Intelligent machines on the rise
Are we experiencing an unprecedented technological advance through artificial intelligence (AI)? There is a lot out there that suggests this! Still, it will take a long time for machines to truly become equal or superior to humans. Until scientists and researchers have developed super-intelligence (strong AI), we humans will continue to co-exist and work well with weak AI.
While strong AI can replace humans, weak AI is an extension of our cognitive skills and gives us already today great advantages in mastering specific application challenges. AI will become a core component of the modernization of society and the economy. It will support us immensely in coping with large-scale global challenges — for example, in developing more intelligent cities and safer and congestion-free traffic, in lowering energy consumption and optimizing our power grids, in cutting down on carbon dioxide emissions, and in protecting the internet more effectively. In the global race to boost productivity, AI will be a decisive factor with regard to demographic development.
Scientists like to present us their latest innovations in the battle between humans and machines. Just look at chess and the popular Asian game Go and you will see that, in these cases, the ma-chine is cognitively already far superior to humans. It would be vastly exaggerated, however, to say that machines are generally speaking superior to humans because of this example. It will take a while for strong AI and humanoid robots (androids) to acquire the skills and capabilities of humans.
More than a string of ones and zeros
AI is supposed to mimic human cognition and actions in machines. In the case of a car navigating its way through urban landscapes, this can take place using a relatively simple algorithm which finds the shortest route; or, it can result from a complex neural network that, for example, steers autonomous cars and all traffic towards the most efficient and congestion-free route. This kind of neural network is being trained with huge data volumes to recognize patterns and derive its own conclusions. There are various approaches to achieving artificial intelligence. So far, however, no approach has emerged that has proven successful. Development is still in the starting blocks.
Although deep learning as a method is a good three decades old, it has experienced a revival of sorts lately. You can imagine deep learning as a type of filter that works its way from rough to fine results, thereby increasing the probability of generating a correct one. It is made up of layers that build on one another and uses the results of the previous layer, which creates a continuous learning process. With its immense computing power, deep learning is able to dig through enormous amounts of data. It succeeds where other approaches have failed.
AI as a black box?
How AI gets many of its results remains largely a mystery; the more complex the machine, the more intricate the task is of reading these black boxes. This may be due to the fact that, in contrast to structured data storage in, say, a database, AI data is stored in fragments that are practically unattainable for humans.
The need for a glass box instead of a black box is more than understandable here. Researchers are working hard to find a way to make computer algorithms more comprehensible for humans. Advances in AI mean that the above-mentioned forecasts, decisions and actions of a machine are based on criteria that constantly update themselves as the algorithm continues to learn.
It remains to be seen if deep learning is the end-all technology. There are other promising AI approaches. Time will tell which approach is the right one for which use case. The best approach is probably a combined one, for example, with semantic (ontologies), static (deep learning), etc.
With value comes acceptance
Given the high number of publications on this topic, it is hard for us readers to judge in single instances if a machine or an application labeled intelligent really is intelligent. Just because something is called intelligent, doesn't mean it really is! The term intelligence is vastly overused and defined in so many ways, but there is no one universal definition. Likewise, AI applications vary widely in their cognitive capabilities. Ultimately, something is intelligent if it offers value.
Weak AI and rule-based systems already offer us considerable benefits and enormous potential in the future. They manage financial transactions, make forecasts, and simulate weather and economic developments. AI detects anomalies, for example, in the form of credit card fraud. It is an excellent means of making diagnoses and prognoses in medicine. Particularly notable is that artificial intelligence can first evaluate radiological images before the radiologist makes a final diagnosis. When it comes to recognizing patterns in texts, images, handwriting, materials and substances, AI is more advanced than humans. It is crucial for predictive maintenance and repair. Artificial intelligence is particularly useful when the best solution or the best possible decision must be made based on huge data volumes and a high number of options. AI has made important progress recently in the area of complex challenges, for instance, in language control and processing.
Humans love convenience. After all, they invented the wheel, because they preferred to drive rather than walk. Just like humans did back then, we are now asking ourselves: Does AI help us? Does it make our lives easier? Where there are benefits, there is acceptance. The more similar interactions with AI are to human behavior, the more accepted AI will be.
On the path to disruptive core technology
Artificial intelligence has great potential in the realm of economics and business. It not only relieves workers from having to do repetitive or even dangerous tasks, it is also much faster in analyzing data volumes, making decisions based on this, and completing tasks. What's more, robots will further automate production, which will open many new doors. For example, countries such as Germany will become a more attractive production location, thus increasing its competitiveness. There will no longer be any economic reasons for outsourcing production to low-wage countries. Whole new business areas will emerge as a result of AI joining up with connected products, processes and machines (Internet of Things; IoT).
AI is developing more and more into a disruptive core technology. It will revolutionize our working lives and current software applications! Let's keep our expectations realistic though: instead of drastic breakthroughs, progress in development will come gradually. For the time being, there won't be a do-it-all AI application that can combine human-like skills and capabilities.
Just like humans, machines are also capable of making mistakes. As long as human health, life and death are not at stake or people are not being assessed, mistakes are acceptable. Using a percentage tolerance level, we humans will define probabilities which allow us to decide if a computation is correct. We will no longer have to complete tasks or process steps ourselves, but will monitor and optimize machines while they handle them.