Artificial intelligence (AI) is a technology that utilizes algorithms and computer systems to enable machines to reason, think, and make decisions independently and without direct human control. AI has been used since 1956 to automate repetitive jobs, personalize customer experiences, create predictive models for dangerous situations, and even create virtual assistants that interact with humans. AI’s ability to learn from data has allowed it to produce outcomes superior to those coded by software developers. AI is continually being integrated into our lives more deeply and can now be found in everything from autonomous vehicles on the road to home assistants in our living rooms. This guide will dive deeper into what artificial intelligence is, how it's used, and what we can expect from it in the future.
AI is the theory and development of computer programs that can do tasks and solve problems that usually require human intelligence. Things like visual perception, speech recognition, decision-making, and translation are capabilities that would typically rely on human intelligence. Computer programs can now engage in automatic deep learning to absorb massive amounts of data and solve tasks in ways that mimic human intelligence.
John McCarthy is widely credited as the inventor of artificial intelligence. He developed some of the first algorithms for computer learning in 1956, which laid the groundwork for research into symbolic logic and representation. Throughout his five-decade career as a Professor of Computer Science at Stanford University, McCarthy continued to expand on his ideas and explore how computers could be programmed to think like humans. Today, his influence is still felt through robotics and natural language processing advancements.
Artificial intelligence and the algorithms that make this intelligence run are designed by humans. While the computer can learn and adapt or grow from its surroundings, at the end of the day, it has limitations. Human intelligence has a far greater capacity for multitasking, storing memories, partaking in social interactions, and having self-awareness. Artificial intelligence doesn't have an IQ, making it very different from humans and human intelligence. There are many facets of thought and decision-making that artificial intelligence simply can't master. While AI applications can run quickly and be more objective and accurate, their capability stops at being able to replicate human intelligence. Human thought encompasses so much more than a machine can be taught, no matter how intelligent it is or how it was coded.
Artificial intelligence operates by processing data through advanced algorithms. It combs large data sets with its algorithms, learning from the patterns or features in the data. There are many theories and subfields in AI systems, including:
- Machine learning. Machine learning uses neural networks to find hidden insights from data without being programmed with what to look for or conclude. Machine learning is a common way for programs to find patterns and increase their intelligence over time.
- Deep learning. Deep learning utilizes vast neural networks with many layers, taking advantage of their size to process massive amounts of data with complex patterns. Deep learning is an element of machine learning, just with larger data sets and more layers.
- Cognitive computing. Cognitive computing aims to mimic human-like interaction with machines. Think of robots that can see and hear and then respond as a human would.
- Computer vision. In AI, computer vision utilizes pattern recognition and deep learning to understand a picture or video. This means the machine can look around, take photos or videos in real-time, and interpret the surroundings.
AI can be programmed to understand how humans think but only ever functions within the confines of its digital boundary lines, never being able to fully comprehend the complexity of emotions or higher-level thinking like humans can. Therefore, it's important to note that AI lacks certain levels of proper human understanding, moral judgment, and ethical decision-making capabilities that make us unique individuals.
AI can be divided into two main categories: soft and hard. Soft AI is the more commonly understood form of AI, which focuses on the automation of tasks within a given set of parameters. It’s also widely referred to as "Narrow AI." Meanwhile, Hard AI, also known as "General AI," uses methods such as machine learning, in which an extensive collection of data can be used to create a system that can adapt itself without having explicit programming for every action.
Narrow AI, also referred to as weak AI or artificial narrow intelligence (ANI), is a growing research field focusing on developing machines or computer systems that exhibit intelligent behavior. These systems are designed to specialize in one domain, solving specific tasks or problems within certain parameters. They require human-like problem-solving and reasoning, such as visual perception, language processing ability, and the power to differentiate between sounds and voices to analyze data, consider multiple alternatives. and achieve desired outcomes. Examples of narrow AI include self-driving cars, facial recognition systems, and digital assistants.
Artificial general intelligence (AGI) is an ambitious type of artificial intelligence that seeks to create machines with the intellectual capabilities of humans. AGI will involve assigning devices enhanced problem-solving capabilities and allowing them to learn a much more comprehensive array of skills than other AI implementations can. Currently, many AI technologies can carry out specific computing tasks in isolation or with minimal environmental understanding. However, AGI would allow machines to learn from experience and apply knowledge across various tasks and environments. This would make it possible for machines to understand language and images, become more adept at communication, and possess creative abilities similar to humans. AGI could revolutionize how many industries operate, enabling robots to unify their various tasks into one highly efficient unit.
Broadly speaking, there are four main types of AI:
- Reactive Machines detect patterns in data but cannot use the knowledge gathered in the past to inform decision-making in the present.
- Limited Memory Machines store previously encountered information so that it may be used as reference material when making decisions.
- Theory of Mind Machines simulate human cognitive processes, such as reasoning, to interact with humans more naturally and effectively.
- Self-Aware Machines attempt to actively regulate and evaluate their own behavior by considering both external stimulation and internal feelings or drives.
AI has emerged as a powerful tool for businesses and organizations in many industries. AI-driven technologies are being used to automate processes, personalize products and services, analyze large data sets, and uncover trends more quickly and accurately than ever before. Furthermore, AI is being employed to improve healthcare systems, optimize energy consumption, create customized marketing campaigns, facilitate language translation, enhance cybersecurity measures, and provide predictive forecasting based on various industry metrics. AI promises to continue to revolutionize how we work and live by automating jobs and simplifying everyday tasks.
Some of the many commonly known uses of AI include:
- Voice recognition
- Self-driving cars
- Online shopping
- Streaming services
- Healthcare technology
- Factory and warehouse systems
- Educational tools
AI systems are already impacting our lives, and the door is wide open for how AI will affect us in the future. AI-driven technology will likely continue to improve efficiency and productivity and expand into even more industries. Experts say there will probably be more discussions on privacy, security, and continued software development to help keep people and businesses safe as AI advances.
While many people are worried that robots will take their jobs, the truth is that many fields are reasonably safe from automation. Areas like IT will continue to be needed to adopt the new technologies and security systems that make AI run. The roles of healthcare professionals and teachers also won't be at risk—the work they do directly with patients of all ages cannot be automated. While some processes can be automated in business, human instinct, decision-making, and relationships will always be vital for the future.
Artificial intelligence is a rapidly growing field. To get into AI, you should ideally start with a degree in computer science or a related field. Once your educational foundation is set, you can hone your skills by participating in an internship or completing industry certifications. Joining professional organizations and even attending regional conferences and events can also provide excellent opportunities to connect with key decision-makers, including:
- Machine Learning Engineers
- Data Scientists
- Business Intelligence Developers
- Research Scientists
- Big Data Engineers/Architects
- Software Engineers
If one of these roles sounds interesting to you, consider enrolling in an online, competency-based bachelor’s degree program at WGU. Our flexible curriculum is designed with input from industry experts to teach you skills like logic, architecture and systems, data structures, AI, and computer theory. The future of AI is expected to become an integral part of our everyday lives, and professionals working in AI will be instrumental in bringing forth breakthroughs in various sectors, creating opportunities that may never have been dreamed of before.