What are the emerging trends and challenges in user scenarios for AI, IoT, and AR?

-How to give the AI context. -It took many years for users to learn UI design language. The same thing will happen with conversational and generative AI.

Given that AI systems and LLMs are an approximation of semantic intent, it's important to consider the best ways to communicate to a user that this AI system may make mistakes. Additionally, if accuracy is very important, consider ways to show and cite sources from other parts of the application in some sort of chat assistant. The common approach at this time is to show a couple of boxes below a chat message with links to other parts of the application. Ideally, the user is able to use the AI to surface and discover content that's available across their application. And similar to writing a script, also consider the UX of talking to an AI assistant. If it's overly polite, or too assertive, it can come across as rude.

Recently, I was using a new AI-powered virtual assistant to help with my daily tasks. I was impressed by how quickly and accurately it could respond to my questions and follow my instructions. However, I also noticed that it sometimes made recommendations that didn't align with my preferences. I found this to be frustrating. Now imagine a world where AI is so integrated into our lives that we are constantly interacting with it, even without realizing it. This could be a positive development, as AI could help us to save time, improve our productivity, and make better decisions. However, it could also lead to a loss of privacy and autonomy. For example, AI could be used to track our online activity and make predictions about our behavior.

One of the key concepts to consider and design for regarding IoT systems is the Information Architecture around the devices. Are their hierarchical relationships? Strict parent-child relationships or peer to peer relationships between the devices? The answers to these questions can also vary by the user role. Someone managing all IoT devices may need to see the relationships to the hub and the hierarchy by connection type; alternatively, a resident of a smart-home likely only cares about devices based on location or room. I would recommend "the polar bear book" on IA, as it's insights can be applied to IoT devices just as well as it can be applied to intranets and websites.

While building connected systems consider the best ways to meet a user where they're at. If the user is primarily interacting physically with the device, ensure that the primary use case is able to be accomplished via physical interaction. Devices should clearly communicate how they function. Reduce the number of buttons and screens if possible, label unclear buttons, and prioritize the highest impact interactions. Consider the user journey from start to finish and make sure that it is as seamless as possible, including sign up and privacy/security. Even if the person is tired, they should be able to effectively perform this task. Don't optimize for an attentive user, optimize for a user who is trying to build a habit and muscle memory.

I remember the first time I set up my smart home system. It was like something out of a science fiction movie. I could control my lights, thermostat, and even my locks from anywhere in the world with just a few taps on my phone. It was amazing! At first, I was a little overwhelmed by all the possibilities. There were so many things I could do to make my home more efficient and comfortable. But I quickly learned that the key to a good IoT experience is simplicity. I wanted to be able to use my devices without having to think too much about it. I used a single app to control everything, and I made sure that the app was easy to use and intuitive. The result was a home that was truly smart.

Augmented reality has a number of applications that can help improve the learning experience for students, especially for more visual focused learners. Augmented reality also enables students to benefit from at-home experiential learning. Students can run scientific and mathematical simulations in 3D space and view the results from every angle. For example, students can see how certain medications affect various organs in the human body. And they can adjust various physical conditions on a virtual planet to see how those conditions affect its ability to support life. This kind of learning is more likely to be remembered and understood by students compared to other methods.

UI/UX as it relates to AR are far from solved. At this point in time, they're very experimental. That said, it's worth it to take a look at Meta and Apple's documentation as it relates to their AR operating systems to use as a point of reference. For the most part, we're leaning on a trend of simulating a physical screen that floats with elements of 3D. In general, augmented reality can be easier in some ways because it leans very much on an imitation of the physical world. When in doubt, it's probably best to replicate things that exist in real life, just like skeuomorphism. As your users become more familiar, you can iterate into something that may be more convenient to develop and more simplified.

As an avid user of AR technology, I've had the opportunity to experience the magic of augmented reality in a variety of ways. One of my most memorable experiences was when I was using an AR app to learn about medieval history. The app allowed me to see 3D models of castles and swords, and it even let me hear the sounds of battle. It was as if I had been transported back in time. However, I've also had some frustrating experiences with AR. For example, I recently tried to use an AR app to help me find my way around a new city. The app was supposed to place virtual arrows on the ground to guide me, but the arrows kept disappearing and reappearing in different places. It was a total mess.

The trends and challenges are as follows; explainable AI, AI in edge computing, AI ethics and bias mitigation, conversational AI, 5G connectivity, etc. The challenges are also follows; Ethical challenges, data privacy, AI regulations, Security concerns, interoperability, hardware limitations, etc.