Web Directions Design 2018 was held April 12 & 13 at Arts Centre Melbourne.

Old school jump menu

Day One

Day Two

  • design with intent – directing design effort to protect the vulnerable, improve lives and make the world a better place. Or at the very least understanding the ways technology has been failing to do so.
  • Evidence – collect evidence, test hunches, don’t validate your idea – question it!
  • On the tech side, SMS continued to feature as we could text questions, emoji reactions and coffee orders. A good demonstration of being open to using all suitable tech, not just the New and Shiny.

Disclaimer & Image Credits

  • These notes were hammered out very quickly and paraphrase what speakers were saying. If you need an exact quote, use a definitive source such as a recording or slide deck.
  • Photo credits as per the social media embeds, plus some taken from speaker slide decks.

Day One

Sara Wachter Boettcher – Designing Inclusive Products

A piece of design that has people concerned in America – the census will be asking people about their citizenship. This is a very touchy subject in context! The Centre for Survey Management pre-tested the wording and found some Spanish-speaking people were afraid to provide information about people who lived in the same house.

The problem for the census is that if people don’t provide real information, decisions that rely on it become skewed. That includes things like where public infrastructure is built, even the way electoral boundaries are drawn and how many members of Congress are allocated to the state.

Census data is supposed to be private and confidential, but the US may decide it is “under threat” – at which point the government can de-anonymise the data. Which is how 1940 census data was used to identify and inter japanese citizens during World War II.

Every design decision has consequences.

This can be simple. Google Maps added a feature that told you how many calories you might burn if you walked somewhere; and they included how many mini cupcakes that would burn. That raised a lot of questions, from the practical (which cupcakes? what’s a mini cupcake anyway?) to the much deeper ones… like do they realise how much shame this can trigger for someone who has had eating issues?

The issues included:

  • no way to turn it off
  • dangerous for people with eating disorders
  • 'feels shamey’
  • “average” calories counts are wildly inaccurate
  • cupcake is not a useful metric
  • (see slide for the rest, good list)

Because someone spent time tweeting the issues with the feature… and it was pulled after just three hours. Google probably spent more than three hours just designing the cupcake image.

As an industry, we have normalised a chronic under investment in inclusion and harm prevention.

Amnesty International (march 18) declared that Twitter is failing in its responsibilities to protect human rights, to protect women’s rights. Jack Dorsey responded that they were “not proud” that they have been failing on this. But Twitter has been admitting they “sucked at” stopping trolling and abuse for many years.

If you really want to change something, you change it.

James Bridle published an article with examples of nasty content being targeted at children – knockoff Peppa Pig videos on youtube, tagged with “keyword salad” so they come up for children. The videos are autoplayed based on other content and suddenly the kids are seeing psychologically disturbing content. But its designed so that the parent may not realise it while their child watches the videos.

Much of the discussion leads to issues like this, but it’s not just content moderation it’s also an issue of product design.

Consider that Twitter was built for four young guys in silicon valley, who could safely share a lot of information about themselves without experiencing negative results. As their user base grew they quickly heard from users that they were experiencing abuse on the platform, but they were very slow to respond.

The search for hockey stick growth tends to be at the expense of ethical concerns. Mark Zuckerberg has been facing a congressional hearing in the past few days, due to Facebook’s failure to protect user data in the Cambridge Analytica scandal. The apologies that Zuckerberg has published read amazingly similarly to those published by Twitter – they didn’t do enough, they were too optimistic, too focused on the good.

But Facebook used to pride itself on moving fast – Move Fast And Break Things. They prized progress and speed over slowing down. But if you don’t slow down and think, you don’t even know what you’re breaking.

Tay.ai profile picture

Do people remember Tay.ai ? Microsoft’s attempt to create an AI that talked to teens and talked like teens, but trolls immediately trained the AI with extreme keywords. They tweeted so much abuse to the AI that it literally started tweeting aggressively anti-Semitic content within 24 hours.

Withings had some notifications and encouragements about losing weight built into their system, but it didn’t handle the scenario where someone was tracking their toddler’s health stats. Toddlers gain weight because they are growing! It also congratulated a new mother for “hitting a new low weight” just after giving birth.

The year Eric Meyer lost his daughter, he received a Facebook “year in review” notification with her photo. The photo he had posted after she died was algorithmically chosen as the “most popular” photo and surrounded with people dancing, balloons and streamers.

(For more on this story, see Inadvertent Algorithmic Cruelty and Eric & Sara’s book Design for Real Life)

Facebook has apologised for the mistake, but has it really fixed things yet? They used a screenshot of a death threat to advertise Instagram (“your friends are using Instagram” with an example post).

Tumblr sent someone a push notification “Beep beep! #neo-nazis is here”, supposedly because they had read articles about the topic during some research. When queried about it, Tumblr admitted that they were worried about potential problems with the feature, but launched it “because it performs really well”.

Inclusion may be inconvenient to your business model.

We are creating things in the context of biased norms.

FaceApp was a selfie-modifier, which created alternative versions of your photo – older, younger and “hotter”. But they’d seeded the underlying neural network for “hotter” mostly with images of white people. So a side effect of the app was people of colour found that to be “hot” meant to be lighter-skinned.

Google Photos had a huge blow up when it accidentally categorised PoC as 'gorillas’, which is a very deeply insulting term. As part of their apology they talked about making the algorithms much better at recognising images of PoC. The problem with that is that it’s a sort of tacit admission they were happy to launch a product which worked much better for white people than anyone else.

Are we ok with this? Are we ok with products that are only tested for white people? This kind of bias is baked into all kinds of products.

AI and Natural Language Processing is easily skewed by its seed data, but in many cases people will be working on data sets they didn’t create themselves. This is how you end up with image processing associating kitchen implements with women.

Silicon Valley is full of people who are great at tech but out of their depth with the social impact. The infamous “Google Memo” actively promoted “de-emphasising empathy”, claiming being emotionally unengaged helped people make better decisions.

Whose job is it to define “good”? Whose job is it to understand historical context, to anticipate unintended consequences? Should there be a specialised team?

We need to uncover assumptions about normality in our work. Our assumptions say a lot about us, but very little about other people in the world.

The old dad joke applies: when you make an assumption, you make an ass out of u and me.

Facebook had deeply assumed people had a good year, with good and positive experiences they wanted to be reminded of at the end of the year. They did not anticipate people having bereavements, or their apartment burning down.

We need to ask questions like “where did the data come from” and what biases it may contain. Ask who decides what “good” looks like and who things work for.

We need to agree on ethical values in our work.

We need to design to include. Our work has power – this is not a new realisation, but we need to think about how that power is used.

Do we want to keep chasing hockey stick growth and unicorn valuations? Or do we want to make the world a better place?

@sara_ann_marie | rareunion.com | sarawb.com

Stephanie Troeth – Influencing Decisions with Design Research

Research is really about building evidence, particularly about the why.

For a long time research was heavily tied to speed, performance, efficiency… sometimes literally about the efficiency of CPU cycles. “Hello Bitcoin!”

Research needs to include failure stories.

Facebook and Twitter were happening by 2006; the first iphone came out in 2008; and Ethan Marcotte’s post about responsive design was 2010.

Ten years pass quickly.

In 2008 Steph was working on The Book Oven, trying to solve the problems authors faced getting books written and proofread. She added a feature called Bite Sized Edits which let people proofread single sentences in minimal context. People in traditional publishing didn’t understand it at all, but people in tech loved it.

Their main competitors were not competing authoring products, they were actually Google Docs and MS Word.

Catch 22: if you are making something that doesn’t exist yet, how would people know they want it?

But Steph realised this wasn’t the right question to ask, there was an assumption they were really doing something that was new. They were a solution looking for a problem.

Here’s an existential question: Is it bad Design if nobody wants to use it?

In most organisations, there’s not a high level of design and research maturity. How do you put a price on something? If you get it wrong, you lock things away behind a price people aren’t willing to pay.

To have strategic impact, you must understand and use the language of business.

When you talk about value you will quickly get to trust. Customers need to feel they can trust a company or product.

The problem is that when researchers get involved, big decisions have usually been made. Or perhaps there are competing ideas and the winner now has pressure to deliver very quickly. There’s a deep seated desire for genius. Someone to be one, an organisation to act with genius.

No upfront research = high risk.

By the time someone’s convinced that an idea should be built, there is a habit of using research to validate an idea and not question it.

Do you talk to people who don’t want to use your product, as well as people who already do, or want to?

We have given ourselves permission to launch things with very little evidence they are likely to work. Building the wrong thing is incredibly wasteful.

For years we had terrible processes, design problems would be magnified through waterfall projects. We moved to agile processes hoping to course-correct much sooner.

But now people are trying to make revenue from early iterations. To make money before the idea is even finished. Making something as good as it could possibly be is no longer seen as important.

Perhaps the problem is the internal wish for genius. Ultimately everyone secretly wants to be Steve Jobs.

How did we get here?

Clip from Rosencrantz and Guildenstern Are Dead, just before being hanged:

There must have been a moment, at the beginning, when we could have said no. But somehow we missed it.
Well we’ll know better next time.

(Excerpt from an interview with Ezra Klein and Jaron Lanier)

Lanier points out that we made a choice to do everything free but within the context of capitalism. Going right back to the 80s and the free software movement, there was a lot of idealism and no room for dissention. People simultaneously wanted things to be free but idealised tech entrepeneurs like Steve Jobs and Bill Gates. So because people wanted everything to be free, but still make money, the only business model left was advertising. But then at scale advertising becomes behavioural control.

(Tristan Harris quote)

Talking about monetising user attention and Apple execs feel they would never be in Mark Zuckerberg’s shoes.

(Excerpt from an interview with Ezra Klein and Mark Zuckerberg)

Zuckerberg: You know, I find that argument, that if you’re not paying that somehow we can’t care about you, to be extremely glib and not at all aligned with the truth. The reality here is that if you want to build a service that helps connect everyone in the world, then there are a lot of people who can’t afford to pay. ... But if you want to build a service which is not just serving rich people, then you need to have something that people can afford. I thought Jeff Bezos had an excellent saying on this in one of his Kindle launches a number of years back. He said, “There are companies that work hard to charge you more, and there are companies that work hard to charge you less.” And at Facebook, we are squarely in the camp of the companies that work hard to charge you less and provide a free service that everyone can use.

Now we’re going all the way back to the Edwardian period. The early days of electricity, when wires weren’t even covered yet and one touch would kill you. People hadn’t worked out how to make

Excerpt: “Hidden Killers in Edwardian Home” Dr Suzannah Lipscomb – people were running multiple devices off single electric circuits, which would overload them and cause fires.

How do we kill the genius? How do we get away from launching things that don’t work and haven’t been tested? Build evidence. Get research involved earlier in the process.

slide: the classic double diamond of design

We tend to start in the second half of the second diamond, assuming we got the first three right. Agile goes directly to building things, build and test early. But once you build something you generally become attached to that idea. Even when we know we shouldn’t.

Begin with intentional evidence.

Don’t try to be persuasive, let your users do the talking. – Nathan Waterhouse

At Mailchimp they had a notion of collecting evidence as well as building empathy. They also wanted to be where the action was, so they’d regularly talk to people in the C-suite; asking “what’s on your mind right now?”. It helped direct the research to the right places, early enough to have an impact.

Design research often has to be the bearer of bad news. It helps to reframe to “the original idea won’t work, but this might”. Test the boundaries of an idea, of a product, and what people are willing to do with it. Our behaviours constantly change because our barometers.

Don’t be afraid to talk about the business. Make sure you can speak the language and build credibility, so you can keep getting access to the people who make decisions.

Scale and operationalise research – you need to be efficient to be effective. Look at #ResearchOps as it emerges.

Talk about research a lot, talk about “gathering evidence”. Communicate the long term outcomes, the bigger plan around doing research and talking to users.

Be mindful of your target. Who calls the shots? Who do you need to convince? How do you need to convince them? Talk to them in their own language, mindful of the evidence you can bring.


[Aside: this is one of those talks that is quite hard to capture as the use of media adds a lot of atmosphere that is lost in the notes. Well worth watching this back.]

Stefan Schroeder – Why Designers should care about blockchain

Stefan is crazy enough to be a designer, but he was also crazy enough to study maths for a couple of years. He is driven by the desire to make something that makes a difference. This leads to why he thinks we need more designers involved in blockchain.

A good designer is always a pissed off optimist. Challenge the status quo and make a difference. Make the world better, even just a little bit.

Two provocations:

  1. The future of innovation is not virtual reality, people plugged into the matrix. Does that really make the world better?
  2. The internet is dying. It’s broken. Back in the 90s we thought it was a decentralising force, that would give us power and freedom. But we have lost faith that’s happening.

So what is the revolution? Surprise surprise – blockchain!

Diagram of Bitcoin transactions from the article published by Satoshi Nakamoto

A little history first. Blockchain started in 1991, when some smart people figured out how to describe a cryptographically secured chain of blocks. 2008 Satoshi Nakamoto publishes a paper about cryptocurrency (Bitcoin). 2013 Vitalik Buterin describes his vision for Etherium, extending the concept of Bitcoin beyond just currency – decentralised smart contracts (doesn’t that sound like the early internet?!). 2017 saw a huge surge of interest in Bitcoin and the mainstream became aware of cryptocurrency, but interest in blockchain remains minimal.

OK, so WTF is blockchain? Without going into crazy detail…

The blockchain is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but [virtually anything] – Don & Alex Tapscott, authors Blockchain Revolution (2016)

Blockchain’s key features are control of data & sensitive information, connection of physical and digital, zero downtime, no third party… and simply being sure of things. We can create something we can truly trust.

Example problems:

  • A “fake pilot” who flew for 13 years without a license. But if that license was verifiable on a blockchain, it couldn’t have been faked.
  • The average person has to repeatedly provide personal information to apply for jobs or seek permanent residency. Once you hand that information over, you have no idea where it goes or who has it.

So what’s the challenge?

  1. Everyone is new to blockchain (this is also an opportunity for designers to get in early and help pioneer it)
  2. Blockchain has a usability problem (tech driven and under-designed, plus it needs to drive behavioural change)
  3. The challenge is not a new one (compare blockchain with the birth of the internet, there is a lot of knowledge to draw on from decades of experience building the web)

With blockchain we can create real world impact.

The UN is using Etherium in its World Food Programme, to distribute food vouchers. It reduced cost; removed opportunities for abuse or corruption; and increased privacy for refugees.

  1. Collaboration is the core of the vision for blockchain
  2. Define principles to set focus – eg. how do we design for trust? How do we create language that every user can understand?
  3. Apply human centred design

Start with knowledge. We need to educate ourselves better, educate our companies and clients. Showcase the way we could create value for them and our users.

@schrdrs | hackernoon.com/blockchain

Eduardo Velloso – Designing User Experiences with Eye Tracking

Modern eye trackers are relatively cheap, light and easy to use. But in popular culture eye tracking is generally considered something that is only used for evil.

Eduardo is not talking about heatmaps or eye tracking as assistive technology. But rather he’s talking about how eye tracking can enhance the experience when you are also using our hands (manual input).

The main message is that the eyes work in a substantially different way to our hands. Designing for gaze-based interaction is a different game. While it is very fast and indelibly linked to attention, it is still inaccurate and requires a lot of calibration.

Vision is heavily focused on foveal vision, the central area of our field of view. Eye tracking could, at best, control an area roughly the size of your thumb at arm’s length.

Challenge 1: inaccuracy

You can work with this as additional input, for example the ability to distinguish vision and touch allows different things to happen based on whether you are looking at your finger (or a stylus) or looking elsewhere. Looking at the toolbar: selecting a new colour, etc; looking at the touch point, drawing. The vision point does not need to be as fine as the touch point.

Challenge 2: calibration

Calibration is boring, slow and not realistic for many scenarios. Using relative movement negates the need for calibration – our eyes move smoothly when following something. Example: a display with moving items, that can detect which one you are looking at.

Challenge 3: multiple roles

Your eyes are already in use, looking at things! So you need to know when people actually intend to do something, as opposed to just looking around.

Our gaze is intensely powerful in human relationships. Compare the ways new couples glance shyly at each other, versus the deep gaze of a couple in love, or the distant and separate gazes after a fight.

Gaze heatmap revealing game tactics

Gaze awareness adds a whole new element to interactions like games – when you can see what your opponent is looking at, it can reveal their strategy.

Take aways:

  • designing for gaze requires new ways of thinking about input
  • use gaze in a supporting role
  • use movement to avoid calibration
  • embrace the nature of visual attention

@ed_velloso | eduardovelloso.com

David Herse – Using Jobs To Be Done Theory in Design

David tells the story…

Chapter 1: the journey is more important than the destination

David getting to the conference involved a choice between various transport options; and finding coffee; and checking if it was going to rain… It involved a lot of considerations, multiple applications, decisions and some time. This can be thought of as a timeline of decisions.

Chapter 2: how to beat the house

The failure rate of startups in the US is 60-90%. Reasons for that level of failure include…

  • ignoring customers (14%)
  • poor marketing (14%)
  • no market need (42%)

Basically they didn’t create or promote something that people actually wanted.

How do we provide value? Why do customers choose one product over another? How can we tip this in our favour?

Chapter 3: if you want to see clearly, use a switch

Simply asking people what they want doesn’t work, because people generally don’t express what they want – they imagine how they might behave.

Switch interviews focus on a timeline by talking to people who switched to or from a product in the past 60 days. Start at the purchase date, then work backwards to find out what led to it; and forward to what happened afterwards. This reveals what the first thought was, that leads to passive then active decision periods that result in a purchase.

Example: Research for selling audiobooks.

  1. First thought: my commute is boring, I’d like to do something constructive.
  2. Event 1: particularly long and boring commute.
  3. Event 2: struggling to find enough podcasts to listen to.
  4. Buying event: I’m wasting my time, I want to be productive. This is when they’d sign up for a trial of Audible.
  5. Experience phase: reference material like table and diagrams are hard to access.

Forces matrix: push/pull, anxieties, habits

  • push: 45min+ commute
  • pull: lots of content
  • anxiety: felt overwhelmed by the commitment to an audio book – they can take up to 36 hours to complete and people didn’t feel they could dip in and out of them
  • habit: podcasts, music

Chapter 4: to find treasure, you need a map

When David got into this theory there wasn’t a lot of information. He worked with a coworker to create something based on the Google Ventures design sprint idea.

A process:

  1. Draw out the timeline from first thought to experience.
  2. Map out the forces against the timeline, tagged as push or pull.
  3. Identify “how might we” opportunities, mapped to their context.
  4. Get some input from experts, ultimately come back to a vote on which HMW ideas to pursue.
  5. Ideation – flesh out solutions

Question: How might we allow people to easily access diagrams and tables when they are ready to?
Idea: Maybe feature that tracks the mentioned information for later reference

Question: How might we entertain people in a context that reduces their ability to watch a screen or use their hands?
Idea: Battle Howl, a game which is entirely vocal controlled.

These may not have been the greatest ideas ever, but the Jobs To Be Done system gives a common language to work together.


Ben Barone-Nugent & Jamie Kimmel – Collaboration and Scale

Collaboration – teams working together
Scale – teams working together not just locally but internationally

When we build, we start with what we know – it’s our own bias! We think about things we’ve used, people we know; we draw on our experience and view of the world.

Problem 1: empathise and get beyond your biases, nationally
Problem 2: empathise and get beyond your biases, internationally

Billions Building Better … Facebook does put a lot of emphasis on collaboration. Not just to decide what to do, but also what not to do.

This talk will refer a lot to challenges in localisation; and the collaboration that goes on to make it happen.

How do you work out what works well in both NYC and Bangkok? How do you go about understanding the cultural nuances of language and features?

Ben and Jamie work in a group that helps people discover things to do wherever they are; and to connect with businesses so they can make money. The idea is “social at scale” – pairing social information with search results, to make them more compelling than raw search results. If you see a recommendation for a burger bar, it makes a difference if someone you know and trust has said it’s good.

Looking at the way collaboration manifests in team structures… Teams typically have three design roles: designer, writers, researchers. This does mean that everyone has responsibility for UX, even though nobody has the title specifically. Product design is a process of how the roles interact, the healthy tension between them that drives a good result.

To put it another way, collaboration is about having conversations with other people. That’s obviously much easier if you can co-locate. Being able to spin your chair and talk to someone makes it much more likely you’ll do so on a regular basis.

We blur the boundaries of what we do. Most people are good at more than just their supposed core role.

Collaboration in action… the tension between views is essential. It can be hard to be humble, but we will always be humbled if we become overconfident and silo ourselves.

When the recommendations feature was launched in Facebook, it was added in two ways

  1. an intentional choice to post a recommendation
  2. natural language processing would pick up relevant phrases, then suggest the user turn their post into a recommendation request

That means not only does the UI have to have well-localised text and labels, the underlying NLP engine needs different data and training. Simply translating the English into Thai doesn’t work! Slang alone will be a major problem.

Design is incomplete without language.

They researched the literal Thai equivalent to the word “recommendations” and found it had a dual meaning, one that matches closely to the idea of suggestions; but another that had connotations of seeking more-personal help. That made it weird to broadcast to their whole Facebook feed.

When Ben joined the team he needed to build credibility as a content strategist – the new “word nerd” needed to show how they were going to fit into the team and add value. A good place to start is the golden rule – do unto others… Give and take feedback, open up your process to others, get to know your coworkers as people. If you don’t know people at least a little on a human level, you won’t have the context to interpret feedback you get from them.

A useful phrase is “hey I could use your help on this”, to actively bring people in. Similarly ensuring that you acknowledge when you want to go with someone else’s option for something.

But it can be truly as simple as asking people about their lives (“How are the kids?”). Don’t be pushy or invasive, but open the way to talk about more than just work.

The cultural nuances of features… understand “extreme response bias”. If you give the same survey to people around the world, you’ll see very different response rates and content. In Brazil people are more likely to answer a 1-5 scale at the extreme ends (1 or 5); while many asian countries are more likely to use the middle range (2-4). So how would you provide a global rating system for movies? Does a five-star system even make sense? This is one reason some systems have gone to simple 'thumbs up or down’ style systems.

What’s in a name? It’s often either the first or last thing in a project. The idea may start with the name, or it may be built and prior to launch a naming decision has to be made. But what value does the name bring?

Naming is really REALLY important. It says a lot about how you want to engage with your audience. A good name sets clear expectations for what your product is. It shows empathy, shows that you understand the customer.

When you are releasing something globally, you run the risk of losing people with a one-name-fits-all-markets approach. The “Local” feature was well-named for America, but didn’t work everywhere. In Thai the translation of “local” was a bit negative.

A naming process:

  • namestorm – throw lots of ideas around
  • wording – put some contenders into context, write some copy using it
  • locals – check with locals, talk to people who work in various regions to give feedback
  • testing – run experiments to see if the names work

The localised versions of the product did show good metrics; but ultimately it was worth doing to simply have a stronger product.

Last thoughts…

The intuitive is different from the actual – you think that simple translation will be enough to roll out a product or feature in a new region, but it just doesn’t work out that way. You need to understand cultural nuances of the target market and then keep testing and iterating as you learn more.

Ultimately in some markets you will need to solve quite different problems to get to the same result. American users were comfortable asking large groups of people for a recommendation; but Thai users preferred to ask much smaller groups, often with something like messenger rather than the open news feed.

The actual requires collaboration. Get to know your coworkers as people – people don’t have brick walls between their personal and professional life. Meet with people a lot. Co-locate when you can, to the product and not to the discipline. Be open and honest and human. When people know each other well as people, they can have much more honest conversations.

Names are really important. You need to think about them carefully, and not just through your own prism.

Diana MacDonald – Should I really bother learning to code?

Diana is here to help you answer this question for yourself. Also consider the question 'how much code?’

Diana has been described as one of CultureAmp’s “code-ier designers”, but actually started training as an accountant before that; and also worked as a tech editor. Despite never working as a full time engineer, it has become part of her workflow.

Will be talking about…

  • Roles
  • 3 ways to use code in your workflow
  • Where to go next if code interests you

Some people think that designers who code are unicorns that don’t exist, or that you have to choose one or the other. Neither is true. Yes it’s true that you cannot go as deep on everything as you can on one thing. But it’s also true that you do not work alone. So you should consider the skills of your whole team and how they fit together.

Understanding code is important if you work in areas like AI and machine learning. You have to understand what the capabilities are.

However you work out your own role, coach people on your process. By inviting people into your process, you can show where the edges of your role actually are.

Diana uses the limit that she codes, but she does not ever ship code to production. It is the devs’ job to create code which meets the production requirements, which takes time; while the purpose of prototyping is to be fast, you don’t want to spend lots of time planning a robust coding approach.

Ways to improve your coding…

  • Design in the browser
  • Prototyping
  • Personal projects

Designing in the browser can be as simple as:

document.designMode = 'on'

This works in Chrome dev tools and makes the text in the page editable. You can go a bit further and learn a little CSS to tweak colours. Then take a screenshot into your usual dev tools and continue from there.

Another way to improve coding fluency is prototyping. Diana needed to see if some animations were going to work in the browser, so she tested them with real code. Balance speed and fidelity. Don’t write something in code if you don’t need to in order to test something.

Personal projects are another way to improve fluency. Diana uses Rands Trickle List approach to keep track of intermittent activities. She coded a simple way to show which items she’d done on a given day; then used screenshots to track them over time. Yes she could have done a deeper coding challenge and built a full app; but in the end… just code what you really need and fake the rest!

By just creating a simple set of toggle buttons, Diana learned about aria-pressed; which she was able to then use in a future project. So even a small project has broader value.

So where to start if you want to learn?

Build a passion project. They give you an opportunity to play with things without having to go too deeply into them.

Tweak your own tools – Sketch plugins are written in JavaScript!

  • “Design or code” is a false dichotomy
  • There’s opportunity cost – in teams and AI
  • There’s value in fluency – without coding
  • Design in the browser – with a little code
  • Balance speed and fidelity in prototypes – with as much as you need for realism
  • Code for immediate value and fake everything else

So if you ask yourself “should I learn to code?” also ask “how much code?”, but also think about how code can add to your design process.

@DiDoesDigital | slides, resources and notes | DiDoesDigital.com

Remya Ramesh – The art of mindfulness in product design

When you are “present at work” are you really present?

Although initially skeptical, Remya found that with practice mindfulness really took hold and helped her manage feelings of stress. But then why was that confined to home? Why not at work?

Mindfulness is awareness that arises through paying attention, on purpose, in the present moment, non-judgementally. – Jon Kabat-Zinn

Mindfulness focuses on the present – we do not have control over the past or future, we only control the moment.

Meditation is one form of mindfulness, but it is only one way. You can do something as simple as paying proper attention to what you are doing – instead of using your phone during lunch, actually stop and enjoy what you are eating.

Remya then found the science behind mindfulness was also fascinating – mindfulness can literally change your brain. Two interesting points:

  • Activate your Anterior Cingulate Cortex (ACC) with mindful meditation – this helps you make decisions
  • Meditation fortifies the brain’s memory vault, the Hippocampus

People spent 47% of their waking time thinking about something other than what they are doing!

Things people can do:

  1. Micro meditations
  2. Conscious collaborations
    1. Mindful listening.
    2. Active observation.
    3. Purposeful presentation.
  3. Design with intent

Micro meditations are quick exercises that take 1-3 minutes, that you can do several times a day. Try a breathing exercise first thing in the day, instead of immediately grabbing your phone and thinking about the coming stresses of the day.

Think about the way people 'listen’ to each other while doing something else. Drop any judgements, maintain eye contact (although don’t give them a full on stare!), work hard on being present, provide non-verbal feedback.

Most people do not listen with the intent to understand; they listen with the intent to reply. – Stephen R. Covey

Observation… clear your mind, observe others without any assumptions, stop multitasking.

Multitasking demonstration:

  • count 1-26
  • list a-z
  • now work all the way through 1a, 2b, 3c…

1-26 and a-z are easy and you can do them quickly, but it’s much harder and slower to go 1a, 2b, 3c…

Presentation… facilitate conversations (be self-aware and ensure everyone has room to contribute), be prepared, provide feedback, manage emotions.

Design with intent. Apply principles of calm technology, create positive influence and change, value human attention, avoid dark patterns.

A word of caution: we are in an age when mindfulness is being taught in schools and corporations are setting up mindfulness programs. But you have to ask, does a company really care about you as a person if they are setting up mindfulness programs? Or are they just trying to make the unbearable bearable? Also beware of avoidance risk, groupthink risk and the corporate mindfulness bandwagon.



Cory-Ann Joseph – Why a poker-playing AI should have designers looking for a new job

Cory-Ann is a UX designer, a copywriter and a former professional poker player.

Cory-Ann became a serious poker player in 2008, although it’s important to note it has no relationship with what you see in the movies. It’s more like staring at tiled windows, building a database of hands and players. She played for about six months before giving it up.

The software used to play pro poker was all pretty bad, really ugly and hard to use.

She found herself thinking “there must be a job where you fix bad websites”... so in 2009 she got a job at a UX consultancy, intially in sales but then moving into the consultancy side.

The Nash equilibrium was being applied to solve hands of poker; and Cory-Ann wondered if you could solve design in the same way?

  • Poker players are grouped by playing style and behaviours, which is similar to personas
  • Both have fixed and fluid elements
  • Both use a process of many solutions, with refinement
  • Both are fundamentally about human behaviour and actions
XKCD comic comparing AI and human players for various games

It seemed like she was on to something. But in 2010 the technology just wasn’t good enough to be able to beat human poker players. It wasn’t even close. Then later in 2013 design was ranked as being incredibly safe from the rise of AI, compared with many other professions.

But then in 2016 a computer was able to beat a human Go player, which was ranked as being even more difficult than poker… and in January 2017 the Libratus Poker AI soundly beat several professional poker players! At which point she paniced a little and set up a five year plan to get out of design…

So what’s the landscape now? There are many AI-based products, including some successful sketch-to-code experiments. Design is not immune to AI.

See algorithms.design

There’s also another thought though – if demand for design grows the way Jakob Nielsen expected, there will be a shortfall. There will not be enough people to do all the design jobs. So what’s not going to get designed?

There is no agreed or clear vision of the future. There are people predicting both that design will be taken over by AI and that it won’t.

We should consider what companies might look like without UX and designers, what would they be doing instead?

@coryannj | The huge reading list

Darla Sharp – Crafting Conversation, design in the age of AI

While all of us having experience designing screens, many of us don’t have experience designing for voice.

Darla currently works at Google (Assistant team) as a Conversation Designer, although the job may also be called Voice User Interface (VUI) Design, or Voice Interaction Designer. In the end it’s just interaction design with a focus on voice.

Google is moving away from mobile-first to AI-first. Google Assistant’s product line is expanding rapidly, including some devices that do actually add a screen (although not as the primary focus).

Design + AI – there is an increase in voice-forward design. The question of course is why? When we all have smartphones why do we need this additional modality?

  1. speed and simplicity
  2. ubiquity

When voice works it really is quicker – there are a surprisingly large number of taps to do simple things. For example you can ask for the latest Gorillaz album in Spotify, much faster than you can open up the app, search for it, find the album and tap to start playing it.

Phones are considered ubiquitous, but as virtual assistants spread to other places they are getting more popular. You shouldn’t be using your phone in the car…. right?! So the ubuiquity is moving to the assistant and not the device.

Design considerations

  1. conversation design, which owes a lot to linguistics
  2. speakers (not the devices)
  3. the tools in the toolkit
  4. expanding ecosystem

Conversation design owes a lot to linguistics; and the way humans process language.

Words (sound into words) → Syntax (words in to phrases) → Semantics (derive meaning) → Pragmatics (interpret meaning in cultural context).

This is really easy in a first language, basically instinctual or obvious. However it is incredibly fragile, if anything breaks the entire interaction falls down. If someone makes a mistake in a second language, it confuses people who are talking or listening to them. Or if someone’s accent makes the sounds hard to understand, the most basic level of comprehension has broken.

How does this break out into conversation design?

Front end:

  • Words: What’s the weather today?
  • Syntax: In Alameda today, it’s 72 degrees and sunny.

Back end (most of the time is spent after this, on logic and UX flows)

  • Semantics
  • Pragmatics

This interaction requires knowledge of the user’s location and preferred units of measurement (degrees F or C?).

Cooperative principle – rules that we innately know, that we use in order to be good conversational analysts.

  • Quality – appropriate for context
  • Quantity – as informative as required (neither too little or too much)
  • Relevance – unambiguous
  • Manner – true

When assistants get something wrong, they will have violated one or more of these principles.

Examples of Google Assistant getting these wrong…

  • Quality – “open uber” → “I can’t open apps” ... but they wanted to open an action they know the assistant can do
  • Quantity – (a question about politics/law) → the response had way too much information and wasn’t the right detail
  • Relevance – “what was that last song” → (long plot synopsis of a movie called The Last Song)
  • Manner – “ok google can you tell me directions” → “I can’t find that place” (actually she’s just lying, she can tell you directions)

Cognitive load – this is discussed all the time in voice design. When we listen to people talking, we form a syntax tree that lets us understand the words. We can both listen and process, this is within our capacity of cognitive load.

“I shot an elephant in my pyjamas” can translate into two different language trees. One has you wearing the pjs, the other has the elephant wearing them. We know who is wearing the pjs, but computers have a much harder time.

Example 1:

User: Hey Google, any flights to San Francisco on Thursday
A: Yes, there are four flights. They’re at 1:15, 3:55, 5:05 and 6:35pm. Do you want to hear more about one of these.
A: Yes, there are four flights. Big Blue Airlines 47 leaves New York at blah blah blah….

Speakers… people may be speaking in a very large range of scenarios. They may be hands-busy or eyes-busy, they may be multitasking, they may be in a private or public space. Users are all instant experts – we’ve been talking all our lives! So they have high expectations and low tolerance for error.

The other side of speakers is your assistant, which is representing your brand when it’s talking to the user. It manifests brand attributes, it has a back story and a role. If you don’t define all this, your users will!

Text-to-speech can really change the nature of the communication. Simply removing the exclamation mark from “Let’s go!” completely changes the tone. TTS makes the word “actually” sound incredibly rude and condescending, because all the tone and body language is stripped away. So were it might have said “actually” you need to find another word, to design around this issue in the medium.

We have many tools in the toolkit now – people can speak, type, tap and show things to a device. Most organisations still have siloed teams working on these modalities.

The nature of the speech-only signal is unusual. It’s linear, always moving forward (there’s no nesting or layers the way we work on a screen); and they are ephemeral, constantly fading. They were here and now they’re gone – imagine a screen interface that only shows for five seconds before fading away.

There is complexity in recognition and understanding – what users say and mean. ASR and NLP.

“What’s the weather in Springfield?”
→ which one? there are many across America and even around the world

“Play Yesterday”
→ do you mean the movie or the song..?
→ which version of the song? the original or one of the covers?

Text to speech has the rhythm and melody of speech. It’s not just what you say, it’s how you say it.

As more devices become available, it gets more complex to work out how things work across all of them.

There is a spectrum from voice only, to voice forward, intermodal, visual only.

There is a range of user conditions – static or in motion, public or private space, rich or poor touch interaction. Mobile phones move through these, the context changes to the extremes for motion and privacy.

This is also why porting things doesn’t work. If you port a screen app straight to voice, it just doesn’t work.

The number one thing is to design for empathy. That’s a real challenge for a platform as big as Google, but it’s really important… it’s very hard but we try!

Day Two

Sarah Federman – Design Systems at Scale

Sarah is a designer and developer, which is why DesignOps makes so much sense.

But let’s start with a brief history of the universe. Back in the day UI was designed in Photoshop, sliced up and handed off to developers. Then over the years flat design helped bring vector tools to the forefront; and now we have tools like Sketch that have concepts like Symbols into them. At the same time the code grew from basic CSS to systems like OOCSS and BEM; and methodologies like Atomic Design.

We’re not designing pages, we’re designing systems of components. – Stephen Hay

We’ve also moved to a much heavier focus on client-side applications, particularly with React. It encourages a component based approach. This intersection has really exploded in recent months with crossover tools like React Sketch App. In reality the design and dev worlds have been coming together for years.

We have reached the rise of design systems – not just UI libraries or style guides, but well-rounded design systems. These often support money-making work without making money in and of themselves, so they can be open-sourced. This is helping the movement grow as people can get the code.

Design systems are a product that help us scale our design practice. Scale here means getting the best results with the least duplication of effort – keeping your designs DRY. Duplication leads to fragmentation – we have heard all the stories of companies finding dozens of shades of blue through their product suite, when there should have been one.

A design system is an organisational structure. What is the company structure? Are the designers embedded with product teams or centralised? Are product and marketing separate?

A design system is run like a product, not a project. They have ongoing work, they have a roadmap, they need staff like any other team. Design systems as product moves the narrative away from process.

Sarah’s favourite analogy is whiskey. What is it that makes a great whiskey so good? Was it the ingredients, the process, the people involved, the occasion you drank it, the fact it cost a bit of money?

Resources + Ops = product
Product + Emotion = experience

For a design system – operations are how things are made; product is what it is.

What goes into your design system depends on your organisation and what it needs.

Why do we even want a design system?

  • fast iteration
  • stronger brand identity
  • common language
  • better user experience

A good design system becomes a delivery mechanism for important goals… although it can also be a single point of failure!

There is a lot of activity in the tooling and operations space at the moment, giving us lots of opportunities to evolve the way people work together. Adobe is moving away from red lining (annotating the design details) to blue lining (documenting the invisible details like accessibility).

At what 'scale’ is Adobe doing their design system (Spectrum)?

  • 250 designers
  • 124 branded tools in the market
  • 4 colour themes
  • 6 platforms
  • multiple frameworks

This combination multiplies out so that a simple pill button has 1080 permutations!

How did they get there with Spectrum?

First they had to build trust.

They started with a website and an XD file, but since they were often out of date they hit a pain point about which one was the source of truth. People would be asking 'does this work for my product, on its platform?’

So they raised the bar for what was considered canonical, creating Inclusion Criteria for adding things to Spectrum. Anything going in has to work cross-platform, support all 4 themes, be accessible and must be documented. This meant that a lot of features were effectively removed from Spectrum as they didn’t meet these criteria.

They declared that the website is the source of truth for Spectrum. Design assets are still available on a network drive, but they are versioned in synch with the website and released with a scripted process.

The documentation has huge amounts of detail including the interactions, details about implementation (is it available in the CSS and React implementations), usage guidelines (do and don’t examples).

Over time the templates were getting brittle, so they broke them up into more granular pieces – made it much more declarative than imperative. This reduced the need to know the full page design to be able to use components.

How do they build and deliver Spectrum?

They have several implementations – CSS, React and 'native’ for specific platforms. They have recently standardised the web apps to React.

Spectrum DNA is stored in JSON – essentially design tokens. The variables are layered – there are global values, which are used in component variables.

The asset creation pipeline has significant scale challenges at Adobe, where single products like Photoshop need more than a thousand icons.

Only a subset of the original components met quality requirements

Designing at scale hit the next pain point: where did everything go? By raising the standard for inclusion, they removed things people had been using and they didn’t know what to use now. They’re working to reinstate all the funcationality, but they needed to go faster.

They now release “Spectrum Precursors”, for beta features. It lets people share and work on features before they are finalised and go into the main library. They’ve even used spot bonuses to encourage contributions!

They’ve also evolved the way they do documentation. They now start the docs before the development is finished, using Dropbox Paper. By bringing more disciplines in earlier, they find more gotchas.

The design assets include 'sticker sheets’, which is basically a huge set of examples of components in all their states. They have developed a JavaScript tool to generate them as SVGs which can be imported into XD.

How do they measure success? How can you assess adoption at scale?

Example scorecard

Currently they are doing a trial with Spectrum Scorecards – simple, single-number scores; allowing self-assessment so the system can scale. The second part of the system is a Spectrum Assessment, done by a core team member who is more deeply familiar with the system. Currently the scores focus on the basics like color, elements, icons, inclusiveness.

The continued story of success for Spectrum is based on bringing together design, development and operations!

@sarah_federman | Slides | medium article

Hilary Cinis – Crafting Ethical AI Products and Services–a UX Guide

Data61 focus on every aspect of data R&D. Everything from data collection to insights and the interface to consume data.

Discussion of data and ethics will quickly lead to philsophy. There are two general philosophical schools – utilitarian and deontological (sense of duty).

AI and machine learning do not have their own agency – they are created, the agency remains with the humans who make them.

So why have an ethical pratice for technology? What informs it and how achievable is it? There is a great opportunity right now for UX people to get really involved in the ethics of business.

The IEEE make many great points about having to underpin philosophy with legislation, to cover the people you simply cannot control or appeal to. Systems need to be sustainable, accountable and scrutinised. These are not unreasonable things to expect, as this impacts human rights.

The AI Now 2017 Report talks about the importance of user consent and privacy impacts, particularly when business needs (profit) are controlling the development of an autonomous system.

In all data situations there is a trust vs utility tradeoff. Facebook’s recent problems stem from allowing private data to become public data, pushing too far to utlity and breaking trust.

So how can we capture and anticipate ethical implications – what are the tradeoffs and compromises? We need efficiency but we also need to avoid harm. If we can write a sentencing algorithm for the legal system, can we trust it to do what we expect as a society? What level of error is acceptable?

How can we create and use perceived affordances for users to understand what a system is doing, and make a decision on whether they can trust it? Does the system use language people can understand if they don’t know enough to vet the underlying algorithms?

“Edge cases” is a terrible phrase. Everyone is an edge case. We can’t devolve our responsibilities by claiming it won’t happen.

The questions to guide you:

  • can we – legally? ethically?
  • should we – does it give a commercial return?
  • who and why – UX and product (duty and intent)
  • how to actually build it – development (encoded utility)

Where does this leave us as designers? Many people place the responsibility for ethical systems on the product and design teams. This scrutiny is actually a great opportunity to go to the business and push for the support to do great work.

The discovery phase of these new systems isn’t really that different. The who and why should still be considered before the how and what. The most powerful person is still the CEO or whoever is paying the bills; the people with least power are the users… and yet the system is based on their private data. The technical experts sit between the two. Our natural skillsets in service design enable us to guide others.

When we communicate to users about data, there are many layers that go before which affect the credibility and trustworthiness of the experience. If the data isn’t precise or complete, the inferences drawn from them will be questionable. This should lead to disagreement and credibility is lost.

Some industries like aviation safety have this kind of debugging nailed, we should look to them for inspiration.

The myth of the black box has to stop. Hiding algorithms behind IP doesn’t hold up, they can be audited without giving away the IP. People need to know what algorithms are doing, how they work and why they’re being used. We can’t wait for crisis points to have these conversations, it should be going on all the time. You should be able to explain what data is being collected, what you’re doing with it and where it is going.

But these core questions of who, why and what are the core of UX practice. They’re not new or scary, we know what to do! Inclusive design needs to come to the front, everyone needs to be included.

Nielsen’s Heuristics

  1. visibility of system status
  2. match between system and real world
  3. user control and freedom
  4. consistency and standards
  5. error prevention
  6. recognition rather than recall
  7. flexibility and efficiency of use
  8. aesthetic and minimalist design
  9. help people recognise, diagnose and recover from errors
  10. help and documentation

A simple point is to treat your users like smart people! If you are making a prediction with a level of uncertainty, explain that. People can understand the weather forecast isn’t 100% certain. They understand the idea that a 90% chance of rain means it probably will, but might not rain.

Strive for ethical practices; reframe good design practices to apply to the new work; set up diverse, multi-disciplinary teams; challenge “can we” with “should we”. Just because something can be made doesn’t mean it should be made; and not everything can be an experiment when peoples’ lives are involved.

Remember this needs to be an ongoing conversation. Get involved in whatever piece you can, share what you can, keep asking questions.

@hi1z | article

Nathan Kinch – It’s time to design for trust

Nathan has been taking notes watching the presentations…

  • The attention economy was designed. We tend to forget that.
  • The internet is dying! We know that it has to change, so much has happened since its innocent early days.
  • Reframing eye tracking… we look forward to the twitter banter with Jared Spool!
  • Jobs To Be Done has some great discussion going on right now
  • Facebook… that’s all about trust
  • Diving into the evolving role of the designer… we forget opportunity cost when we’re in the process
  • Design vs code is a false dichotomy
  • Mindfulness – while it’s been part of Nathan’s life he’d never thought of it in the professional context
  • Cory-Ann – such a great reframe but I’m never playing poker with you
  • Conversational design – it’s reassuring that even big companies find this tough
  • Ethics – we are in a unique position of power

Themes that emerge:

  • Diversity and inclusion
  • Designing for people (not “users”!)
  • Ethical and trustworthy design

Which brings us to Nathan’s topic, trust.

What’s going on in the world right now? Breaches. Data breaches, or data policy breaches. Facebook isn’t as interesting to look at as Equifax, because Equifax was such an intentional abuse of data and power to make money. We have to be aware of this stuff because there are huge consequences. People committed suicide after the Ashley Madison breach, this is serious shit!

If you talk to people in industries like AI and IoT, you find that people still consider security and privacy as unsolved problems. We are going there before we’ve figured it all out.

Standards are emerging though – there are standards coming for tracking of consent, not every organisation has to solve all the problems from scratch. There’s no reason for us to make it hard to understand what we’re doing with someone’s data… all interactions are designed. There are humans behind the decisions.

We’re heading to more participatory business models, rather than the blunt attention/surveillance model. Participatory models are based on sharing profit with the users who provide the data.

The EU is trying to codify human rights in the digital world, which is something we haven’t seen before.

There is a data trust gap – people trust businesses more than they trust those same businesses to handle data. This varies by industry, eg. we trust our doctors more than the media.

A loose definition of data trust is whether the user will willingly share their data.

Three plays to build trust:

  • Get to know the market
  • Get to know your customer
  • Then evolve design practice to include data trust experience mapping

Book: Designing for Trust

It’s a book that becomes useful when you have a job to be done.

Where are we going with this?

  • we are in a very low point for data trust right now
  • there will be more data sharing in future
  • Greater Than X is working to open source their data trust framework – an example they’ve released recently is a pattern for up-front consent to use data

Let’s design for trust together. The time to design for trust is right now, but we cannot do it alone.

Give people power, respect their agency, give them control. This is great for business – trustworthy brands are more meaningful; and more meaningful brands perform better financially.

Designing for trust is not just good for people, it’s good for business. Together we can design for trust.

@nathankinch | greaterthanexperience.design

Sally Bagshaw – Beyond words: using content strategy for better UX

So what do you think of when Sally says the word “content”?

Most people think immediately of the words, or more to the point what’s going to replace the lorem ipsum.

<insert content here>

The problem is that the words tend to come at the end of the project, after all the research and design has been done.

(Does everyone recognise this..? the red content strategy book)

Sally will be looking at…

  • empathy
  • content systems
  • teams

Empathetic content – content in the right tone that people can read and understand. Content is deeply emotional. You will be experiencing emotions when you consume content… the content can make you feel excited, or terrified, or confident. While it seems obvious, you have to make the content readable – meaning it has to be clearly understandable in context.

Bad example – a letter from a life insurance company explaining they would not be paying benefits. It’s full of jargon and has a very cold tone, out of step with the context of someone who has just gone through a bereavement. There’s no empathy whatsoever and that’s something we can work together to avoid.

So where to start? Embed content questions from the beginning of the project. Understand how people are feeling when they are dealing with the content.

A simple worksheet to help can ask:

  • intent – why is someone reading/view/listening to this content?
  • emotion – how are they feeling?
  • tone – what tone is correct

Useful tools:

  • You can use Hemingway to get a rough score of readability. It’s not perfect but it’s a great sanity check.
  • You can assess whether people understand it with a cloze test, where you take a chunk of text, remove key words and ask people to fill in the blanks. If they can fill it in with a reasonable level of accuracy, the text is understandable.
  • alexjs.com can remove biased language

Content systems – infrastructure that enables people to use content the way they want. Content management at scale is very complex, but the users don’t care – they just want consistent, clear information.

You can start by looking at a content model. A great example to understand this concept is to analyse a recipe, as it has a clear and familiar structure.

In content systems we care about metadata as well as the visible data. Tags are great in content systems, so long as you have a really strong taxonomy. They tie in to things like calls to action, so they cross over with component systems.

Great teams come from processes and culture that enable smart content decisions.

People are the hardest part of the system – people are messy, they care, they have opinions about things. Teams are super important to the content process.

If you have a large content and transformation project, consider…

  • how it impacts roles and responsibilities
  • approvals and workflows
  • training and skills development
  • recruitment and team structure (any new roles required? changes to PDs?)
  • community of practice

A common gotcha is agile project teams handing over to traditional teams for BAU. How do you equip them to use processes designed around an agile mindset, with iteration cycles?

In your next project, think about:

  • editorial (as normal)
  • empathy
  • content systems
  • teams

Peope are at the heart of what we do. They use the content, they create the content. Let’s make sure they are better equipped to do so, because that’s good UX!

@snappysentences | slides | speaker notes

Sara VanSlyke & Trace Byrd – Illustrating Balanced and Inclusive Teams

Sara and Trace will be talking about making illustrations more inclusive… first they want to acknowledge the irony of “two fo the whitest people you’ve ever seen, talking about diversity”. It’s not the job of minorities to promote diversity, it’s everyone’s responsibility.

In the US there is an almost exact 50% split between males and females in the population; but you wouldn’t know that to look at congress. This shapes peoples expectations, as do your own products regardless of whether you intend it.

When Atlassian rebranded in 2017, inclusion was part of the process and it was reflected in the illustration style. Atlassian uses a lot of illustration in its brand, so it’s quite powerful. It also has the same problems of stock photography – where there are easy-but-cheesy images to illustrate things like “teamwork”.

Lessons learned

  1. understand the difference between diversity and inclusion
    1. diversity is quantitative, people are represented
    2. inclusion is qualitative, people feel included
  2. challenge assumptions about your audience
  3. visual diversity
  4. conceptual inclusivity (eg. body language and power dynamics)
  5. communicate and empower

Illustration is a great chance to demonstrate representation. When showing people doing things, you can break the usual stereotypes about roles and who can have them.

Challenging assumptions was particularly difficult at Atlassian as it’s a company for developers, by developers. Atlassians are used to thinking the customer is really exactly just like them. But in reality when it comes to diversity and inclusion, the audience is everyone.

Visual diversity required Atlassian to lose the blue and white “meeples” (like the stakeholder, second from left..) because although they were neutral in some ways, people mentally defaulted to white and male. An attempt to move to more human figures started with “no skin tone”, but that’s not a thing because it just defaulted to the default white background.

Then there was a terrible over-correction to cartoonishly stereotyped images, which thankfully didn't ship. Ultimately they came to a nice set of subtly hinted illustrations, but people didn’t recognise themselves in them.

They tried using brand blues as skin tones, to avoid the entire problem. But it made groups look too homegenous and left it open to interpretation – including a default to white.

The current set of meeples strikes a more nuanced balance. Individual characters do have elements that define race, gender and so on. But they have a wide enough range to avoid stereotypes or homegenisation.

Composition can still create issues. In one example shown, the men were placed noticeably above women in the image, so even adjusting the number of people did not change the implied power dynamic. The fix was simple – swap a male and female figure so there was equality in the placement.

Action and role can still be difficult. An attempt to include a character in a wheelchair accidentally emphasised their disability and not their agency. The solution was to move the disabled character into a different role in the image.

Just creating design assets doesn’t mean everyone will know how to use them. The meeples are published at Atlassian for anyone to use. To remove guesswork, they assigned diverse groups to common background colours; so if in doubt just pick a set with the common background and it should be acceptably diverse. Also the icons for job/role are badges that can be added to any meeple, to avoid tying a particular person to a particular role.

Continuous improvement is better than delayed perfection. – Mark Twain

Leisa Reichelt – Putting Research In Its Place

Leisa starts by talking about a potential tattoo… but she just can’t have the typography of the design. How do you pick a typeface to go on your body?!

Perspective is the user researcher’s super power.

To understand perspective we need to understand truth.

Let’s go back in time… to when the internet looked like NCSA Mosaic and people made things in Hypercard.

When Leisa went to uni they were heavily into postmodernism, it permeated all the subjects.

Postmodernism believes God has died and as a result we now have to construct our own truths. We could agree on some facts back in those pre-Trump days, eg. we could define a general definition of the colour red. Even if our precise idea of red differed slightly.

Trick photo - bird's shadow looks like a shark, but it's really just a duck!

There are no facts, only interpretations. – Nietzche

“I think Nietsche would be absolutely loving politics right now…”

Other people have a view of the world that is very true to them, and how we feel about that is very important to be able to get along together.

William Perry’s schema of cognitive development:

  1. Dualism – Knowledge is received and not questioned. Students feel there is a “correct” answer to be learned.
  2. Multiplicity – There may be more than one solution to a problem, or no solution. Students recognise their opinion matters.
  3. Relativism – Knowledge is seen as contextual. Students evaluate viewpoints based on source and evidence, and even experts are subject to scrutiny.
  4. Commitment – Integration of knowledge from other sources with personal experience reflection, make a commitment to values that matter and learn to take responsibility for committed beliefs. Recognition that acquisition of knowledge is an ongoing activity.

So where do you fall on this scale? Where would you kids be? Where is your company on this scale? ...and why should we care? How does this relate to user research?

It’s part of framing, how we define the problem we set out to solve. Don’t fall in love with a solution… but how do we fall in love with the right problem? How do we konw we are focusing on the real thing and not the shadow of the thing.

Example problem: what to do about the Medicare enrolment form, required for people such as newly-arrived immigrants or newborn children. Well the obvious thing is to digitise the form! But at the DTA they had to work to the DTA standard, meaning they had to 'know all about the user’. Goverment forms have lots of complexity; and the people using them are also complex. They have a huge range of backgrounds and contexts.

If you need reminding that your customers/consumers/users are people you have bigger problems. ... User is a good word because it clearly indicates what the relationship is all about. Our primary responsibility is to make something that someone can use. It’s about utility. – Russel Davies, Consumers, users, people, mammals

The best solution was not to digitise the form. When a baby is born, the hospital already collects all the information required to enrol in Medicare. So the better solution was to simply have it done automatically before they went home.

However the initial framing had been biased towards immigrants, not the more common case of someone having a baby. The framing was wrong, so the solution was wrong.

The answers you get depend on the questions you ask. If you ask people about the shadow, they’ll tell you about the shadow.

A classic case for Atlassian: “what is the thing you do most often in JIRA?” The problem is the assumption that JIRA is the centre of the user’s world. It’s not really how people think about it.

You could instead ask: “what are you doing most often when you come to use JIRA?” This puts the focus onto the user and what they are trying to do.

No research is neutral. No analysis is unbiased.

It is a complete fallacy that you can do research without a bias. You can just try to have as much awareness of that bias as possible; and which truth you choose to privilege. Know which duck you are dealing with. Where you are in the organisation impacts the questions you can ask.

Six models for situating user research:

  1. non existent (we need to be realistic that this happens)
  2. sporadically outsourced
  3. ad hoc, not specialised
  4. internal consultancy
  5. embedded in product teams
  6. centralised strategic

(Natalie Hanson’s stages of UX maturity)

There are really only two models you want to aspire to: embedded researchers, or centralised strategic.

So which one is right for you? Naturally to decide you make a 2×2 because, well, that’s what you do. This one is Transaction/System vs Optimisation/Innovation.

Applied examples:

  • UK Govt Digital Services – embedded approach worked really well, everyone was convinced. It was heavily driven by transactions that were quite difficult, but the overall shape of the transaction was quite linear.
  • Australia’s DTA – initially the work was very transactional, so they started with an embedded model. But over time they started to look at 'super services’ that moved across multiple government systems, which is a very messy transaction. So they shifted to having a centralised team as well, to work on the cross-cutting issues.
  • Atlassian – started off with an affinity sort and decided to focus on impact and capability. For a large team Atlassian had very few researchers. So pooled into a central team.

Atlassian’s approach:

  • User centred
    • For Atlassian an example focus area is How do teams make decisions and prioritise work? This is a user-centred approach, not a product-centred approach.
  • Continuous research
    • They talk about hunches, a feeling or guess based on intuition rather than fact.
    • Over the insight lifecycle they take a hunch and research it, until there’s more certainty.
  • Mixed methods (quant/qual)
  • Decentralised product research

Just about every designer reacted that they agreed with this academically, but in reality it did make their life a lot harder. So they needed to help people a lot, as they grew their ability to do research. They also had a lot of challenges with user recruitment for testing.

The truth will set you free, but first it will piss you off. – Gloria Steinem

...and that might be the next tattoo.


Lucie Paterson – Evolving an organisation’s culture through design

Lucie has worked at many museums; and while she gave agency a go when she moved to Melbourne, she missed the ability to effect change over time… so she’s now at ACMI. In 2015 ACMI got a new CEO and a new vision to completely redo the museum by 2019, which has just been approved and fully funded.

Lucie is part of a very small team. Everyone is responsible for the user experience for ACMI visitors. In the modern world where the moving image is in everyone’s pocket; and art is moving from content to experience; what value can ACMI provide? The old world of providing background information about artists doesn’t really cut it.

They were facing some issues.

  • There was not enough holistic, cross-team collaboration.
  • They had low brand recognition, 48% of visitors were “unintentional” visitors.
  • They did not leave the house to come to ACMI, they just came across it and visited. Even then they may not think of having visited ACMI, just that they’d seen an exhibition at Federation Square.
  • Internally there was a low appetite for risk – people were not comfortable with experimentation and failure.
  • Matching the pace of internal change to the pace of external change is hard (exhibitions generally take 2-3 years to plan and execute)
  • Lack of transparency in comms and decision making
  • Current “design” team sits in marketing and they are strictly visual designers, not UX.
  • The required change is ongoing, never finished – and that doesn’t match the project model people are familiar with.

There’s no silver bullet or magic wand for big transformation. But there is design. As designers, we break down large-scale change into a series of discrete but interconnected acts that together, over time, lead up to new behaviors and opportunities. – Diana Rhoten, IDEO

Museums are exciting spaces to test and experiment. They are both physical and digital; and people often spend a couple of hours when they visit.

So what have ACMI been doing? They treat each exhibit as an opportunity to try new tech.

  • Scorsese – they put extra content onto an app on your phone, which could be viewed on site or at home. 58% of visitors in the first month used the audio guide (usual rate would be 20%).
  • Terror Nullius – a 55 minute work, but they noticed a lot of people were leaving immediately. It was an onboarding problem, so they added a countdown to when each run started (too soon to measure results).
  • They followed a hunch that people would like extra content to consume before and after visits. So they put up lots of information for an Oscar Wilde exhibit, and 20% of people read every last bit.
  • Rebranded and relaunched a clearer website, prioritising the majority use cases instead of being an exhaustive list on the homepage (focus on the 80% and don’t sweat the rest).
  • They attempted to create a tablet-based ticket sales system, but it just couldn’t be done… so they just built another ticket desk at the second entrance. Not what they imagined but it worked!
  • Wonderland included NFC treasure maps; and post-visit content to continue the experience.

This is the result of about two years of work. It required user testing prototypes with visitors; working across all areas of the museum. They apply the same UX design approach when designing internal systems and processes. Simple things like introducing Slack and Trello have really helped break down silos.


  • Visitors love to help – recruit them for testing
  • Empathy and patience with staff goes a long way
  • Change is hard!
  • UX design is a great way to help make transformation happen

What’s next?

Building on their successes they are working with more teams across the museum, to spread UX design thinking. They’re building up a UX playbook to help people do it themselves.

But most of all… they’re ready to get started on the user-first rebuild of ACMI.

@luciepaterson | slides

Kate Conrick – Doing Good (Design) in Government

Everyone who has interacted with government has probably said something like it was the worst website I’ve ever used. You hear it a lot when you work in government.

In goverment Kate finds she’s usually starting at the bottom of the pyramid – simply does it meet needs and nowhere near is it enjoyable to use. Building things that work is hard, making them great is harder.

Building the wrong thing is wasteful; and people in government are aware they’re spending public funds. But the environment makes it very hard to make changes around entrenched processes and power structures.

Digital transformation is a big focus for all governments in the modern world. However in Australian government it’s not yet evident in areas outside the DTA. In most areas it’s just digitisation, a lift-and-shift change and not the digital revolution needed for profound improvements.

But then, small changes in government can still have a huge impact on people.

Example: a form which cannot register someone as a gender other than male or female; but has a message acknowledging this is a problem. It’s a step, however small, towards changing a system steeped in old assumptions.

Referring to the double-diamond, in government people tend to focus on solution validation – bringing designers in very late in the delivery process.

People don’t trust the government, the robodebt debacle demonstrated that the measures applied in government can be disconnected from the impact on the humans they affect. People were placed in extreme stress, but the savings made were praised.

At the ATO, Kate’s team was tasked with….. everything. Improve anything in ATO Ecosystem. Which is so big people pretty much didn’t know the full breadth of organisations or the number of people involved. They grew from two people to being a reasonably large cross-disciplinary team.

They still had the problem of being invited to give input on projects, sometimes just days before the planned release date. There were some that were so far off course the project needed to be stopped.

In practice this meant there were opportunities to talk about better processes; and to assist and mentor people on lean and agile processes. It was a challenge just to get people to accept the idea that early failure was not bad failure, it was part of an exploratory process.

Data and evidence really worked wherever it was available, particularly when they had the chance to take people through the process that created the evidence.

Understand your stakeholder’s needs. Treat it like a form of user research – what are they dealing with? What issues do they face? What’s the political situation for them? It’s realistic and useful to spend time on this.

The ATO is aware it needs to build trust with Australians; and is starting to set internal KPIs around fostering “willing participation” from its users.

Big changes can also be quite tricky and have unintended effects – halving the time something takes can put jobs at risk. What’s intended as a good thing can still create a bad result for some people. Or simply “going paperless” without a realistic solution for how people would get the form they used to pick up from a post office.

Internally UX helped to convince people to change, or to explain a problem in a way that motivates action. They were able to show a comparative evaluation of a portal against more-successful projects.

Challenge. Use evidence. Make Change. Do good.

Chris Stonestreet – Outsourcing design. The good, bad and ugly

Chris started out in print design before moving into frontend development, then a few years ago gravitated to human-centred design and currently works at NIB. Recently he was lucky enough to start the DesignOps team there as well.

But he’s here to talk about experiences outsourcing design; breaking it into individual designers, then medium organisations and large enterprises.

Sharing a blog post where someone jokes that they’ve outsourced sleep, exercise and eating. The point is to highlight the odd way people think about the impact of outsourcing.

A wolf in sheep’s clothing… people often sell one title and do another, both ways in the process (either to get the contract, or to attract a contractor).


  • Balance your team – contract designers who balance the people you do have
  • Upskill your current team – get them pair designing with a contractor
  • Request to meet – before you engage, sit down and talk to people

The kool-aid effect: lots of places are latching onto human-centred design as a sales or success strategy. But many are just having a workshop with internal people; then suddenly a full design turns up and gets shipped. People might feel great, but no user was actually involved in the process. This can still happen when outsourcing or bringing in contractors…

What can you do?

  • Call it out
  • Ask why there isn’t budget for user research
  • Document things that aren’t captured
  • Propose steps to get real testing happening
  • Advocate the right way

Are you in synch?

  • Communication is key
  • Define roles and responsibility
  • Partnerships – make sure teams are integrated, avoiding disconnected external outsourcing

Caveat – Chris only has second hand experience with large enterprise, but it’s important to look at.

link: designintechreport.wordpress.com

Large businesses are trying to use design more, they’re moving into areas like AI that need new kinds of design. Some buy expertise, some build it internally, others use a combination.

Talking to people in large enterprise, some themes emerged:

  • Less choice over projects (being restricted to one sector)
  • Designers diversify and take on more problem spaces
  • Culture (risk of losing the culture)
  • Less pressure to pitch

Take aways

  • integrated teams – make the contractor feel like they’re part of your team, treat them as one of your own
  • onboarding is critical – people need guidance, good docs and tooling to be productive quickly; set clear expectations
  • make sure you and your team are available to the people you contract – they’ll have questions; and you can take advantage of the power of pair design
  • continuous delivery – don’t give the impression that outsourced work is done with no more involvement


Andy Polaine – Design for the long term

I want to talk about our addiction to speed (not the drug). When computers were slow, we had moments to think.

But actually when Andy fired up an old MacOS 7 machine he was surprised to notice how snappy the interface felt. But there was no multitasking, if you had to wait for the computer or printer… you read a book.

Now we say things like “I’m really busy so things need to be faster.” We’re all just making ourselves and others busier. In that mode two things are lost – mindfulness and long-term thinking. Ten year, hundred year thinking.

The digital ephemera problem – we have a culture of free content, which also leads to it being ephemeral and therefor impermanent. It’s free, who cares? But even when we pay we still don’t really care – we get upset about paying $3 for an app we’ll use daily, while we buy a $5 cup of coffee.

Reference: blinkist – helps you read books fast, down to 15 minutes… so you have more time to read articles about time management and procrastination.

We are all guilty of this.

We shape our tools and thereafter they shape us. – J.M. Caulkin / attrib. Marshall McLuhan

The tools and methods we use represent mindset and intent. A calligraphic brush and chisel do not encourage a mindset of thrashing out some content. This is why Bootstrap websites all follow a particular pattern and it all starts to look the same.

Management culture is an artefact of the industrial revolution. Prior to that, you had artisans who would sit and make things and sell them directly to customers, learning what they liked before making the next thing.

After the industrial revolution the Taylorist approach took over. Artisans were replaced with people who just did one part of making the overall thing – putting a wheel on the car, not making a whole car. Suddenly we needed managers, someone who knew the big picture.

Designers need to evolve, there’s so much to know and keep up with. There’s a lot to know and a lot of new technology to understand.

In a longer context we can consider the way people talked about Flash allowing them to make things really fast. People were proud of cranking designs out fast… and it seemed appalling to Andy. Plus the new version of Flash had a thousand new methods and it seemed unattainable to keep up with it. Every time something new came out it felt like you had to start again.

All of this draws you away from honing your craft, you just constantly reset. All the while adding to the digital ephemera. But perhaps none of it matters?

Perhaps none it matters. Until it does. Zuckerberg, despite all his money, still looks tired and scared. “Look at the bags under his eyes!”

First world problems are still problems, and Kendall Jenner can’t help us.

The capability of technology is always over-estimated as a solution to things; and the difficulty of great design is always underestimated.

Most digital products aren’t products, they’re service ecosystems. Perhaps the only true product on your phone is the calculator. It doesn’t connect to anything.

Single touchpoints are contained within a multi-channel service, which lives inside a business ecosystem, which lives inside a PEST (political, economic, social, technological ecosystem).

Part of the job is to be able to move between these layers, to shift between the problems and challenges in each layer when it’s relevant.

Andy loves a good metaphor because it helps reset the mental model. So what can we learn from landscape architecture? Very large estates and manor homes took very long-term thinking. In the 1800s the people creating the garden would probably not live to see its mature state (as close to “done” as a grand garden can get). It took lots of care and attention to make sure it grew in the right ways to reach the original vision.

Imagine if it was like software? “We’ve shipped the garden, we’re done!”

Andy keeps a sketch of the Sydney Opera House on his desktop, to remind him it was once just an idea. The final design wasn’t even the first choice, but it had been created considering the different directions you might approach it. What would the experience be? When you walk up the stairs, there are no skyscrapers behind it.

The Opera House is also a building that faces outwards. Skyscrapers are egotistical, they face into themselves. But the Opera House faces you on each approach.

Jorn Utzon noted that “we made the working drawings just ahead of the actual construction”, so the construction and design actually influenced each other. The sketches would change as the construction continued.

Compare it with a carefully-planned difficult conversation: they rarely go to your mental plan.

The responsive approach to the Opera House is also part of the reason it was so far over budget; and Utzon didn’t even live to see it finished.

A lack of long-term thinking can be deadly, as it was in the Grenfell tower fire.

Compare that with the Voyager space probe, which still works 37 years after people were no longer able to touch it. They are firing the thrusters in tiny bursts with almost a day’s delay sending the signal.

Four principles and a metaphor (and a movie nobody recognises any more, making Andy feel old… students stay the same age but you just get older!)

  1. Design for long-term and worst-case scenarios
    1. NASA is great at this. They only get one shot at the real thing, even when they keep a reference replica on earth.
    2. What are you delivering to future generations? On a shorter scale, what are you handing off to people to build?
    3. Worst case… what if someone 3D prints a gun? The creators thought nobody would do that, but it was one of the first things people tried.
  2. Design for ecosystems, not products
    1. (story of introduced snails on an island destroying the natural ecosystem, destroying the life work of someone who had documented the native snails)
    2. The point here is that small things have huge ramifications.
  3. Balance ego with humility
    1. The life of the designer is to critique everything they see, but you need to be able to assert humility.
    2. The example of Ghandi may be cliched but he does embody the combination of humility and still the ego to demand big things.
  4. Go slow to go fast later
    1. There has to be time for reflection, analysis and training.
    2. Usain Bolt noted sleep was important for his body to “absorb his training”.

The four seasons of design…

Gardens need to be maintained according to the seasons. So perhaps we could think about design the same way.

  • Spring: synthesis, concepting, alpha, beta, pilots
  • Summer: launch, scale, manage
  • Autumn: harvest, reevaluate, prune, repair, stock for winter
  • Winter: stop, recover, take stock, research, dream, get ready for spring

When we move too fast, we lose winter. The moment to be mindful, to breathe.

So why not start here, in the winter moment? The cycle never ends. We may be thrown into any one of the seasons, they are forced upon you. But you can recognise them and know what to do when they arrive.

@apolaine | slides

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