Apr, 2021 - By WMR
Not many technologies have been as revolutionary as artificial intelligence is. Although we are yet to experience or witness its full potential, its initial results have proven to be remarkable. Ever since its inception and recent its developments, AI has made its way into almost every field. The field of artificial intelligence now covers a vast array of possibilities for machines to help mankind. Consider the development of a machine that can create new medicines or medical treatments, design new products, or even diagnose and cure diseases. Such a machine is clearly beyond the capacity of a human, as all of these things require human intervention. Even though we are enjoying the fruits of AI, there some major shortcomings that are not fully dealt with by engineers. These issues are indeed crucial and can sway the course of how AI behaves and gives results.
One of the key issues regarding AI is the presence of bias. In simple terms, AI is provided historical data where it uses smart algorithms to create something called a propensity model, which starts making predictions. The bias comes from the type of information or historical data that is provided to AI machines. Biases can hinder the possibility of making the right decision, where businesses might get false assurance. As a matter of fact, models with biases are not really solving the learning problem that they are supposed to solve. However, AI developers have found a way to deal with this issue. Using the balanced datasets for training, typically evaluating the model should be balanced so that they do not reflect real-world biases.
Another common challenge is the quality and quantity of the data. Artificial intelligence and machine learning have an enormous potential to accelerate business operations by making better use of massive volumes of data. However, sourcing the most consistent and accurate data has remained one of the prevalent challenges since there are no standardized practices in the industry. What businesses could do is gather the data from diverse sources and filter the data so it remains relevant to the objective. Moreover, businesses can train AI models and establish data governance to get more and more precise results.
Although artificial intelligence has been around for a long time, there is still a scarcity of skilled personnel that offers desired results with machine learning technologies. Without having the right team, a business cannot achieve its objectives since AI is a far more complex technology to work with. Besides, AI has become an imperative part of the day-to-day operations in various industries where having a team of skilled working professionals who excel in machine learning is essential. To tackle this challenge, companies will have to invest in the right talent, train those resources, and add creative people to those teams that can provide solutions to unusual business problems. In fact, businesses have to create an environment of excitement around AI so that more and more people get to know about these technologies.
AI is here to stay and will be a part of almost every industry in the near future. Integrating it with your business will only enhance the daily operation and boost revenue generation with optimum customer satisfaction.