Human bias in Machine Learning

AI is developing at the pace of a rocket. Recent developments in AI have nearly disrupted finance, banking, healthcare, and the education sector. However, bias and emotion is the only thing that is lacking in AI. Researchers are facing a huge dilemma whether or not they should include human bias in machine learning. This topic sparks debates every day in the newsrooms and dining tables across the globe.

You must be aware of the saying, “Technology is a good servant, but a bad master.” The notion of ‘mastery’ or giving orders come when technology has a bias. If machines start distinguishing people, it will be a dangerous situation for society. Nobody can deny that AI will develop superior intelligence in the coming years. That is why bias in machine learning algorithms might take us back to the era of slavery.

Unequal Development of Artificial Intelligence :Human bias in Machine Learning

If you’re someone who thinks that AI is just about predictions, then you must readjust this notion. Artificial intelligence algorithms can perform almost every task that we can think of. AI is far more than face recognition, text to speech, or NLP. Let us look at another perspective that thrashes the general dogma.

If we deploy an AI in a hiring system, then it can give us a variety of results. For instance, if you hire more males, then the model will treat them as superior. Now, even though it might benefit the company, it develops a bias against females. Mainstream AI products are facing a similar situation.

Generally, the voices of AI assistants used at homes are feminine, and so are the names. Take Siri, Cortana, Alexa, for some examples. Whereas, business AI have masculine names. ROSS, Einstein, and Watson are their patrons. These subtle things are piling up into a more sexist AI system.

How Does This Affect Us? And How Can We Change It?

These developments impose massive challenges on women and minorities. According to a study, women who hid their gender on a platform have been more successful. Furthermore, generic data suffers from a similar societal bias. Training an AI on such data with flaws automatically deems one section as inferior.

Therefore, it is high time that we keep this bias away from machine learning algorithms. AI researchers such as Kriti Sharma are working on this situation. She’s developing an artificial intelligence algorithm that can help needy women in Africa. Kriti suggests that this sexual bias in AI is changing with increasing women coders.

Summing Up : Human bias in Machine Learning

Emotion and bias have always been one of the most controversial topics of AI. Human bias in machine learning can prove lethal in the coming future. That is because of an unintentional premonition due to bias in training data. Furthermore, things like sexist/racist steps taken by humans have a similar effect on AI models.

Although we can control AI in today’s date, its power will rise dramatically in the future. If we embed a bias in current AI systems, then it’ll leave us with two options.

• To redesign complete technology.
• To surrender the minorities up to decisions made by AI.

Therefore, it's completely up to us whether we want to keep human bias away from it or not.