today we are unpacking the concept of AI i.e ARTIFICIAL INTELLIGENCE
WHAT IS ARTIFICIAL INTELLIGENCE
Artificial Intelligence is the creation of machines to mimic human capabilities, such as teaching
a machine to see (recognise objects in an image) and listen (interpret and analyse sounds). In a traditional computer program, our algorithm tells the machine exactly what to do (step-by-step), whereas, in an AI program, the machine is programmed to learn and make its own decisions. Artificial Intelligence is a broad term that covers a range of specialisations and subsets, such as computer vision and natural language processing.
APPLICATIONS OF AI
DIFFERENT TYPES OF ROBOTS
Supervised and unsupervised learning
Supervised learning is the process of the human providing the program with many examples of what it is we are wanting it to learn, along with a label that helps the machine classify or identify an object.
- Classification is a supervised learning technique used to group data based on attributes or features. Humans can provide labels on the data (e.g. for images or text) that tell the machine about the attributes or features (e.g. colour, size, shape, measurements) in each data and how to group the data.
Unsupervised learning involves providing the machine with a large amount of data and letting it find patterns in the data on its own, by trying to identify patterns in the features included.
- clustering-Clustering is the task of dividing the population or data points into a number of groups such that data points in the same groups are more similar to other data points in the same group and dissimilar to the data points in other groups. It is basically a collection of objects on the basis of similarity and dissimilarity between them.
Areas of AI
Fields of AI
- aappComputer vision Computer vision is the ability for machines to recognise objects in images or videos. Computer vision aims to mimic human vision by teaching the machine using many examples of images either labelled or unlabelled, where it discovers patterns and learns to recognise objects on its own. Examples of computer vision include face tagging on social media photos, automatic recognition of number plates, and vision used by self-driving
- NLP (Natural Language Processing)
Natural Language Processing (NLP) is the ability for machines to interpret and analyse forms of human communication, such as text and speech. NLP aims to mimic human communication by teaching the machine to read, write, speak and listen by providing it with many examples of communication data
Other areas of AI
In addition to Computer Vision and Natural Language Processing, there are other areas that use AI to mimic human capabilities such as recommendation systems such as those used by online shopping, e-book purchasing and music sites. These systems provide recommendations based on our past usage data and ratings from other users who share similar behaviours and preferences.
AI is also used in the area of logic or cognition to solve complex games that require human-like cognition. Some examples include board games like Chess, Go where AI systems defeated human champions.
History of AI
The concept of ‘Artificial Intelligence’ first emerged in 1950 when an English Mathematician, Alan Turing
The Turing Test was developed as a method to determine whether or not a computer is capable of thinking like a human. For example, if a human is having a conversation with a computer (an AI system), the goal for the system to achieve intelligence is if a human cannot recognise whether the answer has been provided by a computer or by another human being. If the human believes the answer was provided by a human, when in fact it was the computer, that AI system is considered to have ‘passed’ the Turing Test.
Benefits & Risks of AI
AI has both advantages and disadvantages for humans and society. This lesson will discuss some of the key benefits and risks associated with AI. We also discuss the ethical considerations of AI, with a focus on the impact of conscious and unconscious bias on the design of technologies.
As with many technologies, there are number of advantages and disadvantages associated with AI-driven technologies. In the video below we identify some of these benefits and risks.
Just as with any tool, AI can also be used for good and bad or have both positive and negative consequences. The AI could be intentionally programmed to do something bad, or it could also be programmed in a way that it has unintended consequences that do harm and/or discriminate against people or groups in society. If AI machines learn to make decisions on their own, who is then responsible for poor or harmful outcomes?
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