Essentially an algorithm is a component of AI – as in a mechanical gear is a component of a watch. You use the watch to tell the time, but it’s going to be impossible without the gears inside that are used to drive its time-telling capabilites.
At the local level, Artificial Intelligence is an algorithm. It solves input problems based on accessible data and operational parameters depending on how much computational power is available to the algorithm.
When you read about AI in the press, typically its the name given to machine intelligence.
Within the vast field of AI are specific concepts such as machine learning and deep learning. The difference between how AI works as opposed to a traditional algorithm is as follows.
Typical algorithms match an input with some logic, the combination of which provides an output. Machine Learning Algorithms take an input and an output and provide some logic which can then be used to work with a new input to give you an output. That logic which is generated is what makes this Machine Learning – many sequential iterations of a similar process to arrive at an intelligent result.
What are the pros and cons of AI?
Automating mundane tasks
Artificial Intelligence will displace many low-skilled jobs. This can be seen as a pro or a con depending on whose case you’re arguing, but essentially, as long as robots are forced to pay the same taxes as humans (which, currently they don’t) this should result in a net positive result for the human race.
Essentially the robots will be replacing humans for dangerous, mundane and difficult manual labour tasks that will free up human resource for high strategy and creative work.
At my agency, we use an AI tool to process large amounts of keywords into logical groups. It’s the type of task that would typically take an SEO exec days to manually sort through, but at Blue Array, we can categorise keywords into semantically relevant groups at the click of a button.
Global Impact: Theoretically this can remove “boring” tasks from humans and free them up to be increasingly creative.
Faster decision making
Using artificial intelligence alongside cognitive technologies can help make faster decisions and carry out quicker actions. With the example of our Keyword Processing tool, the machine makes much faster judgements about where a keyword should be categorised based on a set of rules. Rather than debating whether ‘Liverpool Hairdresser’ is better in the ‘Liverpool’ column or as a ‘Hairdresser’ a machine learning algorithm is able to make up its mind with either a ‘1’ or a ‘0’.
If programmed correctly computers don’t make the same slip-ups as a human. They don’t suffer from tiredness or mood swings (well, some old Windows machines could be exempt from that last statement) and they certainly don’t take sick leave or turn up 5 minutes late to their desks.
Risk Taking For Humans
With artificial intelligence, you can arguably lessen the risk to which academic research poses to humans. Take, for example the Mars rover, known as Curiosity. It can travel across the landscape of Mars exploring the dangerous territory and gathering data that’s invaluable to humans.
Using artificial intelligence in this manner will lead to growth in areas such as demand forecasting, medical diagnosis and oil exploration.
Artificial intelligence carries the risk of taking control away from humans – de-humanising actions in many ways. At the moment AI has a very low-level impact on your day to day life. Imagine shopping at supermarkets of the future (via your VR headset device) and getting promoted to buy certain brands or food types based on a combined algorithm of inputs from your GP, Dentists, Nutritionist and Regional Agricultural data service. Imagine one step further when you no longer even do shopping (‘What does shopping mean, Granddad?’) – your Alexa or equivalent personal assistant knows exactly what you want when you want it.
Will you even be aware of whose choosing what you eat for dinner – you or your AI? And when I say AI, I’m talking about the monolithic marketing departments of huge brands that have access to manipulate and transform the outputs of that AI.
Humans can take unique circumstances and judgement calls into account when they make their decisions, something that artificial intelligence may never be able to do. One example occurred in Sydney, Australia, in 2014 when a shooting drama downtown prompted numerous calls to Uber in an effort to escape. Uber’s ride rates surged based on its supply and demand algorithm – showing no consideration involved for the circumstances in which the riders found themselves.