The term AI and Machine Learning (ML) have created a lot of buzz over the past several years with all the talk on autonomous vehicles, data analysis on a massive scale, and the world’s leading organizations relying on machine learning and deep learning algorithms to improve business intelligence and refine business strategy. It was also considered to be among the most advanced technologies and techniques used to deploy artificial neural networks that are expected to reach between $3.5 trillion and $5.8 trillion in annual value across many industries. Those dealing in computer science and engineering industries will find it beneficial to implement Artificial Intelligence and Machine Learning as they will be in high demand with the evolution of these technologies.
With the ever-increasing demand for modern technology is most businesses today, there have been plenty of changes experienced in the workplace due to the implementation of these technologies. One study has found that roughly 30% of activities from about 60% of occupations can and, in some instances, are automated. It’s, therefore, safe to say that automation has a major impact on today’s working environment and it’s all thanks to Machine Learning and AI There are very few things that cannot be automated, at least in part through the latest developments made in AI and ML
Computer Science Leveraging AI and ML
Both employees and employers can benefit from these technologies. Statistics show that roughly 20% of an employee’s time is spent on repetitive administrative tasks that can be easily done by machines. Similarly, CEOs and entrepreneurs can automate different fields within their workplace and save large amounts of time, which will further improve the performance and overall production of their organization. Below are several examples that help them achieve this level of optimization.
The Development of More Secure Systems
Every business owner will want to have their confidential data secured from various security breaches. It’s, therefore, important for the IT industry to develop secure systems and mobile applications for both the business and the users, themselves. Every organization will need to protect its data and the data of its customers from being stolen by cybercriminals. Between 2005 and 2018, data breaches in the United States have increased significantly, reaching more than 446.5 million private records being exposed. But when an AI system is introduced, it can help secure that data from all sorts of cyberattacks.
With the help of advanced search algorithms, Artificial Intelligence (AI) will not only help identify potential threats and data breaches in real time but also provide the necessary solutions to avoid those issues in the future. And when it comes to computer science, data security becomes even more relevant.
Process Automation
One of the biggest advantages of this technology is that it can automate many different types of work that can be done without any human interaction. By making use of deep learning and computer science, companies will be able to pass extra miles in automating their backend processes. This will further reduce the amount of wasted time as well as the direct human interaction in various activities within the business.
Numerous AI-enabled methods will improve with time and will also improve business productivity along with them. This will also help decrease the incidence of human error and help manage internal processes more accurately and systematically than before. All research and development tasks can also be completed faster and more accurately, providing great insights for future decision-making.
Server Optimization
Hosting servers have millions of inbound requests on a day-to-day basis. These servers need to provide an outcome in relation to the searches made by users. But due to the continuous flow of queries, some of these servers may end up slowing down and become unresponsive. Artificial Intelligence can be of great help in optimizing the host server and enhance the operations, boosting customer service. Due to the increasing demand in AI, the demand for skilled and competent employees is also increasing. In fact, the talent gap in the computer science sector is among the highest in the world.
Quality Assurance
This concept refers to the process of ensuring that the right tools and methods are used throughout the entire software development lifecycle. As such, developers can use AI-based tools to fix any bugs and issues within their software and mobile applications. They can implement Artificial Intelligence-based methodologies to automatically repair any errors that can occur during the development and deployment phase. It will also ensure that these bugs and glitches will not be present in the software before it will be released onto the market.
How Machine Learning and Artificial Intelligence Are Affecting Computer Science
As mentioned, more and more companies are starting to implement various AI and machine learning solutions into their systems. It’s important to keep in mind that some of these organizations don’t even fully understand how they work. In 2020, it’s estimated that around 20% of companies have at least some employees fully dedicated to monitoring and guiding a neural network. In addition, around 10% of IT hires in customer service will be responsible for writing scripts for chatbots; this being just one application of AI
While by-and-large, this push will provide numerous benefits, it will also have several side effects. Firstly, some novel projects that may have the potential to provide even more impressive results than machine learning will be pushed aside as many talented computer scientists and engineers flock to AI and ML positions. This means that the next major breakthrough in computer science could be pushed back.
A Lack of Diversity in AI
There is also a major lack of diversity when it comes to the AI and machine learning fields. Experts in the field are predominantly white males, which is a trend that is also affecting their body of work. For instance, facial recognition technologies have had problems recognizing people with darker skin tones, since most of these systems were developed and implemented by mostly white people. And as an interest in AI and ML will continue to grow, this issue is bound to appear in more places. Artificial Intelligence will be in charge of search results, choosing which news articles it will show to people, while also gatekeeping access to important files and sensitive data. And since the field will likely expand faster than the diversity problem will be resolved, it’s bound to introduce new problems in the future. These will be both for consumers as well as for the computer engineers and scientists trying to stay ahead of the issue.
It Will Be Harder to See Where Problems Arise
Even though AI and ML will streamline and optimize many processes, they will also introduce an additional level of complexity that will make certain problems harder to solve. For the most part, a ML algorithm isn’t just a set of strict instructions that the machine will follow. Instead, they are better described as a flexible set of learning processes for the machine to abide by. The machine will collect data from millions of examples on whatever subject it’s studying and will gradually learn about the concept.
While there’s plenty of evidence that shows the machine getting closer and closer to its end goal, sometimes even surpassing the human-level skill, developers aren’t able to tell which pieces of information actually led to a specific conclusion. To put it differently, it will be extremely difficult to determine where and why machine learning algorithms work and don’t. As AI and machine learning become more commonplace, this complex issue will become an increasing problem for computer scientists.
Automating Automation
There will probably come a time in the foreseeable future where the process of creating new machine learning will also be automated. Such a multi-layered approach to computer science would open up a new branch of study that will need the creation of an entirely new way to look at problems within the computer industry. It’s pretty obvious that Artificial Intelligence and Machine Learning aren’t simply passing trends, even if there will be newer computing breakthroughs in the near future. Computer scientists will have the responsibility to predict and adapt themselves to the massive changes that will be in store for the industry in the years to come, as AI and ML will become even more sought after than it is today.
Takeaway
Artificial intelligence is changing many sectors, particularly information technology because of the amount of data sets it can process at superspeeds and ability to learn faster than the human brain. Together with MyComputerCareer, you can be part of the future of AI and Machine Learning, as well as what they can bring to the Computer Science sector in today’s ever-increasing digital world. We will provide you with valuable IT certificates from leading organizations such as Microsoft, Cisco Systems, CompTIA, and EC-Council. Contact us today, and start your career in the industry!