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Intelligence- is it a question of the right wires?

Artificial Intelligence (or AI) has become a buzzword- it's been seen in sci-fi films and horror. 

There is the genuine human fear that we can build something that can destroy us- sounds like something Mary Shelley would be proud of.

With multiple billion-dollar countries trying to get ahead in the AI race- this is a big deal, and despite the fear, AI is the future.

AI is the future- and it's also the subject of media and nihilistic fantasies.

It's a buzzword and a "buzz-theme"- but let's break that down.

Artificial intelligence (AI) was first introduced around 1955 by an American computer scientist and cognitive scientist, John McCarthy. Artificial intelligence is when a device imitates the cognitive response of humans and is able to take its own actions. Artificial intelligence has constantly been growing and developing since first discovered, and on the daily new robots with new skills are being developed.

Learning and developing machines is the process of studying computer algorithms and along the years it is continuously improving, with major applications in our world now. With this major impact coming soon from AI, humankind must start to adapt to changes.

There are a few disadvantages that could come with the increasing development of AI. An example is overpopulation and this is because our world is already suffering from human overpopulation and with AI possible walking around it would increase to fill the little spaces left. Furthermore, some jobs could decrease or completely prevent humans from performing them as one of the main AI uses would be to do human’s jobs and assist. However, it could take over rather than just assist, and humans would be useless in some working fields.

Having said that, many advantages can come from further development of AI that could positively affect our future world.

AI is now not only used in computer programs, video games and ‘chatbots’, but also, it is starting to develop towards the medical field where it is used to assist doctors and facilitate patients’ stays.

Examples for AI being developed for use in medicine such as the following:

  • Increasing accuracy in diagnosis:

As artificial intelligence is much more informed and has access to many resources such as past cases and the latest medication and studies on specific areas needed to diagnosis different patients. This cannot be done by people as it is too time-consuming and would take at least a few days whereas artificial intelligence could get this information in a matter of seconds.

  • Apps such as –Derma Compare:

This is an app that uses artificial intelligence to carry out a scan of the body for any cancerous spots on the body (skin cancer), with fairly high accuracy, ensuring a faster treatment which could make a difference between life and death for some.

An example of other uses of AI include:

  • AI Lawyer:

AI is also being used as a lawyer to see whether parking tickets could be appealed using a few question to understand the situation. According to The Medical Futurist, in both London and New York it has a success rate of around 64% as the bot has successfully appealed between 160,000 to 250,000 parking tickets.

  • Search and rescue:

AI has been specifically made to detect people stuck in danger due to a natural disaster. This helps save many lives before it’s too late. This is possible as unlike humans, AI has special algorithms that it could use to start ‘the search’ and try to find victims. This is usually done under 2 hours.

The uses of AI do not end here as there are so much more uses and more is being developed for a better and more facilitated future.

Jobs in AI development

There are many jobs related to AI development such as neurology, computer science, engineering, data scientist, etc. The majority of those who work in those fields are males and a few are females.

According to, since 1990, the number of women in computer science related jobs has decreased dramatically from 35% to 25% over the last 15 years as well as only 12% of females are engineers. Around 2010-2011, women made up only around 17.6% of computer science students whereas according to National Centre for Education Statistics in 1984 they made up 37% of computer science undergraduate students.

Why more women should consider studying computer science:

Computer science jobs facilitate the work-life for women, as it provides a very balanced lifestyle. Computer science jobs make it easy to work from home as it is involved around computers which are generally portable, as well as the hours are very flexible allowing employees to work at the time that is best suited to them. Furthermore, for women, they are provided with maternity leave (in America), which facilitates women’s work-life and family life- Apple is a company that holds up such standards.

For example, Apple provides gives 18 weeks maternity leave and 4 weeks prior to delivery, and fathers and adoptive parents also get 6 weeks paid leave.

Encouraging girls to take more STEM-based subjects, and head for more computer science related jobs is the key to increasing the percentage of female working in that field. There are many ways to encourage girls to get into STEM subjects such as organisations and camps.

An example is the summer camps done by, ProjectCSGIRLS, etc., which are mostly held in the United States, to motivate younger girls to get into more STEM subjects. This is provided through STEM activities, working with technology, as well as it would help them build teamwork skills. These summer camps aim to end the gender pay gap between males and females in the future by creating more interest in women and encouraging them to follow a career technical jobs such as computer science.

There are more women nowadays that are trying to make a change, challenge themselves and study computer science and machine learning. An example, according to is Hannah Wallach, a researcher on machine learning since 2001. She has attended many conferences such as the Neural Information Systems Processing where she met other women too in the field. However, has estimated that only 13.5% are females whereas the majority that is left are males “When I started out in machine learning as a PhD student, I didn’t know any other women. Most of the people I knew were men.”. This percentage could increase dramatically if more girls were encouraged to enter this field, inspire them for a better change in our future

Written by Noor Ali

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