4 essentials you can learn about Artificial Intelligence

Daily News Egypt
4 Min Read

Google launched, on Wednesday, ‘The A to Z of AI’ guide in Arabic in collaboration with the Oxford Internet Institute.

The Arabic-language guide aims to make information on Artificial Intelligence (AI) more universally accessible. It is a series of simple, bite-sized explainers to help everyone understand what AI is, how it works, and how it is changing the world.

Search interest for AI-related queries on Google Search has grown due to the increasing number of jobs requiring skills in the field across the Middle East and North Africa (MENA) region in the last few months. 

While there is plenty of information out there on AI, it is not always easy to distinguish fact from fiction, nor find simple explanations. Here are a few things everyone can learn through the new interactive guide:

AI is powering practical tools that exist all around us

You have probably interacted with AI without even realising it. Artificial intelligence is the name given to any computer system taught to mimic intelligent human behaviours. 

These technologies show up in everyday life, whether by helping organise photos on our smartphones or planning a commute to work. They use computer programming to do tasks that have historically required considerable human intellect and work, helping make our lives more efficient. 

We have all seen major progress over the past decade, sparked by faster computers and the introduction of techniques such as machine learning.

AI learns from examples in the real world

Just as a child learns through many life examples, the same is true of machine learning algorithms. Datasets are large collections of “examples”, like weather data, photos, or music, that we can use to train or “teach” AI. 

Due to their scale and complexity (think of a dataset made up of extensive maps covering the whole of the known solar system), datasets can be very challenging to build and refine. This is why AI design teams often share datasets for the benefit of the wider scientific community, making it easier to collaborate and build on each other’s research.

Incomplete data can lead to bias in AI

AI could form a bias when the data it is learning from is not fully comprehensive, and therefore starts leading it toward certain outcomes. Because data is an AI system’s only means of learning, it could end up reproducing imbalances or biases found within the original information. 

For example, if you were teaching AI to recognise shoes and only showed it imagery of trainers, it would not learn to recognise high heels, sandals, or boots as shoes. To ensure that AI systems are ethical and reduce the risk of bias, programmers design their systems and curate their data vigilantly.

AI can help our efforts to spot deepfakes

“Deepfakes” are AI-generated images, speech, music or videos that look real. They work by studying existing real-world imagery or audio, mapping them in detail, then manipulating them to create works of fiction that are disconcertingly true to life. 

However, there are often some tell-tale signs that distinguish them from reality. In a deepfake video, voices might sound a bit robotic, or characters may blink less or repeat their hand gestures. AI can help us spot these inconsistencies.

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