It is now admitted that technology area has deeply transformed our world, from our way to consume, our way to travel, our way to communicate with relatives. Lana Wachowski, Matrix’ movie’s producer, lit the fuse in 1999, smartly explaining to her audience that we lived in a world of data. Today’s scientists are the starting point of the new usage of the numerical patterns of zeros and ones.
By linking complex mathematics algorithms with huge sets of data coming from databases all around the world let the data scientists find invisible paths and relations between variables. Medicine, retail, insurance, banking are currently the most valuable places to start with data analysis. What is the point ? What is the goal ?
Depending on the area, data can be used to predict human behaviors, to validate a loan request or to help medicine improve diseases understanding. The winning skills basket of a data scientist is made of statistics deep understanding, computer programing, a deep knowledge in database architecture, as well as a lot of transversal skills, such as teaching and popularizing. Those hard-to-find profiles usually work at decision level in private compagnies, giving some precious hints to the top management regarding business’ concerns, such as customer acquisitions, customer relationship improvement, products’ evolutions.
In this particular case, the goal is to develop the core business. Google itself is strongly investing on Data Science. For example, Google’s self-drive car is using a combination of very complex machine-learning algorithms, such as neural-networks. Inherited from mathematics researches and adapted by computer programmers, those complex systems’ main ability is to learn from their environment. It means that data from a particular situation that the car will face will be used in the future as an experience for the car. Without any driver’s assistance.
Real-time learning is also used in retail distribution, to be able to make adequate offers to potential customers browsing a website. Data science leads to privacy concern. To what extent can our data be used by other to manipulate us ? To influence us ? Legal data gathering systems, such as most of mobile applications, ask for your permission to get your position, access your emails, etc. What if those data come in the hands of badly intentioned people ? Banking security issues, viruses, geo-tracking, pressure on customers.
At the time of the technology revolution, hot-topics start to emerge, one of the main happens to be security. Nowadays, entire study programs are dedicated to cybersecurity, everywhere in the world. Artificial intelligence is one of the main topics in large technology groups, as they are now understanding its potential benefits. Replacing a broken-arm with a bionic one is not particularly dangerous if the engineers solved all technical issues. We are free to make our decisions, but we have to keep in mind that consequences don’t happen in our circle of influence. Personal ethic and laws are then the major topics to work on.
The « digitalization » is unstoppable, always remember that the decision is yours.