Artificial Intelligence (AI): An Overview, applications, ethical side

These days, artificial intelligence or AI has become the trend. With dozens of AI software already in the market, trying to allure new customers by providing the automation of tasks normally done by humans, promising to raise quality and reduce production costs, AI is indeed a revolution in technology and today’s online world.

So what is AI and how does it work? Is it really worth of all that hype? And how can you use it efficiently and wisely to help grow your business or get rid of previously daunting tasks?

In this post we will provide an answer to all these questions and more. So read it and stay tuned!

What is artificial intelligence?

AI, artificial intelligence, in the broad sense is the simulation of human intelligence by computer system or any other programmed machine. It is the intelligent performance of tasks normally executed by real humans, and kind of “offshoring” them. It’s use can range from scientific experiments, business purposes, education, and even daily use. It’s application so far includes sophisticated expert systems, art creation, natural languages processing, and speech recognition.

How AI works

To train a machine and it’s algorithm to perform complicated jobs, AI software vendors use highly specialized software and hardware for those system training, including material from other networks such as stock images. When it comes to programming, no exclusive programming language is identifying with AI, as the later use multiple languages such as Python, Java, and R.

The very fact of using others’ content without consent in training robots has created a large uproar and dragged famous AI bots to courts.

Ai bot creators would use a large amount of data input, including texts, mages, audiovisuals, and making them available for the bots to analyze, get used to, create patterns, and everything they may need to perform hard tasks when requested. This way chatbots for instance, are able to communicate with users in a more humanlike manner. And Midjourney, a bot for creating images and visual art, is able to generate images as is asked by users via description they provide to the software.

All AI manifest the following three cognitive skills:

Ability to learning: this is done through filling the ai machine system with plenty of input data so it becomes smart in analyzing requests and creating rules. This help polish the algorithm of the system and render it smart in handling various tasks.

Reasoning: the ai systems are able to do reasoning processes, which untill few years ago was believed to be a faculty exclusive to humans. This skill comes as the fruit of that large data fed to the system. This aspect focuses on getting the right algorithm to gain the desired results.

Self-correction: AI programming is forged to constantly improve algorithm, fine-tune the system so that it generates the most accurate possible outcome.

Why AI really matters?

Businesses can use AI to perform certain tasks normally executed by humans, can do it better in some cases. It also allows their CEO to more enterprise insights of operations and actions and analyze data more efficiently and faster than before.

This is even true when those tasks are repetitive or when dealing with huge amount of data; AI can do all that easily and almost error-freely than most people. Filling forms and treating documents properly is where AI has an upper hand over humans.

The implementig of AI has indeed raised the business to another level and opened the door to entirely brand new eterprise opportunities. Google for instance, has been using AI to gather the most effective data about users and user online behavior so that it can efficiently target them with the right ads and services. They make use of AI to determine what a user needs when typing a certain query on their search engine, and provide the most accurate and relevant search pages that likely to answer those needs. The same with Facebook, now Meta, Twitter, and the rest of the big platforms. Sundar Pichai, Google CEO, stated that Google was the first AI company.

Adnavtages and disadvantages of AI

Artificial intelligence apps are developing rapidly and their use is spreading throughout the globe. This is mainly because AI can process and analyze huge amounts of data in a matter od seconds, which is abviously beyound any human brain capability.
One of the primary fears that these tools brought about is the one among content creators. This group of people are scared that AI tools might take their jobs out of them and do them even more accurately and with much shorter time.


This includes but not limited to:

  • Accuracy and rapidity of data processing;
  • Saving a huge amount of time to get the same results that are normally done by real humans;
  • Always present and ready to handle the job: no need to breaks to regain active status or even a weekends to rest

That been said, AI also brign forward some challenges and shortcomings which we will summarize in the disadvantages below.


  • Taking human jobs out which may contribute to unemployment of a large sector workers and employees;
  • The lack of creativity: some tasks do need a lot of creative thinking instead of know how things;
  • Most if not all AI tools are task oriented and may spoil data output in some areas where precision and real mind conclusion is must;
  • All prificient AI tools are a little bit expensive and beyond the reach of small businesses;
  • AI tools require a lot of efforts and energy resources to keep them running and improve their performance;
  • AI tools and bots were trained by using others’ content, which may imply copyright infrigement

Application of AI

What are the applications of artificial intelligence?

Artificial intelligence in healthcare. The most money is being bet on improving patient outcomes and lowering expenses. Machine learning is being used by businesses to make better and faster diagnoses than people. IBM Watson is a well-known healthcare technology. It understands natural language and can react to inquiries. The system mines patient data as well as other available data sources to generate a hypothesis, which it then provides with a confidence grading schema. Additional AI applications include the use of online virtual health assistants and chatbots to aid patients and healthcare customers in locating medical information, scheduling appointments, understanding the billing process, and completing other administrative tasks. AI technologies are also being utilized to anticipate, battle, and comprehend pandemics like COVID-19.AI in business.

Machine learning algorithms are being integrated into analytics and customer relationship management (CRM) platforms to understand how to better service clients. Chatbots have been integrated into websites to give customers with immediate support. Job automation has also become a topic of discussion among academics and IT specialists.

Artificial intelligence in education. Grading can be automated using AI, providing educators more time. It is capable of assessing students and adapting to their needs, allowing them to work at their own pace. AI tutors can help students stay on track by providing extra assistance. And it has the potential to transform where and how children study, possibly even replacing certain professors.

Artificial intelligence in finance. AI in personal finance apps like Intuit Mint and TurboTax is upending financial institutions.

These kind of applications capture personal information and offer financial advise. Other programs, including as IBM Watson, have been used in the home-buying process. Currently, artificial intelligence software handles the majority of Wall Street trading.

AI in the legal field. In law, the discovery procedure (sifting through documents) can be daunting for humans. Applying AI to help automate labor-intensive operations in the legal business saves time and improves client experience. Machine learning is being used by law firms to describe data and anticipate results, computer vision is being used to classify and extract information from documents, and natural language processing is being used to interpret information requests.

AI in the legal field. In law, the discovery procedure (sifting through documents) can be daunting for humans. Applying AI to help automate labor-intensive operations in the legal business saves time and improves client experience. Machine learning is being used by law firms to describe data and anticipate results, computer vision is being used to classify and extract information from documents, and natural language processing is being used to interpret information requests.

Artificial intelligence in banking. Banks are successfully using chatbots to inform clients about services and opportunities, as well as to manage transactions that do not require human participation. AI virtual assistants are being utilized to improve and reduce the costs of banking regulatory compliance. Financial institutions are also utilizing AI to improve loan decision-making, set credit limits, and locate investment opportunities.

Security. AI and machine intelligence are at the top of the list of buzzwords used by security providers to differentiate their products today. These are also terms that indicate actually feasible technologies. Machine learning is used by organizations in security information and event management (SIEM) software and related domains to detect abnormalities and suspicious actions that suggest dangers. AI can detect new and developing attacks far faster than human employees or prior technology iterations by evaluating data and using reasoning to spot similarities to known harmful code. The evolving technology is playing a significant role in assisting enterprises in combating cyber threats.

Artificial intelligence and ethics

While AI technologies provide a variety of new capabilities for enterprises, their use presents ethical concerns since, for better or worse, an AI system will reinforce what it has already learnt.

This can be an issue since machine learning algorithms, which are at the heart of many of the most advanced AI products, are only as smart as the data they are fed during training. Because the data used to train an AI algorithm is chosen by a human, the possibility of machine learning bias exists and must be properly managed.

Anybody interested in using machine learning in real-world, in-production systems must incorporate ethics into their AI training procedures and aim to minimize prejudice. This is especially true when utilizing deep learning and generative adversarial network (GAN) AI techniques, which are intrinsically inexplicable.

Explainability is a possible roadblock to employing AI in businesses with stringent regulatory compliance requirements. In the United States, for example, financial organizations are required by law to justify their credit-issuing choices. When AI programming makes a decision to refuse credit, it might be difficult to explain how the decision was reached because the AI tools used to make such judgments function by picking out small correlations between hundreds of variables. When a program’s decision-making process cannot be described, it is referred to as black box AI.

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