What Is Artificial Narrow Intelligence?

Artificial narrow intelligence (ANI) specializes in performing a single task or a group of tasks within a specific domain. You may also hear people refer to this type of artificial intelligence (AI) as weak AI due to its task limitations. ANI often matches humans in performing various functions. 

Data from the CompTIA IT Industry Outlook report reveals that 55 percent of business organizations are already implementing AI, with 22 percent doing so aggressively across various workflows [1]. ANI is one option that companies may explore. Read on to learn more about ANI, including how it differs from other forms of AI, what it's used for, who uses it, and more.

ANI vs. artificial general intelligence (AGI) vs. artificial superintelligence (ASI)

All AI falls into three types based on capabilities. To better understand artificial narrow intelligence, artificial general intelligence, and artificial superintelligence, it helps to consider how each differs in terms of capabilities. For example:

Examples of artificial narrow intelligence

Artificial narrow intelligence spans various industries, including entertainment, finance, health care, and retail. It demonstrates both the limitations of current machines and the potential for machines in the future.

Four examples of artificial narrow intelligence include:

1. Expert systems 

These computer systems can solve complex problems within a specific domain by accessing a knowledge base and using an inference engine. The performance of expert systems mimics human experts’ problem-solving and decision-making abilities. Examples of expert systems include machines used to diagnose various health conditions.

2. Chatbots and digital assistants

These computer systems can help people and companies automate tasks and make processes more efficient and cost-effective. Chatbots answer questions or guide users by simulating a human conversation through voice or text. Digital assistants, meanwhile, perform tasks that assist users throughout the day—like setting an alarm or playing a movie when asked.

3. Predictive maintenance models

These models use sensors measuring data like temperature, vibration, and humidity to detect irregularities in machine operation. This can help manufacturing companies and other types of businesses know when to repair or replace machinery. The ability to schedule repairs or replacements reduces downtime and saves businesses money.

4. Recommendation engines

Recommendation engines analyze data like what clothing styles a customer buys or what movies they watch to make recommendations based on past purchases. This type of narrow intelligence helps boost customer engagement, broaden customer reach, and improve customer retention—all benefits that can help increase revenue.

What is artificial narrow intelligence used for?

People or businesses use artificial narrow intelligence to complete specific tasks with the aid of machines instead of humans. Machines access data from a particular source and use it to perform a singular task or a series of related tasks. Because these machines lack human-like intelligence, they operate only within the confines of their programming. 

ANI can help improve business operations and enhance daily life at home. For example, manufacturing machines can produce products more quickly and safely than humans, and digital assistants can play music or videos when asked.). In addition, many machines get better at tasks over time through programmed training techniques called machine learning and deep learning. 

Who uses artificial narrow intelligence?

As mentioned, the use of artificial narrow intelligence spans many industries. Types of professionals that use ANI and how they use it include the following:

• Data analysts: For help with data collection, data cleaning, and data organization.

• Investment analysts: To analyze trends in stock performance. 

• Manufacturers: For automated product assembly, predictive machine maintenance, and quality control.

• Marketers: To analyze customer data and deliver targeted advertising for higher sales.

• Product developers: To speed up product design processes by analyzing data and optimizing product blueprints.

• Radiologists: To detect abnormalities in medical images like X-rays that the human eye may miss.

• Surgeons: For analyzing data involving a patient's specific anatomy to perform a more precise and accurate surgery.

• Teachers: To detect plagiarism on essay tests and to automate grading on multiple-choice tests. 

Benefits and challenges of artificial narrow intelligence

Simplifying workflows is just one of the potential advantages of ANI. Due to its specific focus, artificial narrow intelligence offers a variety of benefits to users. Common benefits include:

• Ability to work around the clock without tiring

• Automation of tasks considered repetitive or dangerous 

• Strengthened decision-making as a result of quick data processing

• Task performance as good as (or better than) humans

Although ANI offers important benefits, it also presents some challenges to users. One common challenge (dubbed the "black box problem") involves the inability of experts to completely understand the decision-making process used by some types of narrow AI, including recommendation engines that offer movie suggestions. Additional challenges of narrow AI include:

• Ability for hackers to penetrate ANI systems

• Inability to perform tasks outside of defined programming

• Incorrect information or bias in data that may deliver skewed results

• Vulnerability to human error due to reliance on human programming

How to start working in artificial narrow intelligence

If you're interested in a career in artificial narrow intelligence, it may help to follow a few key strategies, starting with building helpful workplace and technical skills. Additional steps include gaining foundational knowledge and getting practical work experience.

Skill-building

Building a robust skill set ranging from analytic thinking to familiarity with programming languages can help as you travel down an AI career path. Workplace skills you may wish to build include:

• Ability to communicate verbally and in writing

• Analytical skills

• Attention to detail

• Flexibility

• Problem-solving

Some technical skills that can help in this career include:

• Familiarity with big data and database management

• Knowledge of data analysis

• An understanding of data manipulation tools

• Knowledge of programming languages like C/C++, Java, and Python

• Proficiency in AI platforms like Google Cloud AI, IBM Watson, and Microsoft Azure AI

Education

To build the foundational knowledge you need for a career in narrow AI, you may want to consider getting a bachelor's degree in a field like computer science, data science, engineering, or mathematics. You may get by with a certification instead of a bachelor's degree for some entry-level positions. It all depends on the available job and the employer in question.

Practical work experience

Practical work experience might help you get an entry-level position in AI. To gain practical work experience, consider these methods:

• Apply for an internship with a local AI company.

• Participate in AI research while you're getting your bachelor's degree.

• Attend AI conferences or engage in AI projects accessible through AI community websites.

Build a foundation in artificial intelligence on Coursera

Currently, all types of AI fall under the narrow AI category, where systems excel at specific tasks but lack the broad understanding and adaptability of human intelligence. Knowing more about narrow AI can help you decide if you want to pursue it as a possible career choice. 

For a quick overview of AI, take DeepLearning.AI's AI For Everyone course. There, you'll learn what AI can realistically do and not do, how to spot opportunities to apply AI to problems in your own organization, and what it feels like to build machine learning and data science projects.

Top build job-ready AI skills to enhance your career, enroll in the IBM AI Foundations for Everyone Specialization. Learn foundational AI concepts, explore AI tools and services, and engage with AI environments through hands-on projects.

To learn how AI can address complex real-world problems, explore DeepLearning.AI’s AI For Good Specialization. Here, you’ll build skills combining human and machine intelligence for positive real-world impact using AI in a beginner-friendly, three-course program.