What’s happening in 2020 for tech, and design

Slide Ben Evans

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.

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

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.

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?