Machine learning technology has changed the opinion that machines and computers are cold and calculating. They have personalities and assumptions – but with all the semantic technology advances involved, are they as biased as humans? DATAVERSITY brought this interesting topic to our attention in their article, “Big Data Analytics: Do Machines Have Biases?“
They take a certain amount of input and produce a desired result based on their programming. You have to remember who is doing the programming. This idea has only become more pronounced as big data analytics has entered the mainstream, and while most will still think machines are unbiased, this may be a misconception.
Most experts tend to think that using more data is a significant benefit since more data means the elimination of biases. With more information, there’s a more stringent process of filtering out data that might be slanted. When it comes to analytics, the trend is to adopt machine learning algorithms. Basically, these are algorithms that tell a machine how to learn in order to come up with new solutions. This isn’t a recipe, where ingredients are put in and a clear product comes out on the other end. Machine learning is a process, where two different machines could come up with two radically different ways to solve a problem or produce a result. Essentially, machine learning is the next step toward artificial intelligence.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
