Collective Intelligence: Human Centered Design,
Teaching & Learning WITH Machines
Collective
intelligence is all about bringing a group of intelligence together and merging
it, more like a collaboration. This can be the way that humans and machinery are
seen when used together. When speaking of machine learning and artificial
intelligence a lot of confusion can arise as many people believe that they are
in fact the same, which isn’t the case, there are major contrasts.
Machine
learning is an application of artificial intelligence, it is known to be “the
study of computer algorithms that improve automatically through experience”
using large sets of data to “Examine and comparing data to find common patterns”.
The machine learning program focuses on large sets of data and allows them to
be examined, it is is able to find common patterns and compare them with
others, for example radiography, x-ray images.
On
the other hand, artificial intelligence (AI) is known as the “science and
engineering of making computers behave in ways we thought required human
intelligence”[1]. AI has majorly grown over the recent years, now being incorporated
into our everyday lives and homes, with the help from products like Google Home
and Alexa even down to Siri on our iPhones. From people believing that calculators
were the extent of AI to now having actual walking, talking robots like Sophia a
social humanoid robot created in Hong Kong, receiving citizenship in UAE.
The
main difference between Machine Learning and Artificial Intelligence is that AI
is ever growing, the field of it is so broad and changing more and more every day,
in contrast with machine learning which is a very “clear cut” definition.
Further
examples of Artificial Intelligence with machine learning are Self driving
cars, sounds crazy, right? This shows the extent of how big AI can go. The self-driving
car is a vehicle able to drive its self through sensing its environment with no
form of human interaction. Despite this idea seeming cool and fun, the risks
are extremely high, if there is an accident, whom is responsible? If someone is
hit will the car stop or would it be classed as a hit and run? The possibilities
are endless and the controversy around this topic goes on.
My
personal view on AI and machine learning is both positive but then also has
some negatives, as I believe that AI can be used in ways of good as long as we
are careful with it, as we build upon the machinery to think for themselves we
also have to think of the concequences they could bring. For now I am excited
for the future and what else will be brought to life.
[1] Iriondo, R. (2018). Differences Between AI and Machine Learning and Why it Matters. Available: https://medium.com/datadriveninvestor/differences-between-ai-and-machine-learning-and-why-it-matters-1255b182fc6. Last accessed 2nd Jan, 2019.
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