Thinking Machines: What Artificial Intelligence and Machine Learning Mean for Our Future

Eleanor Barlow

To many of us, the words ‘Artificial Intelligence’ (AI) conjures images of a dystopian world, abundant with merciless, power-hungry robots and an overthrown or destroyed humanity. From the 1984 film ‘The Terminator’ to ‘Ex Machin’ (2015) intelligent, destructive automata have permeated what AI symbolises. Many critics and scholars within the field, including Martin Ford in his new book Rise of The Robots, argue that machines are “getting too smart, too flexible and too convenient” and, as Stephen F. DeAngelis, content writer for Wired states, pose “a grave threat to humanity”.

Robot with human body and detachable face

Tesla founder, Elon Musk, even goes as far as to testify that “AI’s are as dangerous as nukes”. Indeed, when we view the 2016 edition of Gordon Moore’s Law, the “number of transistors in a dense integrated circuit has doubled approximately every two years”. This, so far, has proven to be true. Thus, at the speed technology is advancing, it is not implausible to envisage the depiction illustrated in ‘I Robot’ (2004) of the year 2035 overrun with lethal machines.

 

Not all Doom and Gloom

Wall-E the loveable robot

Yet, despite these dystopian representations, an opposing concept of AI is not only promoted but adored. In the 2008 film ‘WALL-E’, an AI recovers and revives a desolated earth, ruined and abandoned by civilisation. In ‘Star Wars’ droids R2-D2 and C-3PO become brave and lovable companions, and in ‘Robot & Frank’ (2012) an AI is used to assist an elderly dementia patient with daily activities. Supportive, intelligent, convenient and valuable, these creations emphasise how AI could assist humanity and aid in our development.

With such contrasting depictions in the media, many would question whether the advancement of AI is simply a means for control, or, in its advancement, are we, the creators and controllers, supporting and facilitating in societies development for the better? To answer this, we must first understand the difference between the terms AI and ML (Machine Learning).

 

 

AI v ML

Data board

AI requires the computer system to complete tasks as a human would, either by using visual perception, speech recognition, or decision making. ML has the ability to assist AI by allowing the system to instinctively learn, as well as correct itself, through practice, without being instructed or programmed. In short, ML focuses on the development of computer programmes which access data and uses data analysis techniques to evolve.

Far from the designs of red-eyed robots, ML is used frequently and often “dozens of times a day without you knowing it” (Lee Bell, writer for Wired). When you enter a typo into Google, for instance, the system has learned that the misspelt word was not the intended word and generates an alternative (‘Did you mean?’). The same concept applies when searching for features such as the ‘Top ten places to visit in Amsterdam’. The system has learnt from the data provided based on positive and negative reviews and feedback, which order to show these places to the user and categorises items without being programmed to do so.

Not only can ML aid in menial daily tasks efficiently and effectively but Mahesh Pancholi, Research Computing and Life Sciences Specialist, states that “there isn’t an area that can’t benefit from artificial intelligence”. From Apple’s Siri to Smart Home devices, you use AI’s at your bank, in your car and on your smartphone. AI’s can aid in decision-making which can either be accepted or rejected by the observer, to which the AI/ML will learn from and improve.

Robot and human working together

AI’s can make life more stimulating by perfecting tasks that would have otherwise been monotonous, such as analysing vast quantities of data. Assignments are completed at a faster rate which creates time for other things; making your day more productive. Sites such as ‘Modernising Medicine’ have been formed using AI technology to assist doctors when faced with patients with unusual symptoms, and to determine what treatment to prescribe. Police have been able to fight crime by using lip-reading AI, and University College London researchers have shown how AI could benefit children via one-to-one tutoring.

 

 

The Future

If AI and ML are managed and progressed in the best possible ways their potential to make immense, progressive changes to our world are consequential. AI’s and ML are, essentially, the tools of the next generation.

Here at Pansensic, we are embracing these new technologies and are using these tools to enhance our world for the better. We work with organisations from all over the world in a wide range of sectors. What they have in common is the understanding that the experiences of their customers, staff and stakeholders can provide game-changing insights and, by incorporating ML into our work, we can provide more accurate insights quickly and efficiently.

Nowadays, most sites, especially social media platforms, are all concentrated on imagery rather than text. Of course, comments are still plentiful, but pictures are promptly increasing. In places, such as Instagram, people tend not to leave extensive texts that we can analyse so, as a result, we are starting to use image recognition to decipher what is in a picture.

By utilising ML here at Pansensic, we are able to not just simply summarise data, but provide a real depth of insight that is more granular, more accurate and more actionable.

Contact the team today to see what Pansensic can really do for you.

 

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