Machine learning (ML) and Artificial Intelligence (AI) are two buzzwords, particularly when talking about the realm of data innovation. Artificial Intelligence is the ability that machines have to mimic the cognitive processes of humans. The word ‘artificial’ comes from this idea that machines are not intelligent per se. Behind them, there are humans programming them to perform certain tasks. Nevertheless, depending on the complexity of their programming, some machines are more ‘intelligent’ than others. This means that some machines only need to be programmed once and they will continue to perform the tasks or increase the complexity of the task performed, on their own. For data enthusiasts and innovators working in the humanitarian sector, AI expands the possibilities of processing data in a more accurate and timely way — data that could help Senior Management make decisions quicker or prepare our teams on the ground better for eventual contingencies.
A robot? Not exactly.
According to TechTarget, a robot is a machine designed to execute one or more tasks automatically with speed and precision. Some robots, for example, only need simple programming to do specific repetitive tasks, and sometimes they do not necessarily require AI embedded in them. This is the case of a robot in an assembly line. However, not all AI is necessarily applied into a robot. For example, sometimes AI is applied in a computer or a mobile device. And sometimes — once AI is programmed — it has the ability to ‘learn’ from the original programming and then compute tasks on its own. An example of this is Siri on your iPhone. Siri, is a form of applied AI that is capable of ‘learning’ voice patterns and convert them into dictation. It recognises a language, a local accent to then, perform a task — like looking for the weather conditions in a particular city. Siri synthesises millions of data points coming from different words, languages, and even different accents around the world, becoming ‘more intelligent’ and recognising more patterns every time. Siri uses then Machine Learning (ML) techniques to process all this amount of data, and responds in a matter of seconds — even if the same question is asked in different ways with a different tone — how’s the weather today? Is it going to rain? Is it cold? To compute an answer: bring an umbrella.
- : http://www.unhcr.org/innovation/teaching-robot-detect-xenophobia-online/
- : Rebeca Moreno
- : UNHCR Innovation