Artificial intelligence (AI) is cloning the human intelligence processes by computer systems. Like human intelligence, AI also follows same process includes learning (identifying the information, acquisition of information and set rules for using the information), think logically (using new rules to reach conclusion) and at the last step self correction.
Regarding the objectives that AI would be designed for it, AI classified into two categories: strong or weak. Strong AI is a system with generalized human cognitive abilities that when face with an unfamiliar task, it could able to find a solution without any human intervention. On the other hand, the weak AI is a system which is designed and trained for a particular task like Apple‘ Siri or other virtual personal assistants.
As establishing AI is very expensive, big players of IT, software and hardware industries offer standard components of AI as Artificial Intelligence as a Service (AIaaS). Some of these popular AIaaS are those which were offered by IBM Watson Assistant, Google AI, Amazon AI and Microsoft Cognitive Services.
Examples of AI technology
AI is incorporated into a variety of different types of technology which they are:
- Automation: What makes a system or process function automatically. As an example, IT automation that can be programmed to perform repeatable tasks that humans normally performed and could be adapted to changing circumstances.
- Machine learning: The science of getting a computer to act without programming. As an example, deep learning which is a subset of machine learning, can be thought of as the automation of predictive analytics.
- Machine vision: The science of allowing computers to see. The machine vision technology captures and analyzes visual information by using a camera, and process them. It is often compared to human eyesight, but machine vision has not biology limitations of human eyesight and can be programmed to see through walls, for example. It is used in a range of applications from signature identification to medical image analysis.
- Natural language processing (NLP): The processing of human language by a computer program. One of the older examples of NLP is spam detection, which looks at the subject line and the text of an email and decides if it’s junk. Current approaches to NLP are based on machine learning. NLP tasks include text translation and speech recognition.
- Robotics: A field of engineering which focused on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. They are used in assembly lines for car production or to move large objects in space. Researchers are also using machine learning to build robots that can interact in social settings.
- Self-driving cars: These kind of cars use a combination of computer vision, image recognition and deep learning to build automated skill at piloting a vehicle while staying in a given lane and avoiding unexpected obstructions, such as pedestrians or bikes on the street.
Applications of AI
Artificial intelligence could be used in diverse fields. In below, some of its main applications were reviewed:
- AI in healthcare: Companies are applying machine learning to make better and faster diagnoses than humans about patients. One of the best known healthcare technologies is IBM Watson. It understands natural language and is capable of responding to questions asked of it. The system mines patient data and other available data sources to form a hypothesis. Other AI applications like virtual health assistants or chatbots that are computer program to answer questions and assist patients online are also follow same targets. They can even help schedule follow-up appointments or aid patients through the billing process and provide basic medical feedback.
- AI in business: Robotic process automation is being applied to highly monotonous tasks normally performed by humans. Machine learning algorithms are being integrated into analytics and CRM platforms to uncover information on how to better serve customers. Chatbots have been incorporated into websites to provide immediate service to customers.
- AI in education: AI can automate lecturing and grading and can assess students and adapt to their needs, helping them work at their own pace. AI can provide additional support to students, ensuring they stay on track, too. AI could change where and how students learn.
- AI in finance: AI in personal finance applications, could collect personal data and provide financial advice like buying a home.
- AI in law: The discovery process, sifting through of documents, in law is often overwhelming for humans. Automating this process is a more efficient use of time. Some virtual assistants through question and answer automated whole of the process and could even provide legal advice.
- AI in manufacturing: As a forefront robots revolutionizing, industrial robots used to perform single tasks and were separated from human workers. They can detect the failures and correct them more quickly than past.
Security and ethical concerns
AI tools offer broad range of new functionality for businesses and due to this, using AI is increasing. But it also raise some risks, too. One of the most risk is ethical matters, because deep learning algorithms, which underpin many of the most advanced AI tools are selected by a human. So, the potential for human bias is intrinsic and must be monitored closely.
Moreover, security is also one of the main concerns of using AI. Self-driving cars could be hacked and if they cause any accident then liability is unclear. They can also be hacked and misused in terrorism attacks. All of these, force programmers of AI to consider security and ethical matters and find ways to minimize damages.
As AI systems grow more powerful, we need to review our objectives more carefully to be ensure that those AI systems do exactly what we want or not.