DON'T MISS A UX THING

Here's what Mr. Jakob Nielsen had to say following Sam altman's keynote:

After listening to 45 minutes of Sam Altman’s keynote at the OpenAI conference on Nov. 6, it was striking that the words “UX” or “usability” were not included among the almost 7,000 words in the keynote.

You can watch the keynote for yourself on YouTube.

The word “UI” was mentioned once, in the context of a demonstration of how to integrate AI features within a travel application that was being built on stage. Indeed, the UI was quite nice, in terms of presenting a map of Paris that dynamically updated as the user was asking about tourist attractions to pinpoint their location. While this feature is old, what’s interesting is that the AI took it upon itself to visualize the location of the tourist attractions without the programmer having to add the feature to the app. In many ways, this demo reminded me of Bill Gates’ demos at Comdex 30 years ago, where he would also show how “easy” it was to build cool features with various new tools he was hawking. It was never as easy for the developers back home.

It’s promising, but scary, when the AI is not just employed to answer users’ questions but also to introduce features into an application without the designers or developers having specified those features. In the demo, the AI-injected feature was useful and worked well, but one can also fear the consequences of rogue AI features for user experience.

OpenAI was pushing a new type of custom-built bots, called “GPT,” that you can train with specialized knowledge, for example, by uploading a corpus of your past content. This seems useful, but also potentially confusing since there will likely be an overwhelming number of such bots on the botstore. I’m reminded of the mobile platforms’ app stores.

An unconvincing demo showcased the use of a custom bot from Canva: first, the user asked the bot in natural language to design a poster for a certain event. This resulted in a range of options, similar to the current use of Midjourney. The user would pick a preferred design, which would then be transferred to Canva for further refinement with the normal Canva design tools. This disjointed user experience evidenced a stunning lack of integration and cannot be the road ahead.

Accessibility was mentioned, when discussing the ability of ChatGPT to describe visuals. Blind users can use this to find out what’s in front of them — definitely a positive development. Though, as a usability expert who has been involved in usability studies of disabled users, I’ll add that just getting a verbal description read aloud doesn’t provide the usability that people need if they can’t see things. The most helpful description depends on the context: what the user is trying to do. A longwinded description that covers extensive irrelevant aspects of the scene will delay users and be more annoying than helpful. Knowing the context of use is critical for any good accessibility feature. I hope AI will learn how to adjust its verbal descriptions to the users’ needs, but this area needs work and won’t happen on its own.

My primary point has always been to treat disabled users as users first and foremost. The usability criteria are the same whether or not people can see: they must be able to accomplish their tasks quickly and easily. Converting visuals into speech is only helpful if the text is short and to the point relative to the user’s task.

The announcement of ChatGPT 4 Turbo was greeted with enthusiastic applause when Altman mentioned that the different modes will now be integrated so that users won’t need the mode-switching menu to change between, say, generating images and working with text. While the dirty word usability wasn’t mentioned in the presentation, this will surely be a usability improvement for the product. People who study the history of UX have known since Larry Tesler’s work to eradicate modes from the Apple Lisa around 1980 that UI modes are bad for usability.

The more technical upgrades to GPT-4 will certainly have UX benefits. A bigger context window will allow us to work with more data without workarounds, which will be particularly helpful when analyzing qualitative user data. The lower prices for developers using GPT through the API will support the creation of a broad range of new innovative applications. Many will be bad, but some will be great, and experimentation will give us a new class of user experiences that we don’t envision today.

Sam Altman was quite aggressive in pushing AI agents as the next step. Agents will interact with the world rather than just answering questions about the world, as is the case for ChatGPT now. The demos were primitive, and as always with demos worked perfectly. From my perspective, the broader tasks we attempt with AI, the more we need both task analysis and good UX design to ensure a smooth workflow and user control.

So, what do we have on our plate?

Responding to numerous requests, I'd like to provide a summary of Meta's launch highlights, paired with some interesting UX insights.

Let's talk about the Quest 3 Glasses first. These are not just any glasses. They offer a mixed reality experience unlike any other. Being lighter in weight, they boast a 30% better resolution. What's more, they are free from the shackles of cables, can instantly recognize your surroundings without you needing to calibrate them, and can even recognize hands, making controllers a thing of the past. Now, if you delve deeper into the world of mixed reality, you'll realize it's all about blending the digital with the tangible, the real world. This gives birth to countless applications, from interactive games that mold themselves to fit your room to immersive experiences like gazing out of a virtual window.

Moving on, let's dive into Meta's AI Innovations. The name of the game? The Llama2 Engine. Facebook has pulled out all stops to enhance this engine, and yes, it's named after the animal. They've launched its variations in the media realm. The standout feature here? The creation of diverse AI personas. Each one comes with its own distinct personality designed to assist users in various fields and activities. And here's a nugget of information: this engine, now paired with Bing, is adept at recommending web content and can fetch answers directly sourced from the vast expanses of the web. On a side note, I find it interesting that Meta seems to have taken inspiration from an idea I floated a while ago. I'd suggested a design revamp for the ChatGPT platform where AI personas came with their own areas of expertise. Meta's current approach feels eerily similar, with AI models representing distinct personalities and skills.

But that's not all on the AI front. Meta has also unveiled the AI Studio. This platform allows users to craft an AI persona that mirrors their own character. I believe this is a game-changer, not just for individual users, but for businesses as well.

And then there's the Emu Image Engine. And before you ask, yes, it's named after another creature of the desert. Emu is designed to create visual representations from textual descriptions, adding a new dimension to conventional messaging.

Last, but by no means least, let's discuss the Meta-Ray-Ban Glasses. These are a substantial upgrade from their predecessors. Their design is more ergonomic, the in-built cameras are of superior quality, and they come loaded with groundbreaking features. One such feature is an integrated AI vision. This allows users to live stream what they're seeing in real time. The options are plenty: you can seamlessly switch between streaming from your mobile device or directly from the glasses. And for those keen on real-time data, these glasses provide instant feedback.

Drawing a parallel, if you were to compare these glasses to Google's earlier smart glasses iteration, you'll find that Meta's offering is in a league of its own. By combining data with AI, Meta has managed to revolutionize the user experience without compromising on the glasses' primary function.

In conclusion, Meta's foray into these technological realms underlines the rapid strides we are making. What was once seen as futuristic is now within our grasp. Meta’s seamless fusion of AI into our daily lives means that whether you're an entrepreneur, a designer, or just an enthusiast, you're about to witness a significant paradigm shift in your respective domains.

And for those deeply embedded in user experience, the path forward is rife with challenges and opportunities. The horizon is expanding, from envisioning broader customer journeys to pioneering the interface of human-digital interaction. Think beyond screens; think audio. There's a new realm awaiting exploration, a realm where audio, data, visuals, and AI coalesce. The future is about leveraging real-time information from the web and ensuring seamless communication with AI assistants.

Regardless of where you stand in the tech ecosystem, Meta’s latest offerings compel us to widen our perspective. It's an invitation to immerse ourselves in technology and explore how it seamlessly integrates with user experiences.

For those looking for an even deeper dive with rich visuals and details, I'd recommend visiting the Verge blog. You'll find a treasure trove of information there.

It is surprising, but even today there is a discussion about the business importance of design and the contribution it has to business is not obvious. At the end of 2018, consulting firm McKinsey published a report that sheds light on the clear business value and unambiguous competitive advantage that design can produce.

If you still have a hard time to convince them, this is the magic link you need to send to your managers and customers. We know they do not have the patience to read the whole thing, so we've summarized what's important.

The most significant study to date
McKinsey claims to have carried out the most in-depth research ever undertaken to uncover what actions product leaders can do to maximize business benefits through design.

For five years, McKinsey representatives have studied the design processes of 300 public companies from a variety of industries and countries. They analyzed over 2 million financial records and identified 12 design actions that have the most impact on the bottom line. The 12 actions were divided into four main content areas. This model is used as a new measure called the McKinsey Design Index (MDI), which is used to rank the quality of companies.

Starting from the end, the business performance of companies with a high MDI score is twice as good as that of companies with low MDI scores - both in profitability and return on investment for investors in all areas examined including medical products, consumer products, and banking.

Another interesting insight was that the business value generated in the upper quartile was significantly higher compared to the relatively small differences in the companies' business values by bottom 3 quarters. In other words, the market disproportionately assesses companies with the highest level of design.

Guidelines
So what are the 4 magic principles that make for great business?

1. More than "just feeling" - the understanding that analytical leadership is required for design
The first principle is the understanding that design is a subject that requires management leadership and direction, and that the performance of the design needs to be measured in the same way that the company's expenses and revenues are measured.

In most organizations, it appears that the design is a secondary element. It remains at the level of junior management and the organization’s decisions on design issues are made according to gut feelings rather than concrete and clear evidence.

2. More than "just a product" - the understanding that we create a user experience
The second principle is the holistic observation of the user experience by breaking of the walls between the customer’s physical conduct, digital behaviors and the service experience. We live in an age when a smartphone can warn you to leave earlier than planned in order to arrive at a meeting on time.

Leaving the boundaries of the product itself and focusing on the entire customer journey should form the basis of conversation at every meeting around the product. In practice, only around 50% of companies say that they carried out some sort of user research before designing the initial design version of their product.

3. More than one department in the organization
In companies found in the leading quarter, it is overwhelmingly felt that user-oriented design is the responsibility of everyone, not just one department. On the one hand, lateral attention and general awareness of the importance of design are required, and on the other hand, the design community must be nurtured. It turns out that designers belong to 2% of the most influential business. The study found that leading companies paid three times the average compensation for designers and also gave out prizes for the greatest business contribution to design.

4. More than one step in the process - design is an iterative process
Design culture develops in an environment that encourages learning, testing and Iterative work processes with users. These processes produce significantly better products, reduce risk and reduce development costs. In practice, the principles of iterative design and learning are contrary to the processes that exist in most organizations. The best product results come from processes where user research is performed repeatedly throughout the process.

Current situation
According to the study, 40% of companies still do not include users in development stages, and over 50% of companies do not have objective measures to measure the quality of product design.

Summary of principles
The four principles that make the most significant contribution to business success are management’s awareness of the importance of design, leading a culture of measurement and control of design, a lateral view of the customer experience and breaking the walls between the digital product and the rest of the content world.

Well, have you sent this to anyone already?

Fabricio Teixeira reminds us of the basic evolution of products.
Successful products usually start from a good solution to a small and focused problem. Over time, the product team realizes that additional problems need to be solved. In response, they develop additional product components and try to answer additional usage scenarios until the product becomes too complex. Interestingly, we almost never download components from the product.

The need to expand the product parameters usually stems from customer demands, the identification of additional business opportunities and the assumption that if we expand the scope of the product, the business opportunity will also expand.

After we set out with broadening the product scope by adding capabilities, it becomes very difficult to go back. From that point, when we reduce the product's capabilities, it becomes very difficult to answer the question of how many people use the component and whether its change will produce resistance. In addition, it becomes very difficult to prioritize the removal of existing capabilities higher that are higher than the creation of new capabilities.

As usual, a new and fresh product comes up, which can do exactly what is needed in a simple and precise way. In the process taking all of our customers…

When thinking of successful products such as Dropbox, Trello, Slack, Lyft and even Twitter, every successful product has been able to focus on one precise business value that guides every other product components including design, branding, communication, components and structure.

The idea of a targeted product that does less and better is not a new idea. For example, Dieter Rams, the German industrial designer who is recognized as one of the most influential designers of the 20th century, is famously quoted for saying "Less, but Better".

This is an opportunity to emphasize the principles that help to maintain a focused product:

• Identify the essential features that your product needs. Now cut them in half and cut them in half again. This way of thinking will help you identify and distill what really matters.

• By analyzing product usage information, you can identify your significant components and locate the components that are not being used.

• Set the maximum number of components that you should not exceed.

• Most importantly, you must learn to say "No!". Try it a few times and you'll find that over time it gets easier.

Fabrizio recommends that you stop for a moment to look at your product and see if you are still focused.

You'll find that this way of thinking will help you make better products.

Eugen Eşanu revisited the legendary book Don’t Make Me Think by Steve Krug and checked if we were able to implement the ideas brought up in the book.

The article in UX Planet begins with an important quote by Jacob Nielsen. He said that the human brain's ability does not change every year. Therefore, the insights we have about human behavior have a long shelf life. Things that were difficult for us twenty years ago are still difficult for us today.

• We continue to invent new solutions
While we try to making exciting new innovations and feel that doing what others do is wrong, users are impatient and want to learn as little as possible. Before you invent the next thing, it is important to ask yourself whether your users need anything new in the context of the product in question.

• We continue to write a lot of text
Today websites tend to include a lot of text; however, users tend to scan rather than read. Users view written content as a task they are trying to complete. As such, they will read only what they must.

• How do I get users to read?
Using lots of headers, short paragraphs, bullet lists, and carefully highlighting important terms on the page (do not overdo it) will help encourage users to read.

• We continue to write instructions for users
Self-explanatory product design is no longer an option. It is the only option. We need to minimize instructions and explanations to zero and design products that are obvious to use. It is important to remember that our users do not care how our product works. They just want to be able to complete the task at hand and move on.

• We continue to let opinions and emotions lead us
It's hard to avoid the moment of thinking that you are the users too and know what is good or bad.

• We continue to ask the wrong questions
In everyday conversation, we tend to ask - "Do people like drop-down menus?” instead of checking whether it is the best way to help people navigate the current task. Instead of asking what people what they like or prefer, we need to look at our solution in the context of the task at hand and see if people can successfully perform it.

• We continue to make people think...
Effective product planning should make sure that people who use it will never have to ask questions like –
o Where am I?
o Where do we start?
o Where the hell is the button?
o What does this term mean?
o Is this an advertisement or part of the page?
o Should I click on it or not?

People might like challenges; however, not in the context of trying to complete the task at hand.

The principles that Steve Krug presents in the book "Don’t Make Me Think" remain relevant and it is worthwhile to go back sometimes and remind ourselves not to miss the basics.

A study was conducted to test eye-tracking and comparing different kinds of click-ability cues. The results show that week signifiers have an impact on the way that users comprehend web pages. 71 General web users were recruited to take part in the experiment. Nine different sites were tested. A "strong" and a "weak" version of the same sight were compared side by side. The participants were asked to find a specific UI element that was meant to be clicked on. Once found they would call out that they found it and then stop. During the study, the participants eye movements were tracked. The two key components that were measured were "fixations": when the eyes linger on one area of interest, and the amount of time it took to complete a task. Essentially, it took longer to find the click-able parts of the weaker designs this increases the likelihood that people click on something other than what they were looking for. Likewise, there were more fixations associated with the weaker design. In general terms, this means that users were less engaged with the web page. Less engagement means bad news. This article offers a significant amount of visual data representations to back up the research that was conducted. The fastest way to summarize this article would be to say that: the weaker the clickability, the more time is wasted for the user and the more uncertain users feel; this leads to depleted traffic over time.

After delivering a world-shattering report on usability that was fully hyperlinked with reproducible methodology, the expectation was that academics would be praising it all over the world but instead, nothing happened and a full two years afterward, none of the original findings had translated into product action.

This newly-minted researcher asked himself ‘why didn’t that work??’ and it set him on a six year journey that is still going forward. This question has been transformed into something more complex. It has gone from why didn’t it work to what does it take for research to positively influence product and design and how do I do that? Of course, a complex question has a complex answer.

It is a broad interplay of dynamics of people, structure and processes. Success lies in the mastery of the research process, technique and ability to influence the team.

This can be done by thinking which means process mastery and ownership of the research process, execution which means technical competences in technique, method and output, and impact which means organizational influence, empowerment, alignment and direction. The research process is somewhat linear: first comes figuring out what to learn, then deciding how to learn it, followed by uncovering and observing evidence, then making sense of what was learned (synthesis or insights) and deciding how to act on what was learning and finally ensuring consistent action.

There are three levels of researchers. At a junior level, the process mastery focuses on who, what and when, the technical competence focuses on recruiting, interviewing and interview notetaking and debriefing, observation, data collection, surveying, user testing, and simple reporting. Influence should be making a credible report, a fair and honest judgment of product and design and interaction level and usability authority. A mid-level researcher should add what and why to the process, project planning and management, structured design and research methods and complex synthesis to technique and embed and partner with functional teams, empower other project teams, reframe and focus research questions and develop a respected point of view on product level decisions.

A senior level researcher should add why and the ability to shape, reframe or reject the entire process accordingly to process mastery, centralizing customer feedback, roadmap planning, framing and storytelling, and workshop facilitation to technique and strategic partner to product design and functions, reshaping higher order processes, centralizing and unlocking existing knowledge and direct organizational research focus to influence.