Is AI the last invention we make as humans?

But how relevant is this quote today or tomorrow? Nowadays almost everyone as access to a lot of information via the internet of things. Articles, papers, essays, newspapers and whole books are digitize and published in this black hole of information. Everyone can use it. The relevance of this quote, however, is not about the memory of computers what is a source of information for us humans, but it is the processing power of artificial intelligence that is a source of using all this knowledge. Decades Moore’s Law was applicable, where every 18–24 months the number of transistors doubles. This made it possible to develop computers with far more processing power than years before. The computer that made it possible to bring the first human on the moon for example, Apollo Guidance Computer (AGC) for the Apollo 11 had 64 kilobytes of memory. This is just a fraction of what today is available with a simple smartphone, which is even a lot smaller than the AGC.

Where computers used to be slow, stupid, big they are now small, smarter and faster. We also get more data, all we do on the internet and also things not on the internet is stored. Companies like Google or Apple uses this data to make sense of the world they are looking at. They managed to combine this data and computers for machine learning to know better what their customers want. When you wanted to improve a machine or computer you had to write a code, test it and write again. Machine learning means that you don’t need to do that, you don’t need to program everything. Computers can adapt itself. With machine learning the invention of deeplearning came. This implies that machine learning is made possible by mimicking the brain and how it works. If the system does something good a connection growing stronger and if it does something wrong a path between two points is getting weaker. It uses it’s input data to reflect itself, it runs a simulation, then it purposes an action, possibly do the actions automatic, measure the results and optimise it’s actions.

It is not future. Almost everyone has a smartphone, a device that has several AI’s working together. For example you want to know the quickest route to the central station in The Hague. You can ask your phone “OK Google, Take me to The Hague central station”. The microphone of your cell phone receives your message processes it by AI to data the little computer can use. The AI for speech has had a lot of inputs to determine how speech work and how to translate it into text. Then Google Maps opens and calculates the quickest route for you. Also from its experience it knows where and when the road is crowded or how long it takes to use a route, such that it calculates your fastest way. So the AI of speech in your phone will make an action and the AI calculating a route gives you an advise. More it cannot do, but you are happy because you don’t have to think yourself by looking on a map and decide which route you want to make.

Such application is called narrow AI: a very intelligent system which is very good in its trained field. Other examples of narrow AI are Netflix, face-recognition, Siri. These systems are trained for instance to know what kind of series you might watch tonight or how a person look like on a photo. Training machines gets more easy when the processing power increases and when the amount of data increases. When we train machines today, in a later stadium they will train each other with experience. And with this improvement the machine may know how to solve things different, but especially faster than we do.

So machines are better? Then machines will take our jobs! First of all, there are some jobs and activities no one wants to do. Back to Google Maps, you don’t want to crack your brain on the quickest route. You just want to get at your destination. Besides the ease of Google Maps, artificial intelligence or robots are also needed in industries like agriculture. By the year 2050 the population of the world is in a need for such amount of food that there must be an innovative way to increase the production, but nowadays there is already a shortage of workforce in the farming industry. This need of manpower can be filled with machinery, preferably including AI. Artificial Intelligence can keep the production high or even higher when the need of resources will decrease. A robot will therefor reduce the costs personnel, but it will also reduce the costs of water and pesticides. Not only in farming but also in industries like construction, fabrication and others where there is a lack of manpower, AI will be a solution.

And it doesn’t stop there. High-educated jobs are under a “threat” too. Secondly robots will improve the results of jobs. For example the well educated profession of radiologist will no longer be necessary, because a computer can do things much faster and much more precise than a highly trained radiologist. There will also be surgeons which shall be replaced with machinery. Bankers and stockbrokers too will be replace by this artificial intelligence.

Eventually there comes a moment in time where the profession of AI-specialist isn’t needed anymore for improve machines. Machine intelligence is the last invention that humanity will ever need to make — Nick Bostrom. The time will come when a robot is far more smarter then what a human could be. It will improve its previous self. When the AI-researcher is replaced with a robot, at that point it is hard to keep up. Machines improves machines. Computer getting better in even a faster rate. When robots can think more like humans, we speak of artificial general intelligence. This is when a computer can have a conversation of human level and the mechanism is able to use multiple actuators. With better AI, Kurzweil predicts: faster computing leads to faster innovation leads to faster solutions to hard problem. All diseases, hunger, energy, etc will be solved what results in immortality leading to bodies that become obsolete, people will only be minds and therefor an interconnected mind arises across mankind.

This is a speculation about the far future, but where the roots of it are today and before today. Mainly narrow AI is applied today and in the near future. Many vacancies on humans are and will be filled with thinking machines. With the estimated growth of the population, the production of resources like food and materials for housing must be higher with a decrease of the amount of people working there. Also on many other jobs humans will eventually be replaced, but with the improvement of technology other jobs will arise. And when all jobs are done by robots, people will care for products which are home made. Items made with love. Also empathy is something difficult for the robotic brain. Some things humans will still be better.

Related posts:

Making money online has become increasingly popular in recent times, as more and more people are looking for ways to supplement their income or even make a full-time living. While the more…

A real user monitoring tool embeds a short code in every app or web page that allows the tool to collect data directly from the users’ browser or app and display the same on the tool’s dashboard…

This Article is the second in a four-part series to show you “How to Complete a Six Sigma Root Cause Analysis.” The Input Map (or X-Map) helps the project team to identify all the Xs (or Inputs) in…