What is Artificial Intelligence

Artificial Intelligence (AI) definition

What does artificial intelligence mean, and how would you explain artificial intelligence? Basically, an overview of artificial intelligence, commonly referred to by its abbreviation AI, is the ability of a machine or computer program to think and learn. The concept of AI is based on the idea of the development of machines (not hardware or computers) capable of thinking, acting, and learning like humans.

As for who invented artificial intelligence, the term dates back to 1956 and belongs to Stanford researcher John McCarthy. He created this term and defined AI's key purpose, objective, and goal as a sub-field of the computer science industry.

A more nuanced meaning, explanation, or definition of artificial intelligence is that AI is a modern, progressive, interdisciplinary concept that studies the possibility of inventing machines capable of interacting with their environment and acting upon the received data in a manner considered intelligent.

While some people falsely consider AI to be a technology, the more accurate approach would be seeing it as a broad concept in which machines are able to deal with tasks in a way we would deem “intelligent” or “smart.”

There are certain things a machine/computer program must be capable of to be considered AI. First, it should be able to mimic our human thought process and behavior. Second, it should act in a human-like way—so be intelligent, rational, and ethical.

It is worth mentioning that the AI concept relates both to Weak AI and General AI with cognitive functionality.

What is Generative AI?

Generative AI is a branch of artificial intelligence that creates a variety of content, including code, text, and images, using training data. The most popular generative AI tool is ChatGPT, which you have likely used for research purposes, but you can also use it to write text (emails, letters, social media captions, etc.), create new images, and even create downloadable documents like spreadsheets.

For instance, you can upload your photo to ChatGPT and ask it to make it look more professional. The tool will produce a photo with enhanced posture, clothes, and more to ensure you put your best foot forward on LinkedIn.

But Generative AI is nowhere near perfect. It’s still in its early stages of development, so it can make mistakes and can be misused.

AI regulation and governance

Governments and other organizations are finding it more and more crucial to regulate AI as it develops and is used more frequently.

The laws governing AI in different nations are broken down as follows:

• The European Union (EU): The EU AI Act establishes stringent guidelines for high-risk applications and classifies AI systems based on their level of risk.
• United States (US): The US is looking into regulating AI. For example, the Blueprint for an AI Bill of Rights seeks to prevent discrimination, safeguard data privacy, and clarify how AI makes decisions.
• Other regions: Canada, China, and the UK are also actively investigating AI governance that limits deepfakes and addresses how AI uses data.

Stanford has outlined a helpful AI FAQ on these topics.

How does artificial intelligence work?

AI helps humans boost productivity and streamline daily tasks such as reading, writing, and problem-solving. It achieves this by mimicking human thinking, though it can’t reflect. Since it is not human, it can only offer information and solutions based on the data it’s been given. The more information it receives in training, the better it can respond to commands.

Explore how it works in detail in the sections below. Consider these types and features of artificial intelligence.

1. Machine learning

Machine learning teaches AI systems to learn from data instead of following a set of hard rules. The idea is to help AI technology think like a human by feeding it large amounts of information as opposed to dictating how it should respond to commands.

Think about the shows Netflix suggests you watch and the posts that show up in your social media algorithms. Machine learning drives those suggestions based on your past activity on those platforms, making it actively adaptive.

2. Deep learning

Deep learning is a more advanced subset of Machine Learning that processes data in multiple layers known as neural networks. These networks allow the system to understand and process complex patterns in larger datasets. Deep learning helps computers learn by example, enabling AI to differentiate between objects. It is used in speech recognition.

3. Neural networks

Neural networks are a type of Machine Learning that works similarly to how the human brain processes information, except that it uses mathematics and artificial neurons. Neural networks enable AI systems to learn and improve as information passes through various layers.

4. Natural language processing (NLP)

NLP helps artificial intelligence understand, process, and respond to large volumes of text and audio, saving you hours of work. For example, Grammarly uses NLP to check your text, correct it, and suggest improvements.

5. Computer vision

The processing of visual data, such as images, videos, and live camera feeds, makes computer vision a little different. AI does this by recognizing, contrasting, and categorizing pixel patterns. Facebook, for instance, automatically recognizes and tags people in photos using computer vision.

Artificial intelligence benefits

It's impossible to argue against the importance of artificial intelligence. From automation to resolving problems, its potential is limitless, and its capabilities are incredible.

Continue reading to find out more about the benefits of artificial intelligence.

1. Automating repetitive tasks

AI can free up your time to work on more complex tasks by taking over monotonous ones. For instance, it can sort files, set up appointments, and produce intelligent email responses fast.

2. Solving complex problems

Artificial intelligence tools can analyze large or complex datasets and offer solutions or recommendations in a fraction of the time it would take you. The industries of manufacturing, finance, and medicine particularly benefit from this.

3. Reducing human error

AI systems don’t have fatigue like humans, so they can reduce certain types of mistakes—but they can also introduce new risks if trained on biased or low-quality data.

4. Improving customer engagement

AI tools like chatbots enhance customer experience through personalization and recommendations. They also respond to customer queries quickly, reducing delays and potentially improving customer satisfaction.

5. Advanced decision-making process

AI helps humans, especially in the workplace, make smarter and faster decisions based on previous data inputs. It can come in handy for forecasting trends and providing strategies for better efficiency.

6. Round-the-clock availability and constancy

One advantage of AI is that it is always ready to solve problems, increase productivity, or make tasks easier when necessary. By counteracting some of the disadvantages of human limitations, like getting bored, tired, or distracted, AI becomes dependable around the clock.

Where Is AI Used?

Many people associate AI with the distant future. They incorrectly believe that despite all the buzz around AI, the technology is unlikely to become a part of their lives anytime soon. Little do they know how many devices, routines, and services they love are already affected by it.

Take Siri or Alexa—personal assistants that have already become the new normal for thousands of people around the globe. These and similar intelligent gadgets are able to recognize our speech (read: "understand what we want or need"), analyze the information they have access to, and provide an answer or solution. What is remarkable (and a little scary) about such assistants is that they are programmed to continuously learn about their users until the point at which they can accurately anticipate their needs.

Spotify, Pandora, and Apple Music are some other touching points between AI and you. These services are capable of recommending music based on your interests. They monitor your choices, insert them into a learning algorithm, then suggest music you are more likely to enjoy. This particular use of AI is probably one of the simplest, but it does a good job of helping us discover new songs and artists.

AI is making headway in areas you might least expect it to. For example, when you find short news stories on the Associated Press or Yahoo!, chances are they were written by AI. The current state of AI already allows for some basic robot writing. It might not yet be ready to compose in-depth pieces or creative stories, but it does a pretty good job of writing short and simple articles like sports recaps and financial summaries.

Other examples in use today include smart home devices like Google's NEST, self-driving cars such as those produced by Tesla, and online games including Alien: Isolation.

And even if you use none of the above, you still interact with AI daily while surfing the internet in your browser. It is widely used in advertising to target you with the most relevant ads, personalizing messages and putting them in the places where they are most likely to impact you.

How to use artificial intelligence

Artificial intelligence is used across various disciplines and everyday tasks to improve productivity, efficiency, decision-making, and customer satisfaction.

Here’s how to use AI in various disciplines:

1. Fraud detection
2. Customer service
3. Finance & banking
4. Personalized marketing
5. Human resources and recruitment
6. Retail
7. Healthcare

Here’s how you can use it effectively:

1. Fraud detection

AI prevents fraud by using predictive analytics to meticulously flag suspicious activity that human beings might miss. This ranges from general anomalies, like consecutive credit card transactions, to granular-level checks like identifying unusual patterns in documents. The result? Mitigating fraud in real time and preventing major losses.

However, in order to prevent inconveniences, fewer legitimate transactions are blocked because AI tools can distinguish between anomalies and real fraud. AI tools continuously improve and develop their systems to offer strong fraud protection by monitoring fraud trends.

2. Customer service

Businesses can enhance their customer service and increase customer satisfaction with AI tools. Chatbots enable businesses to not only respond to customer queries in real time with automated responses but also help guide customers to the right resources or web pages to solve their problems. Otherwise, they can collect customers’ information, which real employees can use to contact them.

3. Finance & banking

AI can help with compliance, approvals, credit scoring, and more. AI technologies can assist in customizing the digital and mobile experience to swiftly and precisely satisfy customer needs.

Through ongoing monitoring and insights, AI automation can strengthen cybersecurity efforts, increase accuracy, and streamline workflows, just like in other fields. By managing time-consuming tasks like responding to commonly asked questions users may have about the bank or branch, AI can also increase productivity and efficiency.

Finally, AI powers innovation by informing the production of new products and services to stay ahead of industry trends and demands.

4. Personalized marketing

Businesses used surveys and conventional marketing strategies in the past to learn what customers wanted. They can now obtain that information directly from the source, focusing on accuracy for individuals rather than groups, thanks to artificial intelligence.

Machine learning studies user behavior to personalize marketing efforts and improve targeting for better results. Additionally, it adapts to customers' evolving needs and habits. For example, Netflix uses machine learning to offer you personalized recommendations based on your most recent activity on the platform.

5. Human resources and recruitment

With few employees and ineffective systems, the human resources and hiring procedures can be a logistical and administrative nightmare. AI facilitates the hiring stage from screening candidates to onboarding and training.

By creating precise job descriptions, tailoring them to the company's voice and culture, and vetting hundreds or even thousands of applicants based on important factors like experience and job titles, AI expedites the hiring process. It can even find potential candidates on career platforms like LinkedIn to save team members time and find the best talent based on experience and skill sets.

6. Retail

AI delivers personalized shopping experiences. It adapts offers to reflect user interests, helps find specific or similar items using image search, and answers common questions through chatbots on shopping apps and platforms. Beyond that, AI helps streamline processes like inventory and forecasting, boosting productivity and accuracy while cutting costs.

7. Healthcare

AI in healthcare simplifies administrative tasks like scheduling appointments, processing data, and processing claims. Employees can now devote more time to critical tasks like patient care. But AI goes beyond performing mundane tasks. It simplifies the diagnostic process and assists in prevention. It can also offer solutions for early intervention and help with implementing care effectively.

Will AI Take Over?

Some people claim that AI is still in its infancy. Others assure us that we are only a few years away from AI gaining control over humanity. The truth lies somewhere in between. According to the most trustworthy forecasts out there, AI will outsmart humans at virtually everything within the next 45 years as its usage increases. Obviously, this won't happen overnight. Certain spaces or industries will be falling under AI's spell one by one.

Experts predict that within this decade, AI will outperform humans in relatively simple tasks such as translating languages, writing school essays, and driving trucks. However, more complicated tasks like writing a bestselling book or working as a surgeon will take machines much more time to learn. AI is expected to master these two skills by 2049 and 2053 accordingly. It’s worth mentioning that this data is based on a survey from AI researchers linked above; it is not a guarantee.

It is obviously too soon to talk about AI-powered creatures like those from Westworld or Raised by Wolves stealing our jobs or, worse yet, rising against humanity, but we are certainly moving in that direction. Meanwhile, top tech professionals and scientists are getting increasingly concerned about our future and are encouraging further research on the potential impact of AI.

It looks like those who understand the full potential are more scared of it than those who only know the basics. A recent scandal between Google's executives and employees may serve as proof. In 2018, employees of Google demanded the company stop working on a so-called "Pentagon Project" as they were afraid of being involved in the business of war.

The project, officially known as "Project Maven," was meant to use AI to make it easier to open and classify images of people and objects shot by drones. The potential danger is that life-or-death decisions on what needs to be bombed would have been made without human involvement.

The military explains that their only intent was to reduce the current workload and minimize the number of tedious tasks performed by humans—something AI is exceptionally well-suited for. Given that people's lives might be at stake, can these tasks even be called tedious? And there's another critical question. In a world like this, who will be responsible for killing innocent people? Us? Or our machines?

It is widely believed that one day, AI will exceed human performance and extend beyond human control. With so many fearful articles out there, questions like "Is AI safe?" or "Is AI bad for people?" should come as no surprise. AI is obviously exciting but simultaneously warrants caution. More policy and education are needed to ensure it remains ethical and safe.

History of artificial intelligence

Curious about how AI came about? This is a chronology of significant turning points thus far:

• 1950s: To assess machine intelligence, Alan Turing developed the Turing Test in his 1950 paper, "Computing Machinery and Intelligence." But it wasn't until John McCarthy first used the term "artificial intelligence" at a Dartmouth workshop in 1956 that AI was formally introduced.
• 1960s–1970s: Joseph Weizenbaum's ELIZA and Frank Rosenblatt's Perceptron, two early AI models that identified patterns, demonstrated that AI could simulate human speech in a dialogue with a psychotherapist.
• 1980s: The rise of computer configuration systems like XCON and AI gained popularity in disciplines like engineering and medicine.
• 1990s: AI pivoted toward statistical models and machine learning. IBM's Deep Blue made history by defeating world chess champion Garry Kasparov and proving AI's ability to make complex decisions.
• 2000s: Machine learning became more practical thanks to big data. AI also enhanced everyday tasks like search engine ranking and enabled recommendations on streamlining platforms.
• 2010s: As deep learning gained traction, AI systems such as IBM Watson and Google DeepMind's AlphaGo continued to outperform champions in difficult games. In a major breakthrough for AI, GPT-2 was released in 2019. Trained on approximately eight million web pages, it can produce paragraphs of human-like text—the first for a single model. However, its tendency to provide wrong or biased information and the need to study its misuse led to its multiphase release.
• 2020s: ChatGPT, which is regarded by some as the best artificial intelligence software, helped make AI more widely used. It’s also become synonymous with content creation, enabled by generative models. 2020’s developments include GPT-3 showing human-like fluency and DeepMind’s AlphaFold predicting protein folding, a major win for biology. The following year, Dalle released text-to-image generation, and GitHub Copilot’s Codex used natural language to code. In 2022-2024, OpenAI debuted GPT-3.5, GPT-4, GPT‑4 Turbo, and GPT‑4o in ChatGPT, the first consumer-facing chat AI. It came with safety features, memory functionality, and personalization through plug-ins and AI. A wave of similar chat AI solutions integrated into Bing, Office, and more.

Is AI the Same as Machine Learning?

Not really. Although the two terms are often used interchangeably, they are not the same. The difference is that AI is a broader concept, while machine learning is the most common application of artificial intelligence.

We should understand machine learning as a current application of AI that focuses on developing computer programs that can access data and learn from it without human assistance or intervention. The entire machine learning concept is based on the assumption that we should give machines access to information, then let them improve their knowledge from it themselves.

AI is a bunch of technologies that include machine learning and other concepts such as natural language processing, inference algorithms, neural networks, and more.

Closing Thoughts

Given the innate pros or advantages AI machines have over us humans (accuracy, speed, etc.), an AI rebellion scenario is something we should not completely dismiss. Only time will show us whether AI is our greatest existential threat or a tech blessing that will improve our quality of life in many different ways.

So far, one thing remains perfectly clear: creating AI is one of the most remarkable events for humankind. After all, AI is considered a major component of the 4th Industrial Revolution, and its potential socioeconomic impact is believed to be as huge as the invention of electricity once was.

In light of this, the smartest approach would be keeping an eye on the technology’s evolution, taking advantage of the improvements it brings to our lives, and not getting too nervous at the thought of a potential move toward a machine takeover. We advise using Clario Anti Spy to stay ahead of spying threats and breaches, protect your privacy, and prevent access to your smartphone.