Machine learning has changed the way we do business. However, they have been many victims of the changes machine learning has brought forth. The reason why machine learning is so spectacular is its amazing ability to make accurate predictions that most people would know about. In fact, the right ML models can enable you to make predictions before the person even recognizes what is going on.
The infamous story of how Target sent out pregnancy flyers comes to mind. Target was able to figure out that a teenage girl was pregnant before her parents. Obviously, that turned out badly for the reputation of Target. It is also crucial to remember that this happened almost ten years ago, meaning that machine learning algorithms have gotten a lot better recently.
Data privacy is now becoming a major concern because of how powerful some of these algorithms can be. In fact, a data protection policy might be a crucial component in future machine learning projects.
Accidents Can Happen
One of the biggest problems with ML models is that they will eventually become so accurate that they make privacy a major problem. Because of that, machine learning privacy will have to become a field that researchers put time and effort into solving. Problems with privacy are so serious that they could even potentially affect national security.
An interesting example is how a fitness app was able to use GPS tracking information to locate secret military bases on a map. Obviously, this information getting into the wrong hands poses a serious threat to national security. Not just that, but it could also potentially cause problems when that data leaks out accidentally. Good data privacy will mean having a good data protection policy.
The Regulation Question
As you can see, good ML models pose a serious threat to data privacy. A dilemma for companies creating these models is whether they should self-regulate or wait for governments. The fact of the matter is that regulation is coming, whether you want it or not. However, the best solution is for companies to get ahead of that trend. If the industry acts like it is trying to self-regulate, the laws may not be as strict as they would be.
Another major issue will be machine learning in facial recognition. As seen in countries like China, facial recognition technology has the potential to be quite oppressive to citizens. Companies will have to figure out effective strategies for dealing with those potential problems. So far, governments are not waiting, and they are banning facial recognition technology in certain scenarios.
Making Sense of Everything
With everything going on, companies need to understand how to make ML models work for them. The smart machine learning engineers will be the ones that take advantage of trends. The trend in machine learning privacy will be regulation and encryption.
By developing these solutions, you can help your industry not get regulated out of existence. However, the major question will be whether you can use technology to solve a problem that technology has created.