Challenges in artificial intelligence technology

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September 24, 2018
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Challenges in artificial intelligence

Technology is driving the future. In particular, artificial intelligence (A.I) is becoming an inherent part of our lives at a rapid pace. Almost every activity which is performed in the digital world can be traced and analyzed with the use of artificial intelligence. What does it mean for technology to have a definite effect on our lifestyle? What issues come with the rise of artificial intelligence? Recently, we have come across a number of controversies in the digital world regarding the use of data. A lot of information exists on artificial intelligence. Today we are going to explore a less pervasive topic – challenges in artificial intelligence. 

Unbiased Data

The algorithms which run A.I systems are designed completely on the basis of data. It is important to take the data with minimum biases. If AI has to be incorporated in our daily lives, a massive amount of unbiased data must be collected. However, a lot of data is inherently biases. With no true way to separate biased from unbiased (yet), consumers of this data aren’t getting truly objective information. 

Challenges in Artifical Intelligence Software

challenges in artificial intelligence Artificial intelligence is, at the end of the day, software. Albeit complex software, but software none the less. And software malfunctions. For instance, a self-driven car being tested by Tesla crashed into a pedestrian in California. All lose of life is relevant, and advancing technology shouldn’t come at the risk of losing even one human. Since the crash, Tesla has had to go back to the drawing board. 

Lack of Emotional Intelligence & Trust Building

We have all seen the development of chatbots powered by artificial intelligence. Though the success with this practice has grown, A.I. is still at a nascent stage. Natural language processing seeks to better the human-computer interaction, asking questions such as how do computers interpret and analyze colloquialism and natural language data. As natural language processing becomes more advanced, the gap between humans and computer interaction will shrink. Until then, we face a dilemma.

One of the challenges of artificial intelligence is that it’s difficult to understand. In spite of its ability to streamline workflows and save businesses time and money when paired with other software, many don’t grasp the concepts of A.I., making it difficult for people to maximize artificial intelligence or to build a true sense of trust. Thus campaigns exist, as I’m sure you’ve seen them, of businesses using “real humans” for their chatbot services instead of bots.

Though challenges in artificial intelligence are destined to grow as technology continues to shape the future, we see a silver lining. Artificial intelligence has massive benefits and among them is the opportunity for humans to understand ourselves more.

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