Using Generative AI in UX Design

 What is Generative AI?

Generative AI refers to a class of artificial intelligence algorithms that are designed to create new and original content, such as images, videos, text, and music. These algorithms use deep learning techniques to learn from a large dataset and generate new content that is similar in style and structure to the original data.

Generative AI can be a powerful tool in UX design by helping to create new and innovative design concepts that would be difficult for a human designer to imagine. 

Generative AI can be used in UX design to speed up the design process, improve user experiences, automate repetitive tasks, and enhance design creativity.

Using generative AI in UX design:

1. Automating design tasks: Generative AI can be used to automate repetitive design tasks, such as layout and composition, freeing up designers to focus on more creative tasks.

2. Creating design variations: Generative AI can help to quickly generate a wide range of design variations based on specific design requirements. This can help to speed up the design process and provide designers with a range of options to choose from. 

3. Personalizing user experiences: Generative AI can analyze user data and behavior to create personalized design experiences that cater to individual user needs and preferences.

4. Improving usability testing: Generative AI can be used to create realistic simulations of user interactions with a design, which can help to identify potential usability issues before the design is implemented.

5. Enhancing design creativity: Generative AI can be used to inspire new design ideas and concepts by generating unique and unexpected design elements that designers may not have thought of.

6. Creating writeups: Generative AI can be used to reduce the work of preparing long writeups such as interview scripts, survey questions, sample content for the prototypes, tasks and scenarios etc. ChatGPT is a great platform to help in this specific needs for UX designers.

Astounding Artificial Intelligence Statistics for 2020

Artificial intelligence is poised to transform the way we live, from everyday tasks to complex, large-scale projects. Our future will be molded by machine learning and automated systems. These mind-warping artificial intelligence statistics are all you need to prepare you for the artificial intelligence revolution.

Key artificial intelligence facts, editor’s pick

• Chatbots are expected to cut business costs by $8 billion.
• About 15% of surveyed companies use AI, primarily for improving customer experience.
• The percentage of help-wanted ads requiring AI skills is 4.5 times higher than in 2013.
• The median salary for senior computer scientists and managers in  machine learning is more than $127,000.
• Google’s deep learning prediction algorithm correctly diagnoses suspected tumors 89% of the time by analyzing medical heatmaps.

Artificial intelligence has come a long way since IBM introduced a mainframe that could play a competitive game of checkers. Today’s advanced AI systems are transforming the economy, culture, and even politics.

Current AI technology can be roughly divided into “weak” and “strong” AI. A perfect example of weak AI can be found in your living room in the form of smart speakers. Siri, Echo, and Alexa all have programmed responses to certain demands.

Strong AI, on the other hand, is the most important and interesting artificial intelligence technology today. Strong AI is the kind of AI featured in sci-fi movies. It aims to emulate the human cognitive process by grouping various concepts together in associational clusters. While strong AI has a long way to go before we see widespread use, there’s no doubt that it will profoundly change our lives once it passes the prototype stage.

All in all, scientists believe that the future scope of artificial intelligence will encompass almost all human activities. Here are some AI statistics to prepare you for the brave new world that lies ahead of us.

Chatbot Statistics

1. According to Gartner’s AI customer service statistics, chatbots will be responsible for 85% of customer service by 2020

(Gartner)

Artificial intelligence is still far away from taking over sales jobs, but it has proved more than useful in the customer service department. Modern chatbots learn by trial and error and gradually improve their understanding of customers’ questions. Customer service is the first among many boring jobs that will be taken over by AI.

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2. According to Crunchbase’s AI stats, more than 10,000 developers now work on building chatbots for Facebook Messenger.

(Crunchbase)

Facebook has proved itself an excellent platform for businesses to share their products. In fact, many companies use Messenger as a dedicated customer service platform.

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3. Juniper’s statistics about artificial intelligence say that chatbots could save businesses $8 billion.

(Juniper)

Although many companies already outsource customer service and try to save money that way, the truth is, it’s still expensive. Thankfully, we’re not that far from a future where AI will handle almost all customer service.

Business and AI Statistics

4. An Adobe artificial intelligence report says that only 15% of surveyed companies use AI – primarily for improving customer experience.

(Adobe)

However, the artificial intelligence statistics also reveal that 31% of those not currently using AI intend to use it within the next 12 months. In addition to improving CX through on-site personalization, companies also rely on AI and data to refine their marketing methods.

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5. Start-up companies that use artificial intelligence have increased 14-fold in number since 2000.

(Stanford)

The popularity of artificial intelligence has quite literally surged in the past two decades. With such impressive momentum, there’s no doubt we will see a huge supply of jobs in artifical intelligence.  AI courses have increased ninefold in academia in the last 20 years. Enrollment in AI-related courses at Stanford has surged 4,500%.

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6. The percentage of help-wanted ads requiring AI skills is 4.5 times higher than in 2013.

(Stanford University)

While it was believed that AI technology would be replacing humans in the workplace by now, causing widespread unemployment, the truth is quite the opposite. With more and more companies using AI, there will be a steady increase in demand for experts in the field.

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7. The three most desired AI skills on Monster.com are machine learning, deep learning, and natural language processing

(Forbes)

It’s also worth noting that the average machine learning manager makes a salary of $127,000 or more. Artificial intelligence experts earn an enviable salary.

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8. 84% of company representatives believe that investing in AI can bring more competitive advantages.

(Statista)

In fact, according to Statista AI industry statistics, 75% believe that AI has the potential to open up new businesses. They think AI and business will be inseparable, especially when it comes to giving entrepreneurs a better foothold in existing markets. About 63% state that the shift to AI will be primarily driven by a desire to cut operating costs.

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9. Forbes AI statistics state that 87% of early AI adopters say they are using or considering using AI for sales forecasting and improving email marketing.

(Forbes)

In addition, 61% use artificial intelligence for market forecast purposes. AI can efficiently navigate the hectic world of international commerce by applying big data analysis and pattern recognition in real-time, enabling marketers to create valid long-term strategies.

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10. 40% of business leaders believe AI will increase worker productivity.

(Accenture)

Accenture’s AI work statistics say AI has the potential to double annual economic growth rates by 2035. In addition to financial gains, AI’s biggest potential lies in the fact that it can fundamentally change the nature of work and the relationship between humans and technology.

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Credits: This article is originally published at Kommando Tech

About author

Jovan Milenkovic

Kommando Tech

User Experience in Artificial Intelligence

Two years back, Toyota offered us a glimpse into their version of the future where surprisingly, driving is still fun. Concept-i is the star in the autonomous future where people are still driving. And in the case of Toyota, it's so much fun because they're cruising along with their buddy Yui, an AI personality that helps them navigate, communicate and even contributes in their discussions.

Yui is all over the car, controlling every function and even taking the wheel when required to. It's definitely an exciting future where the machine sounds and “feels” like a human, even exhibiting empathetic behaviour.

Related: Preparing for the Future of AI

That's the kind of future I'd imagine awaits user experience (UX) in the world of AI. A time when the human-AI connection is so deep that some experts say there will be “no interface.” But currently, UX does depend on an interface. It requires screens, for instance, and they don't do much justice to it. Integrating AI into the process will mean better experience all around.

From websites to homes and cars, here's how AI could help patch the holes and bring UX closer to maximum potential.

1. Complex data analysis.

Until now, to improve user engagement in their products, UX teams have turned to tools and metrics such as usability tests, A/B tests, heat maps and usage data. However, these methods are soon to be eclipsed by AI. It's not so much because AI can collect more data -- it's how much you can do with it.

Using AI, an ecommerce store can track user behaviour across various platforms to provide the owner with tips on how they can improve their purchasing experience, eventually leading to more sales. AI can be used to tailor the design to each user’s specifications, based on the analysis of the collected data.

All this is achieved through the application of deep learning that combines large data sets to make inferences. Additionally, these systems can learn from the data and adjust their behaviour accordingly, in real time. Thus, designers applying AI in their work are likely to create better UIs at a faster rate.

2. Deeper human connection.

By analysing the vast amount of data collected, AI systems can create a deeper connection with humans, enhancing their relationship. This is already happening in a couple of industries. When you think of Siri, you see a friendly-voiced (digital) personal assistant. When Amazon first introduced Alexa, it took the market by storm. But its usefulness could only be proven over time. And it was. Smart-home owners are using it to do a million things, including scouring the internet for recipes, schedule meetings and shop. It's also being used in ambulances. Even Netflix’s highly predictive algorithm is a case example of AI in use.

Toyota says Concept-i isn't just a car, but a partner. From the simulation video, you can see that Yui connects with the family on a level that current UX doesn't reach.

By using the function over and over, consumers end up establishing an interdependent relationship with the system. That's exactly how AI is designed to work. You use the system; it collects data; it uses it to learn; it becomes more useful; gives better user experience; you use it more as it collects data, learns and becomes more useful; and the cycle continues. You don't even see it coming -- and before you know it, you're deeply connected.

3. More control by the user. 

A common concern about the adoption of AI to everyday life is whether the machines might eventually rise and take over the world. In other words, users are concerned about losing control over the systems. It's a legitimate concern with the autonomous cars, robots guards and smart homes expected to become commonplace.

This lack of control is mirrored in the skepticism for the future, but it can also be seen in commerce and other areas where user experience is of great importance. For instance, a user will be more likely to enter their card information into a system if they feel they have control over when money is transferred, to whom it goes and that they can retrieve it in case something goes wrong.

As AI develops, users will gain more control over the system, gradually improving trust which will lead to more usage. 

In Which AI Could Enhance Your Company's UX 

UX design is about a designer trying to communicate a machine's model to the user. Meaning, the designer is trying to show the user how the machine works and the kind of benefits they can get from it, from the former's point of view. 

Traditionally, this involved following certain rules, and designers understood them very well. A designer knows how to create a web page by following certain rules that they can probably manipulate. With AI, however, the design is dependent on a complex analysis of data instead of following sets of rules. To be able to design using AI, designers will have to really understand the technology behind it. 

Mixing UX and AI as we can have played with “AIBO” 

Artificial intelligence

Artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience. Since the development of the digital computer in the 1940s, it has been demonstrated that computers can be programmed to carry out very complex tasks - as, for example, discovering proofs for mathematical theorems or playing chess - with great proficiency. Still, despite continuing advances in computer processing speed and memory capacity, there are as yet no programs that can match human flexibility over wider domains or in tasks requiring much everyday knowledge. On the other hand, some programs have attained the performance levels of human experts and professionals in performing certain specific tasks, so that artificial intelligence in this limited sense is found in applications as diverse as medical diagnosis, computer search engines, and voice or handwriting recognition.

What Is Intelligence?

All but the simplest human behaviour is ascribed to intelligence, while even the most complicated insect behaviour is never taken as an indication of intelligence. What is the difference? Consider the behaviour of the digger wasp, Sphex ichneumoneus. When the female wasp returns to her burrow with food, she first deposits it on the threshold, checks for intruders inside her burrow, and only then, if the coast is clear, carries her food inside. The real nature of the wasp’s instinctual behaviour is revealed if the food is moved a few inches away from the entrance to her burrow while she is inside: on emerging, she will repeat the whole procedure as often as the food is displaced.

Fixing the AI in real time

Problem solving, particularly in artificial intelligence, may be characterized as a systematic search through a range of possible actions in order to reach some predefined goal or solution. Problem-solving methods divide into special purpose and general purpose. A special-purpose method is tailor-made for a particular problem and often exploits very specific features of the situation in which the problem is embedded. In contrast, a general-purpose method is applicable to a wide variety of problems. One general-purpose technique used in AI is means-end analysis—a step-by-step, or incremental, reduction of the difference between the current state and the final goal. The program selects actions from a list of means—in the case of a simple robot this might consist of PICKUP, PUTDOWN, MOVEFORWARD, MOVEBACK, MOVELEFT, and MOVERIGHT—until the goal is reached.

Many diverse problems have been solved by artificial intelligence programs. Some examples are finding the winning move (or sequence of moves) in a board game, devising mathematical proofs, and manipulating “virtual objects” in a computer-generated world.

About Author

Jagannathan Kannan
UX Lead Designer @ Verizon wireless
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