What is AI?
Artificial intelligence (AI) is a type of computer science where machines think, learn and act like human beings. Some of these machines perform tasks just as well as humans, making AI incredibly valuable for various industries and personal use cases.
As a future data engineer or scientist, it’s almost certain you will be working with AI in some capacity. So, what is AI? Now’s the perfect time to learn this answer and discover the benefits and drawbacks of AI technology.
AI involves building machines to perform tasks that typically require human intelligence. Think about a self-driving car. This technology uses AI to move between two locations without a human operator. The vehicle thinks and acts like a real driver as it brakes, accelerates, and travels to its desired destination.
In 1956, computer and cognitive scientist John McCarthy coined the term “artificial intelligence” at a conference at Dartmouth College. Even though this technology was in its infancy, McCarthy—now known as the “father of AI”—realized the incredible potential of making intelligent machines. Today, there are various applications of AI, including natural language processing, machine vision, and speech recognition. All of these applications assist engineers when building machines that simulate human intelligence.
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Benefits of AI
Artificial intelligence has numerous benefits, including:
Repetitive Task Automation
AI automates the repetitive tasks humans usually do, freeing up resources in multiple industries. Take a manufacturing plant, for example. AI can schedule repairs for broken equipment, removing the need for a human to complete this task. The person responsible for scheduling repairs can focus on other jobs, which improves productivity in the manufacturing plant. Other examples of how AI can automate repetitive tasks include:
- Checking documents for errors
- Assigning jobs to team members
- Automatically responding to customer service requests via chatbots
Data scientists benefit from AI when analyzing data in various scenarios. Machine learning, a subset of AI, can analyze structured and unstructured data in systems, allowing scientists to make more accurate predictions from data sets. It also helps scientists identify patterns and trends that benefit their companies.
Say an organization wants to identify workflows that save money. A data scientist can use AI algorithms to analyze data from multiple systems and discover cost-cutting strategies that improve the organization’s bottom line. While data analysis is possible without AI and machine learning, these technologies make life easier for data scientists.
Ability to Diagnose and Treat Diseases
One of the most valuable benefits of AI is its ability to diagnose and treat various diseases. For example, AI-powered brain-computer interfaces (BCIs) can restore neurological abilities in people who have experienced brain trauma. Innovations like BCIs free up time and resources for hardworking healthcare teams and can improve lives.
Drawbacks of AI
AI will dominate the business landscape for years to come. However, it still has some kinks that engineers and developers need to iron out:
- Creating machines with human-like capabilities is an expensive feat. The technology required for AI costs developers tens of thousands of dollars, which limits future innovation.
- AI critics believe this technology will result in widespread job losses as intelligent machines replace human workers.
- While AI can replicate human intelligence, machines can’t develop real emotions and don’t form the meaningful connections that people can.
What Is AI? Final Word
You will likely use AI as you embark on a career as a data engineer or scientist. Understanding “what is AI?” and what this technology offers will increase your chances of finding a high-paying, rewarding role in your respective industry.
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