I am honestly getting more than a little weary of the constant territorialism in our industry. It is perhaps a natural consequence of a relatively new discipline still trying to find its footing, and define its role and identity, but I wonder how meaningful it really is, and how much of it is just a distracting knee-jerk reaction.

As UX work becomes more prevalent and more commonplace, we see practitioners defensively narrowing their positions, and fragmenting their responsibilities – presumably to protect themselves against feared incursions from other disciplines, or perhaps in desperate attempts to appear more relevant. This results in a proliferation of increasingly niche responsibilities and skillsets, and it does not seem productive.

Fundamentally, these things are all interconnected. There is no reason to incessantly try to define and own little fiefs within the larger domain – it just reduces and limits us as UX practitioners.

Don’t get me wrong, specialization can be a good thing, but it doesn’t have to mean a conscious narrowing of scope. You can focus on something without losing sight of the broader context. Specialized expertise comes naturally with experience, and if you narrow your perspectives prematurely, you may actually end up strangling your understanding of the discipline, and reduce your grasp of the bigger picture. In essence, you’d be digging yourself a hole that might be difficult to climb out of.

UI doesn’t exist in a vacuum – in fact, it could be argued that this is the very reason for why the distinction of the term ”UX” was created in the first place, and why ”CX” even exists.

UX may not be synonymous with CX, but a UX designer will only stand to lose from being separated from the broader consumer context.

UI may not be synonymous with UX, but it is definitely part of it, and isolating it just means the discipline loses some of its cohesion.

UI may not be synonymous with graphic design, but pretending they are unrelated simply weakens the relevance of the discipline. UI used to be called GUI, the ”G” representing the graphic (abstract, visual) nature of interfaces. You really cannot divorce graphic design from UI; the former is the foundation for the latter. A UI designer really needs to understand typography, color, value, proportions, composition, texture, contrasts, etc etc. Yes, they do need to understand more than that, but those are the basics.

You don’t automatically become a good UI designer by being a good graphic designer, but if you don’t know the basics, you’ll be neither.

At this point, it seems to me, we need to be building bridges between the different disciplines, as opposed to creating islands.

Self-help is all the rage. There are books on almost every subject known to man, and the Internet is overflowing with helpful content, trying to instruct people on how to do stuff – all kinds of stuff. There are presumably knowledgeable people lecturing and speaking at conferences about how best to do things, all sorts of things, and people are gobbling it up left and right.

I love the good intent behind this type of advice, truly, and I don’t want this to sound uncharitable, but I’ve personally had a pretty important realization over the past five-six years on this topic:

It’s not for me.

Don’t get me wrong: I used to LOVE this kind of “how-to” content. I read it voraciously, and I think I believed that it would make me productive; that it would clarify things for me; that it would empower me. I read loads of interviews with other creators, and clung to their words as if they were magic formulas. I thought that by absorbing their methods, and using their tools, I could emulate their successes.

But I’ve found that it actually does the opposite. For me. By focusing so much on how other people do things, and by trying desperately to internalize that, I lost sight of how I do things myself. I’ve lost sight of the fact that I actually do know how to do stuff. I have the capacity to work through things, and figure them out for myself.

And after realizing this, I’ve become many many times more productive – so much so that it’s actually astonished me. I’ve been more productive in the past five years than I had been through the entirety of my career up to that point. It’s made me a bit regretful of the time I wasted; all the time I sat there procrastinating, thinking I needed to read up on something before I went ahead and did it.

I’ve done some soul searching to figure this out, and the answer – while not exactly revolutionary – still hit me like an epiphany. I think that I (and many others) learn principally by doing – not by reading, hearing, or observing. And while I was trying to learn how to do stuff in those other ways, I actually wasn’t learning, and it made me feel that I couldn’t do whatever it was that I was trying to do. But by not relying on those crutches, and by instead immersing myself in the work, and trying to figure things out for myself to find my own solutions, it’s really uncorked my productivity.

So, for all the people out there who are helped by this type of helpful “how to” content: more power to you. But please also consider that you may actually be able to figure things out for yourself, and this may be a way of learning that could actually feel much more empowering for you. It could rid you of crutches, of methods which may ultimately not be for you, but which will hold you back as you struggle to make sense of them.

Sometimes, the right way to do something is what works for YOU, not what works for others.

Now I guess I need to go write a self-help book on the subject. Let’s see, how do you write self-help books…?

I’d better Google that.

Dynamic Creative In User Experience Design

All design is inherently subjective.

How people perceive and are affected by design depends on who they are, what their circumstances look like and what their expectations are. Subjectivity applies not only to media and graphic design, but to art, fashion, architecture or any other form of visual expression.

We judge with our eyes.

This is especially problematic in the world of user experience, which to a large extent revolves around functionality and usability. The usefulness of browser- and app-based experiences depends on how well they enable users to accomplish what they’re trying to do. Accomplishing goals, on the other hand, also depends on how motivated users are. This adds an emotional dimension to this otherwise highly rational discipline.

Structuring a website (or an app) so that the user merely understands how to use it is simply not sufficient. If the user does not want to use a website, the empirical knowledge of how to use it is largely inconsequential. Therefore, content must be packaged in a way that the user is emotionally motivated to partake of it and here, design has an important role to play.

A survey conducted by Carleton University in Ottawa, published in the journal Behaviour and Information Technology, determined that users form their impressions of a website and its visual appeal within the first 1/20th of a second of visiting it. Even more surprisingly, these first impressions colored the entire experience of the site, whether or not the whole site actually turned out to match that initial perception. The conclusion of the survey was that this first impression was “unlikely to involve cognition” – meaning it is largely an emotional response.

However, presenting a differentiated audience with a unified, undifferentiated design – however well optimized – will not account for the variances in people’s preferences and goals. Such a design will never be entirely effective. Given that users are different and have different preferences and expectations, effective UX design has to be personalize-able. This is quickly becoming an expectation, if not the norm.

A recent study published by Salesforce found that 80% of users expect online experiences to be personalized and tailored to their needs. This means that brands simply cannot afford to broadcast the same uniform message to a single, undifferentiated audience. Marketers need to find ways of communicating to individuals, not audiences.

This posits a problem of scale.

Very few marketers or publishers of content can afford to employ armies of designers and content producers to tailor experiences to each individual user. More importantly, they cannot do so in real time.

Enter dynamic personalization.

By devising smartly constructed, modular design systems based on creative componentry that can be freely interchanged, it is possible to compose entire user experiences based on incoming media signals. These signals can reveal behavioral-, demographic- and psychographic details about each individual user, allowing the experience to programmatically flex and adjust to some of those factors.

This ensures a successful, results-oriented communicative solution that scales. In addition, it may even be able to predict favorable outcomes through the application of AI-technology such as machine learning. Done right, it will allow marketers to dial in the most effective combination of content and design with increasing accuracy.

Testing naturally becomes a central element in such solutions, where a multitude of creative options can be fed into the learning engine. The ideal mix can thus be determined, assembled and verified as users arrive on site. In iProspect’s own testing, we regularly demonstrate incremental conversion gains through dynamic, personalized experiences. However, fully capitalizing on this opportunity requires a shift in how brands look at design and how brands go to market.

The era of the static, monolithic brand is over. Modern brands need to understand their audiences, find ways of communicating on a personal level, and truly become interactive.

(Reposted)

Design, and especially identity design – but really all types of design that depend on recognizability – is not like auteurship, or artistry.

As a designer, you are not speaking in your own voice – you need to find the voice of the client, and understand how that voice resonates (or doesn’t resonate) with the intended audience.

This means that your job as a designer is more akin to that of a casting director.

You need for your design to play a role, and to express itself in certain ways that are consistent with the script – i.e., the client’s brand strategy. And if the client is unsure about that strategy – meaning, they are essentially shooting a movie without a script – you need to define the role for them, and find the right actor. Your design needs to embody the personality that you would advise the client to assume.

You need to conduct a Casting Call.

You need to define the client’s visual persona, and articulate how it should act when it’s on the stage, in order to be able to convey the right message in a credible and convincing way.

Some clients will come to you and ask for a certain actor: “We’d like for Al Pacino to play this role!”. Meaning, they come to you with an outside-in idea of someone who they think would represent them, when the actor’s job is to FORGET about who they are, not act as themselves, and instead embody the ROLE.

For that reason, you ought to take all such suggestions with a huge scoop of salt.

Treating a visual brand identity like a known commodity, like a well-known actor, means the audience are at risk of only seeing THAT actor; seeing THAT face – not experience the role that the script actually calls for.

This is the same as applying a recognizable ”style” to a brand identity. ”We want clean and modern”, say many corporations, afraid of stepping out of line with expectations and industry tropes. But their identity, as defined by the brand strategy, may not express itself best in a clean and modern ”style”, just like Al Pacino might not be the right face, or the right voice, for that role.

Think about your brand as if it’s an actor about to get on the stage, and then define the role based on how you need the audience to experience and react to your brand. Make sure your designer conducts a casting call, and casts the right actor in the role – an actor which will be able to let audiences see past their recognizable face, and experience the persona they are trying to express.

If your brand identity design does the job right, it will be able to embody the true persona of the brand, as opposed to pretending, and putting on stage clothes while still being recognizable as someone else’s borrowed personality.

Never just create a one-off asset when you can construct something reusable

Never just create a reusable single template when you can design something modular

Never just design modular components when you can devise a framework

Never just devise a framework when you can architect a design system

Never just architect a design system when you can define a user experience

Never just define a user experience when you can plan out a user journey

Never just plan out a single user journey when you can improve lifetime value

(Reposted from 2020)

Over the past decade, we have seen the rise of Fake News, and the dangers of social media allowing us to stay in our closed opinion bubbles, finding support for almost any misguided opinion there is.

Artificial Intelligence will only aggravate that problem.

A.I. supplies the psychological confirmation mechanisms that convince the ignorant that they are right: they can continuously iterate and demand changes until they are satisfied.

In my experience, the only thing that (misguidedly) satisfies an ignorant client is to get exactly that which they want to see through unlimited iterations.

What ”proves” to them that the result is ”good” (which they themselves by definition lack the objective capability to determine) is that they persuade themselves through requesting changes, and that the progressive results of those changes in and of themselves supposedly mean that they have ”refined” the results. When, in reality, all they have really done is go through a long series of bizarre, totally subjective mutations which at no point were guided by deliberate, knowledge-based or empirical judgments.

That is, in my mind, the real problem with A.I.: it enables limitless, automated and arbitrary mutations, without any of us ever really understanding the purposefulness or adequacy of the decisions made along the way. We simply outsource important decisions to the A.I., without understanding or even being aware of those decisions, relying entirely on the machine to make the right decisions – even though the machine has no awareness of “right” or “wrong”.

This is certifiably insane.

We ought to be deeply troubled by the fact that we have no way of ascertaining the factual accuracy of the decisions made by the A.I. or, more importantly, the MORAL consequences of the decisions it makes.

We dismiss the dangers of A.I. at our peril. We may think that the current outputs produced by A.I.s are unsatisfactory, and that A.I. poses no threat for that reason. But those are mere details that A.I. will get progressively better at resolving. That is, after all, precisely what A.I. does: it learns, iterates and improves its output, and that is happening at an ever accelerating pace. If we believe that we can judge A.I. by the quality of what is produced TODAY, then we are missing the very essence of the problem.

Specific results are difficult for A.I. to procure TODAY, simply because they are still new to the A.I., and the machine lacks sufficient data upon which to base its results. This is a challenge that will disappear on its own through the very way that A.I. is constructed: to gather more data, and refine its output indefinitely.

The current problem with A.I. is this: the advocates for Artificial Intelligence are experts on the technology, not subject matter experts in the fields in which A.I. is being disruptively accelerated and implemented. The ACTUAL subject matter experts have no means through which to validate the veracity of A.I. output, and the technical experts don’t appear to care about the morality of it.

The long-term problem with A.I. is an ascerbation of that very problem: the more advanced A.I.s get, the harder it will be for its human counterparts to validate or justify its results, or even understand how it arrived at those results.

The way I see it, the key issue is that A.I. is a “black box”: it produces results without us knowing how it arrived at those results, and we therefore lack the ability to validate or dispute them. And this is an escalating problem, which worsens the more complex A.I. gets: the black box gets blacker and blacker. We will eventually require “Voight-Kampff-detectors” in the hands of A.I.-psychologists, who will try to analyze the A.I., and understand its decisions.

Talk about chasing your own tail.

If we outsource decisionmaking – in any form – to the A.I. machine, we are in deep trouble. Because A.I.s CAN and DO make mistakes: its decisions are only as good as the data fed to it.

Ultimately, decisions are validated not on the grounds of veracity, but on the grounds of morality – morality that A.I.s don’t have. There may be thousands of data points that support a certain decision, but the decision may still be an immoral one.

Decisions without morality?

That is Skynet right there. Or, if you wish to be more sophisticated: Asimov’s 3 laws of robotics – laws that are yet to be enacted.