3 Areas Artificial Intelligence (AI) Must Address

As we have been observing and learning about different parts of Artificial Intelligence as afield there are a couple of themes that keep coming up. First, AI is in more places than ever before, many machine learning professors claim that AI is the new electricity.

This is a pretty bold claim, but we see lots of governments taking this seriously in planning to grow education research and development in AI. Not only AI but also industries that use some fraction of machine learning as well.

A superpower like China alone has allocated over a hundred billion dollars for research in AI over the next ten years.

Secondly well, AI is awesome, it can certainly make our lives easier and sort of gives us superpowers, so who knows what we can accomplish with the help of machine learning and AI. And third, AI doesn’t work that well yet.

We can’t still ask our phones or any smart device to de much and to be honest we4 are far away from personal robot butlers. So, what’s next?

What is the Future of AI?

One way to think about the future of AI is to consider milestones AI hasn’t reached yet. Current football robots aren’t quite ready to take on human professionals and Siri still has a lot of trouble understanding what we are saying.

For every AI system, we can try and list what abilities would take the current technology to the next level.

Automated Driving Systems

In 2014 the society of Automotive Engineers attempted to work on the concept of automated cars. The engineers were able to define five levels of automation, for each additional level they expected that the AI controlling the car can do more without human help.

At level 1 cruise control automatically accelerates and decelerates to keep the car at a constant speed. At level 3 the car is basically on its own, it’s driving monitoring its surroundings and navigating and so on, but a human driver will need to take over if something goes wrong. At level 5 the driver has no intervention at all.

But idealistically speaking not all cars have this technology and the employed technology is not 100% functioning. So this leaves a huge gap for AI to still fill in.

Augmented Age

Due to the advancement of AI, we have entered into a new era, called the Augmented Age. The age where natural human capabilities are going to be augmented, by computational assistants that help us think, robotic systems that help us make and digital network systems that connect us to the world far beyond our natural senses.

If I ask the question as to how many of us are augmented cyborgs? All I would get is laughter. But the truth is we are already augmented, even though the augmentation is not like the movies that we see.

Imagine that you are at a party and someone asks you the question that you don’t know the answer to. If you have your cell on you, then in a few seconds you can know the answer. But this is just a primitive beginning.

Even Siri is a passive tool, in fact, before artificial intelligence, every tool that we have made has been passive. The tools do exactly what we tell them and nothing more.

So there is still potential for AI to not only generatively assist mankind but also play an active part in problem-solving. To understand generative let’s take the example of car design. The AI right now can also augment what the human is asking from it. But by working generatively the AI not only would be able to design a car but also present alternate designs.

That is when the AI would be able to completely understand the human so there is still a long way to go if we talk about complete augmentation.

Impact on Data

Part of the reason we expect so much progress is that people more than ever are learning how to build AI systems and all these problems have lots of data to train new algorithms.

In the past, it used to be hard to collect training data. Going to libraries to copy facts and transcribe books, but now a lot of data is already digital. If one does not know what is going on the other side of the planet, you can download newspapers or grab tweets from a Twitter API.

If one is interested in hyper-local weather prediction, then by combining free data from the weather service with personal weather stations to know when to stay indoors. Imagine this if all of this data is fed to a robot gardener we can have a fully automated weather knowing plant growing robot.

This data, when manipulated by an effective AI system, can take multitasking to another level. So the implications are numerous. This data can also be used to enforce the law as our personal information is being fed processed by systems running on AI.

Conclusion

So, there is still a lot to consider when it comes to the future of AI. AI is a really new tool and it’s great that so many people have access to it, but that also means that there are very few laws of protections about what can and can’t be done.

Innovations in AI have awesome potential to make positive changes, but there are also plenty of risks, especially if the technology advances faster than the average person’s understanding of it. So, it is probably more accurate to say that the future is complicated and the most important thing we can do is to be educated and involved in AI as the field changes.

Elizabeth content writer in USA.As a Digital Marketer. She specializes in writing Digital marketing blogs Custom iOS App Development Company US. She his created variations in the different type of subject app design and development.