amazon, another example, pushes the systems into its edges by introducing pre-ship system where they ship the good close to customers’ doors before they place orders.
They learn from users’ data to predict what would be the next buying and process the “virtual” order before customers click the purchasing button. Recently, Google has the permission to use medical data of 1.6 million patients in the UK for their deep mind analysis. We will never know what would they learn or predict from the data. They may be able to predict when and what would be the main cause of the death of a patient.
Although it is evil to track and watch customers or to apply AI methods to predict users’ behaviors, the benefit of the knowledge is overwhelmed to be turned down. Companies equipped with users’ knowledge learned from big collected data have too many advantages in competing. They would know customers’ need to provide the appropriate services that users or customers will not find elsewhere. They can organize marketing campaigns targeting customers individually or set up traps to lure customers from other competitors. In another, they have one steps in advance in comparing to competitors.
Let’s take a look at one scenery. A mobile providers will be able to collect user’s information including handholds, purchasing behaviours (e.g., what range of phones they bought), budgets, storages, etc. Having the data from history and a model learning from big collected data, they will be easily to predict when a customer would need a new handset or new deals.
For example, they can learn from the database the number of time a customer empties the handset’s storages seeking for a new handset. They also would know the number of time users overuses the current data plan before moving to a new deal.
Having the knowledge will help the carriers to customize a deal to that a particular customer just before he/she knows that he/she seeks for a handset or new deals. In the other words, the provider knows in advance when and what services a customer will need in short coming future. Obviously, it gives the providers a chance to approach and provide the best-personalized services to customers.
They can bring the services to customers before customers would know they may need that. This business model beats completely conventional models out where providers can only propose services or offer to users when users need. In future users or customers may never be in the status of seeking for services or offer.
User surveillance is a next business generation. It is no longer a question of morality as it is the only chance for business to survive in competitive markets. The only question companies or organizations ask now: how to adopt that evil for their business.