“10 principles for design in the age of AI” and other edicts

Not a fan of Yves Béhar or self-promotion packaged as a high-falutin’ design manifesto, and feeling generally ornery, so just one-sentence reactions:

1. Design solves an important human problem

There are millions of design challenges, not every design does or needs to solve an “important human problem”.

2. Design is context specific (it doesn’t follow historical cliches)

Yes, design is contextual, but some contexts benefit from historical references and familiarity for fast and wide adoption, e.g. iPhone intro.

3. Design enhances human ability (without replacing the human)

Some design problems are better solved by getting the human out of the equation; we’re not work animals.

4. Good design works for everyone, everyday

There’s pretty much nothing that “works for everyone, everyday“.

5. Good tech and design is discreet

Being discreet and solving a design problem can be orthogonal.

6. Good design is a platform that grows with needs and opportunities

Not all design needs to be a platform and not all growth is beneficial in the long run.

7. Good design brings about products and services that build long-term relationships (but don’t create emotional dependency)

The driver of manufactured “emotional dependency” isn’t always design; it’s often a business model that requires it, e.g. Facebook, Zynga, Candy Crush, etc.

8. Good technology design learns and predicts human behavior

Algorithms are by definition exclusionary and mostly normative: “learning” and “prediction” aren’t without a price, e.g. aggressive surveillance by Facebook, Amazon, Google, etc.

9. Good design accelerates new ideas

Not all design requires elaborate contemplation, especially for commodity products.

10. Good design removes complexity from life

Complexity is in the eye of the designer and removal is normative, e.g. Trumpworld.

Incidentally, much of this has nothing to do with “AI” brutally slapped onto the title.

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29 shades of insult to injury

For advertising agencies two critical moments are when the team pitches to get a new account and when it finally presents its creative solution after weeks of work to start production. How many “options” should be shown to the client at this juncture is a matter of creative-process folklore.

There’s always the good old triple: “good, better, best” a.k.a. “throw-away, can-live-with, must-sell”. Some would go further than three. It’s not uncommon for boutiques to bet on just one solution and try to convince the client. Whether it’s one, three or six, I bet no one has ever heard of 29 options. Unless you work at Yahoo.

A new CEO looking for a quick turnaround getting company logo redesigned? American as apple pie. Some succeed, some fail and most never get more than a week’s worth of traction. Not a big deal, if you just have a press conference, a happy photo-op and your designer gushing over the “how we did it” part in some design pub. (Especially double-delicious if it’s the CEO who’s doing the write-up!) These are as harmless as they are unavoidable.

But 29 days of unrelenting assault on the design sensibilities of the few who cared? Unfruitful. Yahoo’s intention wasn’t crowd-voting or crowd-sourcing its next logotype after 18 years. The crowd couldn’t do anything about the options. So it was a one-way presentation of five horrid letters plus a punctuation mark day after day for a month. And at no point the crowd could cry uncle.


What then is Yahoo telling us?

We don’t care: We think logotype design is a frivolous activity. Since the goal of what it needs to be isn’t quite clear to us, we can post 29 superfluous variations in as many days. Hey, if you challenge us, we could algorithmically generate 365 options in one hour, one day, one year or until you surrender.

We know we should care: We care about logotype design, it represents our brand. We want people to know that we’re changing Yahoo, the company. The crowd can’t yet see the change fully but they can see the logotype change before their eyes. Since the logotype represents our brand which represents our company…well, you get our drift.

More is less: Look, we already had the logotype design we wanted weeks ago. We had interns come up with a few dozen variations and we let you see just 29 of them. You have no idea what the rest looked like. You’re welcome.

We’re not pros at this: We can’t shout from the rooftops. We don’t have ad budgets the size of Samsung’s or even Microsoft’s. Fine, we probably have more web traffic than both combined to expose people to anything we wanted, but we didn’t bother figuring out how we could use that traffic to have them look at what actually matters: who we are and what we want to accomplish as a company. (OK, that would have been dicey because, frankly, we still haven’t figured that out yet.)

See if we care: Yes, we know we could have done things differently. For example, we could have:

  • respected the design community and the digerati by serving them something serious for a month so that they could become catalysts to positive conversations about our company on a daily basis. (We may still have to recruit a few of those creative types, after all.)
  • tastily presented daily videos and sketches of 29 different designers discussing our logo, brand and company.
  • hosted these logotype options at one specific Yahoo property per day (we have dozens of properties) to draw much needed attention to them.
  • set up a million-dollar (non-binding) logotype contest (with a nominal $29 entry fee to keep out the riffraff) to attract serious designers and design firms. Cheap.
  • video streamed the final selection process, with a few mega-celebs thrown in to attract a crowd and even serve a few ads (or promos for our properties) in the process to boot.
  • had the sensibility to not come up with an anemic rehashing of the old logotype, sans serifs but now with bevels (bevels!) like it was the go-go ’90s.


It’s a logotype for crying out loud: Yes, we could have done a lot of different things besides throwing 29 disparate high school lettering projects on the internets for a month to see if anyone cared. But that would have required adult supervision for design and, honestly, we don’t care that much.

Now you know.


1. I’d love to see Yahoo succeed, I’ve been using many of their services for years.

2. You might also be interested in “Ordered Information” is not a paint job where we consider the sorry spectacle of Yahoo Finance design.

A Memory Hole

I am a phlegmatic man. But once, just once, I want to wake up and invent a new design philosophy, and acronymize it so sublimely even a sixth-grader can instantly grasp its exultation of the human spirit:


I want to shout down from the rooftops — especially from the rooftop of what was once the largest computer vendor in the world — making sure every soul hears it, even the Proles:


I want to get on every telescreen to explain The Theory and Practice of MUSE Design Philosophy:


I want to show everyone how hard our team worked:


Then, right after a Two Minutes Hate, I want to take the stage, hold the fruits of our labor in my hand and let everyone soak in its glory:


Yes, there will be doubters. And there will be haters. But we will deal with them…in Room 101:


In the fullness of time, there will be learning, there will be understanding, and there will be acceptance. One unperson after another.

One bright cold day in September when the clocks strike thirteen, I will come back and reassure everyone that we do what we do for the greater good.


Editor interview: Designing “Data Flow”


Yesterday in Book review: World’s best info-design in “Data Flow” we explored an exciting new book on data visualization. Today we ask Gestalten Publisher and Editor in Chief Robert Klanten to comment on the current state of info-design and the genesis of Data Flow: Visualising Information in Graphic Design:


• Where did the idea of creating Data Flow come from? Any influences?

Information graphics are an interesting topic we have always been following. It has always been very much tied with websites, interactive and screen design, and now we felt there was enough new material to show how much it has matured in the last couple of years.

• Most people get exposed to info-vis in a limited fashion via their daily newspaper, newsweeklies, TV and other popular media. Specialized magazines, trade books, marketing collaterals, text books, etc. where more evolved forms of info-vis might be found are not mass marketed. Have you noticed if info-vis is making more inroads into the popular culture?

First there is a growing demand for information graphics but beyond demand I feel that the aesthetics are somehow en – vogue. I think that everybody is aware of how interconnected our lives have become through media and how the sheer amount of information, references and interests have exploded.

Maybe the deeper logic is that modern people feel more comfortable seeing themselves as a part of a huge network, much rather than being a slice of a pie chart. Everyone has to find new ways of defining and locating oneself – graphic design is somehow providing this trend with adequate visuals.

• There is a vast divide between template-based info-design coupled to digital data sources that generate our daily intake of info-vis and one-off creations that require long and painstaking work by dedicated info-designers some of whose work can be seen in Data Flow. Our digital tools are not yet capable of facilitating real-time, or even reasonably rapid, creation of rich and elegant visualization. Do you foresee a day when this gap might be narrowed?

This day is much closer than we all think. There is a huge demand for visualisation in technology, medicine, science, meteorology, etc and these solutions will make it in museums, onto fairs as well as other commercial applications. Computers are fast enough to handle the huge amount of data that is needed without causing delays handling the data. This is the key.

• In collecting your samples, have you noticed any differences among American, European and Asian approaches to info-design?

There are certain “folkloristic” preferences and traditions that always exists and become visible here and there. Britons are very image driven while continental Europeans are usually working with a reduced and clear structure and favour vector graphics. Americans expect “how to” instructions to come along with the information while Asians are keen to find out on their own.

But it can generally be said that the guys who have devoted themselves to this subject are very diligently trying to avoid local habits and try to react upon the expectations and the intelligence of the viewer much rather than trying to do something which is self-servingly stylish or traditional.

• I assume that some samples were eliminated from the book as they couldn’t fulfill the “Visual metaphors are a powerful aid to human thinking” criteria. With some samples, did you have any difficulty in drawing a distinction between the purely decorative but perhaps inspirational and informative but perhaps purely instructional?

I think we tried to cover the subject in its entirety from instruction to inspiration. There are examples in the book that might use the aesthetics of information graphics without being “informative” in a classical sense. There are other examples that are trying their best to create / discuss new possibilities of visual display. It is quite subjective to determine where one thing begins and the next thing starts and in some cases we have decided to leave this decision to the reader.

We are not delivering a final verdict but try to see this book as a launch pad that provides the reader with enough knowledge and theory and open questions.

• Were there perhaps more patterns beyond the six that you focused on (datasphere, datanets, datascape, datalogy, datanoid, datablocks) that you may have found too restrictive, specialized or amorphous?

Yes, absolutely. Just like information graphics, we had to build an editorial container and include as much information (chapters, types of applications) to create consistent and instructive examples and exclude more freakish approaches for the sake of remaining legible.

Book review: World’s best info-design in “Data Flow”


“Visual metaphors are a powerful aid to human thinking.”

That is the very first sentence of the foreword to a gorgeous new book on information visualization Data Flow: Visualising Information in Graphic Design. In just nine words it captures both the boundless possibilities in making data comprehensible to humans as well as the inability of info-designers to dictate the outcome, as the meaning is always in the eye of the beholder. Info-designer’s principal job is to contextualize data by creating metaphors and hope to ignite thinking. Info-vis is thus condemned to forever straddle the divide between inspiration and instruction.

The book which publisher Gestalten kindly sent us for review is anchored by (IDEO partner) Ferdi van Heerden’s foreword followed by designer interviews, short editorials and contextualizations adjacent to the best collection of contemporary info-vis samples currently available in a book format.

Data Flow surveys a huge swath of the landscape of data metaphor and identifies six gateways which organize the book’s chapters:

  • Datasphere – circle as the perfect but elusive shape
  • Datanets – networks of cause, context and relationships
  • Datascape – spatial flow, context and order of data
  • Datalogy – physical expression of the metaphor for our senses
  • Datanoid – reflections of ourselves for emotional relevance
  • Datablocks – data structured and simplified for comparability

Searching for a “data language” is a common thread throughout the book:

If we can show data as blocks, spheres, rivers, nets, or landscapes, we open up a new and rich visual language through which the external world is brought into our internal world of understanding. In other words, we communicate.


DataFlow also underlines the tension between using accessible info-design vocabulary and complexity:

Design is not just about making things simple. In fact, there is a complementary relationship between simplicity and complexity that influences design choices to produce surprising and informative data diagrams. By shaping their view on data, designers can choose to introduce a level of complexity that allows just the right amount of contrast to drive profile, focus and definition. The choices determining this delicate balance — called simplexity — are highly dependent on the context and audience for the resulting data presentation.

The ever-present danger of that tension is the overtaking of comprehension by composition:

A professional, visually literate audience will relish a higher sophistication and subtlety that can be delivered with sublime elegance. However, access to ever larger databases can seduce the designer into placing complexity, and the challenge of bridging the gap between information and its expression, at the very forefront. Software tools such as Processing [website] have made it possible to give shape and meaning to massive amounts of information, yet in many cases the tool becomes the message.

Among the 250 pages of meticulously reproduced samples, it’s also easy to see that sometimes the scales tilt away from comprehension/instruction towards composition/inspiration, and even towards decoration.


Occasionally, it’s hard to gauge the full-impact of large pieces, both in size and detail, because they are scaled down by the constraints of a printed book page — one longs for a zoom-in button. An interactive format would have obviously allowed a more layered engagement, tying selected samples back to such info-design sources as Tubular Graphics (Tokyo) and Stamen Design (San Francisco). And yet there’s something immensely satisfying about having a single, portable source that captures what’s current and curious about data representation in one place.

DataFlow is that rare collection that elevates the discussion on info-design from wow! to introspection.


Read our interview with Gestalten Publisher and Editor in Chief Robert Klanten on the current state of info-design and the genesis of Data Flow.