Artificial Intelligence continues to grow because of improvements in deep learning and GPU acceleration. Prediction is that AI will create a net increase of 58 million jobs by 2022, and is poised to transform how we do everything. AI advocates promise that our devices will soon know us better than our own families. But the question is can AI/ML be used in the here-and-now, as a tool rather than a whole consuming self-sufficient program? And how AI is influencing user experience?
Before We Begin: A Note on Terminology
You may have noticed that people are rather free with all the terms we’ve been using so far, even though most of them are not really sure what Artificial Intelligence and Machine Learning mean, as they seem to be used interchangeably. On the other hand, User Experience appears to be vaguer. This section is here to eliminate any doubts and resolve any confusion going forward.
AI is the most general term implying an algorithm acting with human-like flexibility. Machine Learning, however, is a subtype of AI, and it tries to achieve the goal of AI by designing algorithms that can learn, either based on training or experience.
User experience is how someone feels while using an interface. For computers, feelings are hard to process. So it’s best to say that user experience is the complex connection between the measurable behavior of a user interacting with an interface and the outcomes of the interaction.
Measurable Behavior and Testing
The first step when trying to understand something is to measure it. With UX this is difficult. Scientists have determined that bias always finds a way to creep into any observation, and the gold standard for research is double- or even triple-blinded studies. When it comes to testing interfaces, they often need interpretations.
This interpretation causes chaos: if the user is asked, then the UX designer must contend with the demand characteristic. Every participant in an experiment forms an idea of what the experiment is for and this immediately brings bias. Worse yet, if a designer is doing the testing, it’s inevitable they are biased as well.
The solution is to introduce a note of objectivity by using extended telemetry. Note the length of each session, where the user clicks, how long they take to do any operation, how often they fail, and how often they quit. A human analyst would drown in this sea of data but when it comes to a neural network, the more data the better.
The promise of chatbots
For most people, chatbots are still some intimidating automation that needs a lot of developers to be involved. Also, there’s a prejudice that chatbots are harsh and they can disturb the user experience.
The truth is that, if you do conversational design right, it can boost not only user experience, but your sales, ROI, and your employees’ work hours. The trick is to know exactly what you can and need to automate and to always leave an option for human connection. You also need to create conversations carefully - you can always start with FAQs. A chatbot can usually recognize only the user’s inputs that exist in the flow you made. especially if the language you use has complex conjugations.
That’s exactly the place where machine learning excels. AI chatbots are regular chatbots with the additional power to recognize fine lines from a user's sentences. The more users use your chatbot, the finer its recognition gets. And I believe you can see how that leads to improved UX.
What can we do about emotions?
Earlier, we decided not to guess what the user is feeling and simply track their behavior, but can’t we do at least a little guessing? Computer Vision offers a tentative ‘yes.’
Right now it’s possible to train a neural network to classify faces according to expressions that are associated with primary emotions — sadness, happiness, anger, disgust, fear. And the precision of getting the emotions right is improving. The problem is that the central idea: that facial expression maps directly to emotion is false. Different people simply show emotions differently.
The solution is the growing field of artificial empathy, where they study emotions in a broader context than just facial expressions. A fully general solution is still far away, but software tuned to a very specific emotional state, like anger or distraction is already in use, especially in high-risk situations like driving.
One step ahead of the user
Your app or website might be broad, but the paths the users take are surprisingly predictable. With A/B testing or heat maps, you can easily learn user behavior. Using that data can change the interface so that it corresponds to a path that’s more likely to be traced from your average user.
From recommendation systems to targeted advertising, this level of analysis is possible thanks to machine learning. In particular, AI can be fed with bis sets of user actions. They can be sorted by the user. Machine learning can then produce either universal insights or ones tailored to a specific user.
AI isn’t magic
Certainly, AI isn’t a wand you can wave to make your UX problems go away. But it’s a powerful tool. It’s a regular Swiss army chainsaw that can solve most UX problems in multiple ways.
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Today, all famous mobile packages are coherently constructed through setting UI/UX layout into attention.User Interface: A mobile user interface (mobile UI) is the graphical and usually touch-sensitive display on a mobile device, such as a Smartphone or tablet, which allows the user to interact with the device's apps, features, content and functions.User Experience:Mobile user experience (UX) design refers to the design of positive experiences during the use of mobile devices and wearable’s, and applications or services running on such devices.
Mobile UX design focuses strongly on efficiency and discoverability.Important aspects of UI and UX design:General use of common colours, symbols, buttons, font style and make that help to persuade the Users and make them greater acquainted the usage of your app.
By making theElements of your simple, you do now not want a manual to demonstrate how your app works.A proficient UI/UX designer informs the users about every ongoing system on the app thru notifications, for instance, whilst loading content, the consumer must be knowledgeable at theDisplay screen that something is loading.
So they must make their contents load very speedy while designing the app.Mobile application development is much more than exclusive and engaging designs.
A much bigger need is a seamless flow of the app for the users with every action they take and also easy to understand content plays a vital role in the complete design.As encouraged by way of the Apple, about 44 pixels rectangular will become the perfect for a touch.
You ought to design your app person-centric thinking about a finger length primarily based on endorsed size.When the use of buttons, visual cues or toggles, gradients and shadows play a important position.It is useful in making UI herbal to your customers.
User experience design is hardly a novel discipline.
However, with the rise of adaptive, responsive, and other forms of mobile-centered design, the question of finding the sweet spot between performance and experience has never been more relevant.This article will focus on some crucial factors to consider when designing a responsive and overall high-quality experience.A separate mobile website will renter faster but will likely cost more to build and maintain.
Conversely, a responsive website is simpler and quicker to build upfront, but there may be some hiccups in the implementation phase.Read More
eLearning content developers are experiencing several problems in mobile teaching and learning: technical learning, digital content development, curriculum design, education for both teachers and learners, IP protection and network stability.To design a good educational mobile curriculum or program, it is important to understand students’ needs and requirements as well as the technologies available.
Not all contents are suitable for m-Learning like a 2 GB video of a class on a mobile device with a 4G connection could be too costly.
should be taken into account while designing a decent mobile teaching program.Learner-Centred DesignUser-centred design and Learner-centred design seems like a similar word but are way apart from each other.
User-centred design is to support a task completion, whereas learner-centered design helps in remodeling the experience around the learner.
Design and development of both user-centered and learner-centered practices are required for m-learning.Learning performance can be beheld by looking into several aspects of design like:a) Motivational lessonsb) Re-Conceptualization, Re-Contextualization and Application of the materials must be done in a parallel manner.c) Feedback session.d) Supporting learners preferences like language, format etc.
preferred by the learner.e) Location-based learning experiencesMobile sensitivity and behaviorIn today’s world, people expect to have a full control over a mobile interface.
About 33% of people would rather read something with a beautiful design than something plain if they have 15 minutes to consume content.
This is just one example of the modern consumer’s preference for a good experience.We now have MedTech, FinTech, MarTech, RegTech, and a lot of other infusions of tech in different domains.
With digital interactions, both official and personal, growing considerably since last year, marketers are competing neck-and-neck for gaining consumers’ trust and loyalty.
All marketers know that it is the experience age, where products are not just utilitarian.
What role does UX play in this modern world?Modern User ExperienceModern User Experience creates experiences for consumers that are personally relevant, meaningful, and add value to their lives.
Reaching the insides of a user’s mind and defeating all kinds of confusion, questions, and problems is the aim of UX.
