AI, Machine Learning and Computational Design: How the products you design today are shaping your future

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Now more than ever, you have the opportunity to actively design and manifest the world you want to live in.

I sat in on a webinar on computational design with the absolutely brilliant John Maeda and Leah Buley today. This post is my stream of consciousness response.

John brought up the fact that AI is an incredible thing, with endless possibilities, and talked a bit about how we need to shift our current approach to educating the designers of the future.

It got me thinking about traditional design education. John joked about needing to start with a clean slate.

In the past, design education taught a foundation in design principles that are still important today. Then you were taught how to use tools. Then you combined the principles and the tools and you were able to make a living being a designer by kicking out physical deliverables.

The breakneck speed at which tools and technology are changing has caused a huge rift between education and becoming a design practitioner. Focusing half an education on tools isn’t helpful. The tools you’re taught to use in your first year will be completely out of date (and may not even still exist) by your 4th year. Education needs to focus on teaching designers to think. The problems they’ll be designing solutions for when they graduate likely don’t even exist yet.

John mentioned a brain teaser during the session. It goes something like this: A lily pad doubles every day. In 28 days the pond will be completely covered. How many days will it take for the pond to be half covered? People often answer the 14th day, but in reality, it’s the 27th.

He likened AI and machine learning to to those lily pads. We’re building up speed, creating all of these tools and optimizations and process improvements at an incredible rate. He likened computational design to “The Upside Down” circa Stranger Things. This network of machine learning data is lurking just under the surface, growing in data points every second of every day. There are some amazing things coming out of it, like helping people design solutions that contribute social good. There are also some not so amazing things coming out of it. Regardless of the intent of the people focused on enhancing machine learning, all of the puzzle pieces are falling into place. Right now, we’re so optimized that a small break in a workflow, a tiny miss, can take down entire systems. And this trend of machine learning and AI optimization is only going to continue.

There is going to come a day when we jump practically overnight from a set of rapid enhancements to a fully technology driven, completely digital, AI and machine run society in first world countries and beyond. The half lily covered pond will explode overnight.

Machines are already “creating art”. We have AI creating realistic photos of imaginary people. I’ve purchased products from Facebook ads more often than I’d like to admit. The algorithms are increasingly intelligent. We joke and write fiction about a future overrun by robots and artificial intelligence. But to John’s point, the leap has begun as a steady incline, with an immanent rocket explosion to follow.

As designers, our role has already evolved from being individuals who learn how to use a tool and create a deliverable, to being tasked with a problem at needs to be solved, and digging deeply to uncover the underlying issues that are creating the problem. I work at InVision, and when I started here we just had a prototyping tool. It was a brand new, cutting edge concept and exceptionally powerful. It cut out the hand coding that was previously required to bring a product to life for testing. Over the 3.5 years I’ve been with the company, we’ve grown from just being a prototyping tool, to a company that has built an entire suite of tools for team centered product design based on cross company collaboration.

Design thinking has been widely adopted across industries because identifying problems and designing solutions that benefit companies across teams is a key to market success. The screen is the most important place in the world, as Clark Valberg points out, whether it be a computer screen, a phone screen, a watch screen, or an eye implant that analyzes everything around you in real time, turning your whole world into an interface screen. Being a designer is no longer about just making graphics for those screens. It’s about building products that move past what is needed today, to what we need for tomorrow.

It’s looking holistically at product design from a company perspective, rather than a screen by screen perspective. I feel incredibly fortunate to work for a company with senior leadership that plans for the “next next” instead of what we need to get by today.

So how can designers ensure that the work we do today will make a better tomorrow? We’re designing our future every second of every day. We need to be mindful about what we put out in the world, because machines are learning from everything we post. Every comment that’s made. Every photo posted. Product decisions you make now hold more long range power than ever before. It’s an incredibly exciting time to be part of the design industry. The future is a crazy terrifying beautiful place, and the impact designers have now is multiplying exponentially behind the scenes.

So, my point? Be mindful about what you put out into the universe, now more than ever. Make your products accessible and inclusive. Ensure that the imagery and videos and language you use in your products represents a diverse population. The things we make a priority now, are the things machine learning will use to shape the future later.

Giant thanks again to John Maeda and Leah Buley for a session that blew my mind and inspired this post. It’s amazing how 45 minutes observing 2 genius’s interacting can impact your ideas around how to help make sure the future is what we hope for, not something to fear.

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