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Generative Design

Adidas Strung; taking shoe design to a new level

Incredible exciting project by Adidas. A shoe created by a robot sewing machine, based on data of the runner. Using less material and reducing the weight. Great example of technology and design.

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Categories
Design Strategy System Design

What’s happening in 2020 for tech, and design

Benedict Evans presented his view on tech in 2020. I’m a big fan of Evans work sharing data on what’s actually happening. If you don’t follow him on Twitter, please do.

In his presentation he shares his views on what he think the next cycle will be about in tech. While we all are talking about a new technology layer, like AR or voice, the next cycle might be more of a framework for a matured industry.

The Next Cycle by Benedict Evans

Software is eating the world. We have arrived at a time where all companies have become tech companies. Do you see a company as a taxi company, a workspace rental company, a mattress company or as a tech company? And does it matter?

Beyond disruption

Tech is moving into the fabrics of daily live and with this the impact and responsibilities are growing. Keep in mind that in the West only 15% of retail is digitised.

Moving to a more systematic model is great for design, we have seen fields like Service Design, Design Strategy, Design Thinking growing up over the years to facilitate the need for systematic thinking and design.

When we create something, we have to think about 2nd and 3rd order effects of the things we do and design for it. Technology is moving from the edges to the center. With this complexity and responsiblity scales.

The technology and design that get or got your company started will not make sure it stays around.

Categories
Generative Design

The computer as design partner

I love it how the computer is moving from a tool to alter something into a tool that is more a co-creator together with the designer.

Studio Unicode created a beetle generator that learned from thousands of beetle pictures.

Categories
System Design

Gender bias

The thing with algorithms is that they expose whatever bias is in the data. We might hide it or not like it. The algorithm does not care and exposes it.

The Apple Card Didn’t ‘See’ Gender, and That’s the Problem

Wired.com

The results is something that has logic and value at the surface, but once you make a deep dive or start to roll it out, it’s fundamentally broken. You could even call it badly designed.

As we start to roll out more of this partly designed, partly self designed systems to larger problems and bigger audiences.

The amount of second or third order effects can not be seen in advance. Creating a fertile ground for Black Swans.

The black swan theory or theory of black swan events is a metaphor that describes an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of hindsight. The term is based on an ancient saying that presumed black swans did not exist – a saying that became reinterpreted to teach a different lesson after black swans were discovered in the wild.

https://en.wikipedia.org/wiki/Black_swan_theory
Categories
Generative Design

The face machine

100.000 photos of faces generated by an algorithm. It’s the huge number that catches your attention. It could easily have been 1 face or 1 bilion faces. The computer doesn’t really care and it doesn’t change a thing.

Again there is something that we think is highly unique that is getting ‘computerised’, making it easy to generate, duplicate or modify.

You don’t know all people. In the end a real face or not does not really matter, right? These faces are generated by a piece of software, and more interestingly, software can be controlled.

https://generated.photos

Why care about faces

We are hard wired to look for faces, it’s the first thing we notice on a website or in a magazine, it’s what we look for when outside. We not only look for faces in people, we even see faces in objects all the time.

A face says; he, here is another human. And that’s good if you’re in a forest with wild animals living in the Palaeolithic era. Other people makes us feel. safe and if these people look like us it’s even better, they are part of our tribe.

From now on the faces you see can be generated by a piece of software. And given the fact that we are biased by pictures it makes us susceptible to more nuanced nudging.

What if all the models in a clothing shop look like you? Uncanny or will you be more likely to buy something? What if people in ads are tailored to your profile?

I’m still not really sure what to think of this, technically it’s really interesting. Is it science fiction or just another step into the filter bubble.

Categories
Generative Design

Machines think different

I have written about generative systems on this blog a couple of times. I think generative systems are the most fascinating thing that is happening right now from the view of the computer as a tool.

I believe they are crucial to designers or other people who like to solve problems. It will change how we think, work and make.

Creativity or creation is often about ideas, iterating, try-outs, feedback, bounce ideas, see what sticks or clicks and continue from there. It’s why we organise brainstorms, design critiques and creative sessions.

It’s why a multi disciplinaire team works and why diversity creates better products. Different views, different angles make ideas stronger. The lone inventor is romantic, but it might as well be a myth.

Generative systems are like adding this person with a completely different background to your team.

A computer is something we know as being very logical, the more examples we see how machine learning comes up with alternative solutions for existing problems, the less logical this computer seems to be.

It’s like these systems operate in a parallel universe without any of the knowledge we have. They don’t respect our rules, or don’t really care about them.

Reasoning without prior knowledge of the problem domain, but a deep understanding of the problem.

To illustrate this two examples from the past days.

This is work on “generative” drug design, which as the name implies, is trying to generate new structures rather than evaluate existing ones.

https://blogs.sciencemag.org/pipeline/archives/2019/09/04/has-ai-discovered-a-drug-now-guess

The first one is a proposal for a cable holder, the other one a proposal for a new drug.

Different fields, similar results.

Computers think different and by doing so they broaden how we see the world.

What makes it most awkward is that confronts us with the often self-imposed limits in our thinking and creativity.

Who’s the one being open minded?

Categories
Generative Design

Wilbert on Design, April

I strongly believe that the biggest challenges and opportunities for designers are going to be on a system level.

  1. Systems grow in complexity; every touch point is connected all the time
  2. Behaviour personalisation increases; what you see is not what I see or what we see
  3. This results in less control; it’s hard to design a blue print for something with a lot of dynamic parts, so design (as a field) also has to move the boundaries of design, where you aim for guidelines, intended behaviour, principles.

In this edition some examples of why we?—?as a design field?—?need to think bigger.

Protecting vision

Self driving and stickers

Making a self-driving Tesla move into the opposite lane…with just stickers pasted on the road!?

A car controlled by a computer it’s still limited by the sensors and rules and data we’ve put in.

People have always been great manipulators of systems. This video shows how easy it is to manipulate a system when you start talking to a system in its language.

We relying more on camera’s for a lot of services, this is a new domain for design, right now mostly driven by technological capabilities.

What’s real

A lot of platforms are having issues with filtering content. Because of the network effects and gaming a system a lot of ? gets the attention it doesn’t deserve. This as much a technical problem as it is a design problem. I don’t think there will be a simple algorithm to fix this, it’s more a systemic problem.

If you don’t design for it it from the beginning you will never be in control.

While most discussions are about Facebook I personally think YouTube has issues of a similar size. It’s the magic place where you can find someone explaining how to replace that tiny spare part in your car, but it’s also full of nonsense, spreading faster then a computer can stop it.

One AI?—?YouTube’s recommendation algorithm?—?determines >25% of ALL internet traffic on mobile by picking what videos we watch… and steering the daily thoughts, feelings and beliefs of two billion people.…?

YouTube screenshot

“I’m so glad we let tech platforms eat the journalism industry. Now, I can sit and watch a live stream of Notre Dame burning while YouTube’s fake news widget tells me about 9/11 for some reason.…?

My reality is not yours

Snap showed some nice demo’s of what it can do with augmented reality. AR personalises reality. Again, we can look at the same object and my experience can be totally different from yours, just like a news feed.

What if AR meets all the problems Facebook and Youtube have? Would you let your kids use it?

Snap summit picture

hello @snap?

Snap New York building

“LSD had a great run tbh.… “?

Generative tools

Design tools will enable more people to become a designer or take part in the act of design. It’s similar to what mobile camera’s and Instagram did to photography.

It could cause a wave of creativity when the same would happen to visual content creation (I’m not sure how to call this).

A peak into how men and machine will work together to make things.

Ai Art

Artificial intelligence: art’s weird and wonderful new medium?

Ai drawing tool

Stroke of Genius: GauGAN Turns Doodles into Stunning, Photorealistic Landscapes?

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