The talk is in 11 parts. It uses history to frame why Normal is a problem and then examples from current practice to discuss possible futures.
Introduction with personal experience of working in research and design for accessible digital and physical products.
2) Inclusion and Diversity
Setting up the problem space by noting the failure to deepen inclusion and diversity in organisations and products.
Reframing the problem from ‘What do we do to be more Diverse?’ to ‘How do we stop being so Normal’?
4) History of Normality
A quick history lesson in 180 years of Normality (using Quetelet, Galton, Thorndike and Burt as key figures).
5) The bias and exclusion of Normal
Clearly stating that Normal, Normality and Norms are biases that exclude. We cannot enable diversity if our tools are biased.
6) The trap of Normal
Given the history, Normality is a trap that holds back organisations
Using acronym to give a clear example of the trap and recognising bias in existing research base. W.E.I.R.D. – White male, Educated, Industrialised, Rich, Democratic.
8) Post Normal Design
Shifting to broader solutions and how organisations are changing their attitudes to Normal and the growing importance of Divergence.
9) Divergence as resilience
Using example from UK government on Groupthink to show importance of supporting divergent opinions in analysis and decision making.
10) Diversity as strategy
Using examples from fashion industry on how lack of diversity creates strategic failures for businesses and how diversity is being used to enable strength.
11) Post Normal enabling new futures
Finishing up by showing that, though breaking the idea of Normal seems both strange and difficult, it is both essential and practical for long-term survival.
About the speakers
Alastair works with global brands, cutting-edge design studios and conferences helping people understand how to use ultra human centered design with new technologies to deliver value in emerging and existing markets, internationally .
With a background in Accessibility and inclusive design, he facilitates workshops, for all types of participant, on understanding how our individual senses and perception affect the use of new products and services from a human perspective. Helping staff understand more about themselves to enable them to work collaboratively developing complex and commerically viable products. He embeds skills into teams so they can make beautifully engineered products which create emotional and human connections to new users and customers.
Workshops and key note talks include global conferences like SxSW , UX Week , UX Lisbon and Generate as well as many smaller events in the EU, USA and Australia. His workshops are fun and informative with excellent feedback, leading to repeat visits to many conferences.
Hi, my name is Alastair Somerville. And this is a talk on personal design, getting to the new next. Most of my work is in accessibility, whether it be physical for museums or public spaces, or digital for apps and websites. And of course, one of the key concepts of accessibility is accessibility is for everyone. And the way that some people describe that is to use the word inclusion, which always seems to be a good word, and yet, it’s the start of one of those places where things start to go wrong. Because to speak of inclusion, you actually need to be able to speak of people not being you, you need to speak of people who aren’t part of the group that you are. Inclusion is othering. You have to have a sense of normal of what is standard, typical in order to have a sense that There are people who are not part of that group. And this is where I started with my problems with normal. When talking about inclusion and talking about accessibility, a lot of people talk about edge cases. And they talk about edge cases and these people who are away from the center, away from the middle. And I sometimes think about the tree and how you have all these branches, all these twigs, all these leaves, at the ends of the branches. And how these of you does different. And yet, there may be another way of talking about this. And then maybe another way of thinking about this, that when we talk about edge cases, we doubt the divergence we doubt the way in which these people are living their lives because isn’t typical, because a decent way that we live our lives.
We have this thing where we consider normality as being the roots, the center, the core At the heart of things, and that other people live at the edges, they live at the end of the branches, and that our sense of normality is right. And their sense of reality is somehow divergent and doubtful, that needs to be tested and queried.
Though what if normal is the problem? What if normal is the root problem in the design? Over the last few years, I’ve been doing a lot of reading as well as a lot of research and these books are quite helpful. So do not economics by cake raw worth is helpful if you’re looking at different ways of thinking about business and economics. Invisible women is very good if you’re looking at ways of talking about how 50% of the population is just ignored by design. Superior is very useful if you’re looking at the history of race science, particularly eugenics and how it never goes away.
It keeps coming back. As we know now, the end of average is drawing out of a lot of disability and Economic Studies, but it’s useful for different ways of thinking about statistical work and different ways of thinking about the organization of work. And normality. A critical genealogy is a more academic book, but it’s very useful if you want to go into depth about disability studies and disability history to understand how we got to know the key problem we’re talking about normal and crystallizing normal and talking about it in offices or with other stakeholders is of course that normal is very, very normal. People find it difficult to understand why it’s a problem because It is the reality that seems to be presented to all of us.
But there are two big challenges. And this talk is about how we both challenge those ideas of normal, and actually have some way of talking about why it is a problem to people who can’t even perceive it as a problem. Fundamentally, normal is biased.
And it’s biased to a very, very specific group of people. And we’ll talk about them later. And secondly, convergence, the idea of convergence in design and processes is a trap. So, let us talk normal. In order to understand how we got to here. It’s good to understand how the history works. And so I’m going to take you through the history of normal to understand how we created the problem that envelops us and which we don’t quite pereceive. Now there have been about 180 years of normal. And it’s useful to us for people to be able to understand that history and how the history creates a tightening of the sense of normal and the tightening of the sense of who design is for. We’re going to be using these four people kettle a golden Thorndike and Bert.
Now catala is Belgian mathematician and he was working in Edinburgh on understanding averages, and particularly he did some work with Scottish Army troops to understand their chest size measurements. And he got to an average, but in the average he also discovered normal curve, he discovered that there was this curve to the left and curve to the right of measurements. And he understood and he discovered the idea of the normal curve. He also discovered the body mass index. But the idea of normal the idea that average works around a normal curve comes out of his work. He created some of the fundamental tools in which the way in which we think about data, and the collection of data,now gotten comes later on and gotten is very, very particularly of a Victorian gentleman concept of a scientist interested in psychology, but also a man very much caught up in the new ideas, Darwinian ideas of eugenics, the idea that humanity could be made to be better.
And in that he took the idea of the normal curve, the idea of statistics and add it on 12 point system when he was analyzing collecting data on humans, which went from those people who were excellent at one end to those people who were in the seals, or the other end. So, already you’re seeing the normal curve beginning to become a symbol of oppression for some people. Because you are beginning to see that there is this idea that you are thinking about a weight from one end to the other, between those who are deserving and those who are undeserving. Now, Thorndike is an American educationalist. End of the 19th century beginning of the 20th century, who is interested in a problem Which a lot of the Industrial Revolution factories had, and the managers of these factories had, which is how do you find the new managers? How do you find the people who should run the factories? How do you use an education system to sort the quality people who should run factories out from the not quality people, those people who just really be just employees. And this is the thing where, taking on the ideas of gotten that one can go for a scale attacks taxonomy from excellent down to embecile. You can also therefore, create systems, exam systems, measurement systems, data collection systems, going back to Kepler, that are actually to try and find those people who are quality in order to then provide more to them, so that they can come the managers of future. One is using the system. One is using the idea of normality in order to be able to find high quality people in order to enable them to be educated, to be employed to be salaried, better than others because they deserve it. And finally, what ends up with Burt, who’s in 1920s 1930s, and also post World War Two, and Bert, who used to play in Golden’s garden, when he was a child, and also, like cold was in charge of the eugenics society in the UK was interested in finding genetic bases for why people are excellent Why they are high quality. And he did a lot of work on twins, particularly twins who had separated such that one twin was adopted by a family who didn’t have a good quality of life didn’t have privilege and power. And the other did in order to be able to prove that their genetic quality, the fact that they were better than others in their blood in their DNA, which hadn’t been invented at that point was true.
And he did a lot of research and he did prove that there was a genetic basis for intelligence. However, this work, which actually underlies a lot of how the way in which British education and also American education is organized even now, this work was criticized by Harvard, Harvard University did actually ask him to provide data because it seemed odd is research And they requested some of the proof of the data. And he said he couldn’t because it was held by his researchers, too. And so Harvard University said, well, could we speak to your researchers? And he said, No. And they said, why not? And he said, because they’ve emigrated. And they said, well, to where we can contact them. And he said, I have no idea. And this came down to the fact that birth research, all of this research on the genetic basis of intelligence, intelligence embedded in people who were better than others, because they were born better, was lies. It was fake. And yet, this is the research which huge amounts of the way in which we think about society and the way which we think about education is based on. So just using these four people, these four examples, one can go through a history of norm. One goes from average, to ranked to quality to better from an idea of we use collection of data to understand averages, to an idea that we use the idea of averages and normal curves, to think about those who are better, and those who are worse, to an idea that we use quality to think only of those people who are better quality so that we can apply resources to them. And finally, an idea of better that actually those quality people are quality because they are genetically historically better than others. And this plays to inflation. architecture in a certain way. Because of course, average looks at data collection ranked looks at the way you can think about taxonomies. Quality, thinks about the ontology ways of being, ways of thinking about what it is to be human, what it is to describe humans. And finally, the idea that you can actually use all of this data taxonomy ontology, to actually create post hoc fallacious arguments that prove a point, which isn’t actually in the data. But it’s actually in the way in which you describe the data. The tools we use, the tools we use for data collection and data analysis, the ways in which we think about taxonomy and ontology are dirty because they Made dirty by hundreds of years of people using it for a very specific purpose to prove a very specific point. For a very specific audience. The tools we use are not necessarily bad. statistical data collection isn’t necessarily bad. Comparing groups of people isn’t necessarily bad. And yet the results can be. We see this in big data, we see this in AI. And also what one sees is what could almost be described as taxonomic momentum. The idea that the way in which people have historically described groups of people, the way in which we use race to describe people the way in which we use gender actually creates a momentum and wait. Which Russia says in Russia, us all into a way of Describing the data we collect now, we use historic taxonomies and historic taxonomies push us into coming up with arguments
which are not necessarily beneficial to any of us.What particularly Burton golden, we’re looking to do is to exclude people. Their concept of normal was an exclusive one. They wanted only a certain group of people to have the benefits of society. The rest can be sorted and discarded. We designed for a weird world. And where does the acronym actually it comes out of social research, where it was beginning to be discovered that there was a problem. In all the social psychology research, all the sociology research in the anthropology research And the problem was this. The people that who were involved in the research, the test subjects were very specific group of people. And they were this white, male, educated, industrialized, rich, democratic. The people who were asked
about their ideas, all of these tests, all of these social psychology,research that you see about the behavior of humans, the way in which humans think all of that is terrifying the bias to a very specific group of people, the people who were the universities. And what you find, historically is course, that these were white men who were well educated in more Rich democratic societies. They were in America. They were in Britain, they were in Europe. These are the people were available, because they were in the right place at the right time to be part of the research. So the research on what it is to be human
is biased and is terrifyingly biased to this group. So how weird are things and how weird is the research that we try to use to prove points about design, behavioral design, particularly? So the Journal of Personality and Social Psychology is the key journal for social psychology research, almost everything which you know, which is the big stuff from the 1950s 60s and 70s will have been in this journal. So, percentage witness how much of this Research do you think is white male, educated, industrialized, rich, democratic participants? I’ll just give you a couple of seconds to think. 96% weird. So the vast, vast majority of social psychology research is not describing humanity. It is not describing the way in which human beings across the world think, or behave. So what do we do?
How do we move forward from this period where we have normal, dirty tools? biased research? I mean, there are many, many options. There are the discussions in design ethics, there are data ethics discussions, you could look at recruitments you could look at user research and usability. I’m just going to talk about a few months from my viewpoint but I think Before you talk about what can we do, you need to think about one crucial point. And it’s this if you stop, and stopping and observing is hugely important in this, if you stop and look at the big picture, you realize something which is incredibly important. This background, which you’ve been watching for last few minutes, the little white rectangle in the corner represents white men. The huge area of think the majority of the slide represents the rest of humanity. All of the way in which we design and all the way in which we think about business plans, business models, is based around the white rectangle. It’s based around the idea of how do we design and create businesses to service the needs of white men. But of course, what this means if we think about post normal is that we’re actually talking about a vast, vast space of opportunity.
The opportunity space that we now have, when we think about going past normal, is extraordinary. And this is the key point, the crucial point. To lose normal is to gain a vast territory. Now, when you look at the way in which businesses think about diversity, and normality, you see terrible problems, particularly in fashion. Dolce and Gabbana, and Burberry, both had huge problems with creating products. Which were deeply offensive because they were racist both times. And this comes to an idea of post normal which is important that diversity is strategic strength. Diversity is strategy by having more diversity. By having more people with different experiences. You actually are able to create products and services which are better, which will sell better to more people in more places. Diversity isn’t a nice to have. Diversity is a necessary element of any company’s work. Because otherwise they will fail. They will fail through terrible public relations disasters, they will fail because their product does not appeal to the vast vast group of humanity. The second problem with normal is of course, convergence. Now, convergence is one of those things which everyone thinks is hugely beneficial to come to agreement to come to a single point to some come to the agreement of the single product seems a good idea. And of course, you see this in the design tools and the design processes. They value convergence. If you look at all the design tools, if you think of all the design thinking, it all values convergence. It has moments of divergence, it has moments where other possibilities are discussed. But the core is always to drive towards convergence, like normal, and it’s tax on momentum. Most design tools and processes have a momentum come towards convergence towards agreement. And this does not necessarily help. Because what you see is groupthink. And groupthink is again, not a good idea in a world of increasing diversity. Now in the UK, after the Iraq War, there was what was known as the Chilcott report, which was a study of how the hell did we end up in a completely pointless war, wasting thousands of lives killing hundreds of thousands of innocent people, wasting millions of pounds. And one of the points which came out of the Chilcott report, which was interesting was that there was a problem with group thing. That there was a problem that the war was created by groups of people who were the same who thought the same have the same background saw the same data, and therefore, we’re converging to an idea. That would be terrible. And that’s the problem. convergent thinking is the problem. And this is why you’ll see in the civil service and the way in which it trains and recruits now is actually to try and stop this. They do not want convergent thinking they do not want group thing. They want diversity and they want divergence. Because divergence is resilience. If you want to create an organization that is capable of dealing with massive radical changes in environment, economic, social, ecological, then divergence is the way you deal with it. Because divergence descent and descent based systems enable To be able to deal with possibilities that specific groups of people with specific backgrounds can’t. Normal is a future that cannot work. It is too brittle. It’s too small. It’s that tiny rectangle. It can’t cope with the vast, vast rectangle, the huge space that we are in now. Post normal is the possibility of many futures that can work. The diversity in a divergence of futures. I keep seeing people talking about new normals. And it worries me because the new normal is a future anchored because of the word normal to the past. A new normal remains trapped in the ideas Normal is good. That if we just had a normal, which was slightly different, was slightly more inclusive, allowed a few of those people, but probably not those people into it, then things would be better. Normal is in itself. poisonous. New Normal is poisonous because you will alwayshave that anchor to the past. So in general, I talk now of the new now and the new next, because that’s the way in which we can talk about what is diverse and divergent. How do we actually create organizations which are capable, which are actually fundamentally based on diversity and divergence to finish normally is biased. Historically normal is biased Towards white men, their needs supporting their privilege supporting their power. So number one, clean your tools, the tools we use, and as I say, in AI machine learning big data. The problem is the tools look innocent, they look clean, but they are not. You must must clean your tools. Look at the datasets, look at the data collection systems look at the data analysis, because that is contaminated. Secondly, convergence is a trap. The idea that we have to converge to a single idea that we need to eliminate divergence, eliminate descent is a problem. So think about stopping and observing There’s a book called how Not to get lost. It talks about the importance of stopping and looking around, because people who get lost, just keep moving. They keep moving. Because they hope that by moving they will find where they are. But they don’t they become more and more lost. And this again, is Rob, like the TAC Sonic momentum. People want to keep going, they want to keep moving, because they think that’s how they will discover where they are and what to do next. But they don’t they just get more lost. People wonder why bro tech keeps being created. biotech exists because there is this momentum in normal to create it. The tools and processes created. We need to spend more time stopping and watching for it. That’s the way in which you start Stop this bias. And that comes back to the fundamental point. You keep questioning, we need to keep questioning things. And specifically, we need to keep questioning normal. When people say this is the normal thing to do, this is the typical thing to do. That is the point not to say, Yes, that sounds fine. That is the point at which you say, we need to think about this deeper. Normal, creates its own momentum to create products and services that benefit a tiny group of people. And we need to stop it. If you’re wanting any more information, then post normal. Co, UK. And if you want to talk to me about any of the subjects raised in this talk, then actually acuity underscore design. Thank you.
Transcribed by https://otter.ai