TOP PRINCIPLES OF DESIGNING A GOOD ARTIFICIAL INTELLIGENCE PRODUCT.

///TOP PRINCIPLES OF DESIGNING A GOOD ARTIFICIAL INTELLIGENCE PRODUCT.

TOP PRINCIPLES OF DESIGNING A GOOD ARTIFICIAL INTELLIGENCE PRODUCT.

 

TOP PRINCIPLES OF DESIGNING A GOOD ARTIFICIAL INTELLIGENCE PRODUCT.

Do you need the top secrets to build a good, useful and highly patronize AI products? Have you been surfing the net on the amazing principles to abide with in other to design and build a robot and machine learning devices that will solve human problem?

 

With the adoption of AI products, where robots and machines are behaving and performing different functions. Almost every sector is engaging their service in performing certain orders as such changing how we react, behave and our certain expectations from these products.

 

With influx of people embracing the artificial intelligence and machine learning, it is paramount for AI designers to put some certain principles into consideration. Designing a product with less important to users wouldn’t bring the desire out comes, hence, you need to strictly abide by the principal of good AI products designs to be discussed below.

TOP PRINCIPLES OF DESIGNING A GOOD ARTIFICIAL INTELLIGENCE PRODUCT.

In the same vein, if you are a designer who wants to create a understandable and easy-to-use products in to order to bring clarity to the coarse realm of machine learning. And also, if you are passionate about using the ability of AI to change people’s lives for better and bring them joy, then the below principles need to be carefully observed.

 

Principle 1: Differentiate AI content visually.

One of the principles an AI products designer need to put into consideration is using visuals to make descriptions between products. In many cases, artificial intelligence and machine learning are used to dig deep in generating data and useful content by various users.

 

It may be use on Netflix in form of movie recommendations, on CRM as sales predictions or on Google Translate for words or sentence translations. While AI generated content may look extremely useful for various users, instances abound where these predictions and recommendations requires greater accuracy.

 

Principle #2: Explain how machines think.

Often, Artificial intelligence does look like sort of magic: in fact, engineers sometimes have problem defining how some certain machine learning algorithm was developed to have comes up with something brilliant and exceptional.

 

Provide some kind of help so that people can better understood how machines work and it will enable them to make judicious use of them. Essence, this doesn’t necessarily mean you have to explain all the steps involved in building it or how a convolutional network works in a search up. But rather, a well detailed guidance or hints on what kind of functions the algorithm perform or what data does it use.

 

Principle #3: Identify and handle awkward cases.

It is quite obvious that a machine cannot think as human do, so be informed that an AI can generate content on it own and take actions nobody would have thought of. Thus, for such unforeseen cases, designers is encouraged to spend enough time test running the products in a bid to detect any weird, awkward or unpleasant edge cases.

 

Also, if you are passionate about using the ability of AI to change people’s lives for better and bring them joy, then the below principles need to be carefully observed.

 

Principle #4: Make the right training data available for engineers.

Also, the fourth principle a designer need to take cognizance of in order to produce a good and useful products is to make the right training data available for engineers. As such, clear and simple communication about such products capabilities will be of great help to humans in understanding them during unexpected situations.

 

That is to say, creating a useful AI device from the engineering desk often takes three bold steps and among them is identifying the perfect AI algorithm for their task and feeding its training data. So artificial intelligence learns and creates a certain prototype to be user for the live product from such data.

 

So, making a training data available is necessitated because engineers will need it — specifically — for an efficient outcome for varieties of inputs they will feed into the MLA.

 

Principle #5: Always test your designed AI products.

This principle is of utmost importance, and it must be treated as such. As a designer, when you are designing with AI, that means you are designing a machine that learns, grows and work with functionality that stand the chance to be changed over time (thanks to various software updates), hence, using a default method to test run your product won’t work well.

 

There are two amazing methods that can work well with it, and they are, personal testing and the Wizard of Oz. You can use the personal content test participants in any test situations of your designs. This tests people’s assumptions plus how they feel to better and bad recommendations.

 

However, products should be designed in such a way that will give room for growth and development since they are no longer immutable – unlike before.

 

End Note

The above discussed on the five important principles to be considered in other to design a good AI products needs to be handled with care, hence, with your designed AI products, mountain Everest could be moved!

By |2019-01-17T02:29:31+00:00January 17th, 2019|Blog, Technology Guide|0 Comments

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