Have you ever gotten into one of those silly arguments about the colour of something? You know where you’re sure that a t-shirt is red, while your friend is 100% sure its redish yellow. Frustrating isn’t it.

Strange as it is, both of you can be utterly right.

You both “see” a slightly different colour because of individual differences in physiology. The receptors in eyes that help convert light into colour often have slightly different sensitivities between people. For most people the differences are so slight they’re not usually noticed, but people with colour blindness experience a world where colours appear very different. Go here for details about the Ishihara colour plate image, which is used in testing whether people are colour blind.

There are thought to be women who are the opposite of colour blind, they are tetrachromats who are able to see more colours than most people (who are usually trichromats). Damn Interesting has a good introductory article about tetrachromats A Life More Colorful, and the Pittsburgh Post-Gazette has a good article with a little more science background, Some women may see 100 million colors, thanks to their genes.

Previously I’ve touched upon individual differences in genetics for Personalised Medicine and the Psychology of Individual Differences.

There are many other kinds of subtle physiological differences, such as variations in taste receptors and densities on the human tongue. Here’s an introductory article about taste blindness.

Individual differences in physiology can be measured. These measures can be used to shape the design of objects. For example measures of your taste receptors could be used to automatically adapt a collection of cooking recipes to enhance the flavour for your tongue. Or TVs could have inbuilt smarts that adapt football game colours so a person with red-green colour blindness can more easily see their favourite football team. No more struggling to see a team wearing a red outfit running around on a green pitch, or a red snooker ball on a green table.

If the above is to become possible then self-mallable / re-shapable objects that adapt to the individual physiology of users need:
1) measures of user physiology
2) predictive models of the impact due to physiological differences, i.e. if an object is adapting to a user how does it know an adaption has a positive or negative effect?

This builds on implications from When Toothbrushes Mate: Form & Function DNA. Malleable objects and artifacts need to be:
1) self-describing
2) user describing (predicting the impact on user experiences due to physiological differences).

To those of you who voted in the poll about HCI tutorials, thank you. To those who didn’t bother (there’s still time) I mutter a future curse: May all your solar panels develop self-awareness and go on strike.

Anyhow, previously I touched upon the idea of objects and tools that enable us to more easily create physical objects (How To Make (almost) Anything), or allow us to more easily reshape existing objects (Shape A Seat, aka Don’t Forget Me). In both cases we do the creating and reshaping, we give objects their physical structure, we are the shapers.

How can the physical structure of an object or artifact reshape itself?

Imagine while drinking a coffee you rush out the door to catch a bus. As you run to the bus stop the coffee cup changes into a sealed heat preserving flat container that easily slips into your back pocket. No more splashing coffee everywhere and your coffee is still hot. Then while standing in the packed bus the flat coffee container runs a straw from your pocket to your mouth so you can continue drinking coffee.

If a smart self-reshaping cup is going to be possible we need malleable materials that can change shape anytime we want. Or even better, they change shape when they realise that’d make life easier, e.g. your soup spoon turns into a straw so you can suck up the last drops from a bowl of soup. These kinds of self-reshaping and self-assembling materials are commonly envisioned as the result of nanotechnology research and development.

Now have a look at this video showing a shaping-shifting robot forming from a magnetic swarm (New Scientist article). The research into programmable material shown in the video is part of Carnegie Mellon and Intel’s Claytronics project. Neat ain’t it – yep, its still a young research area but online you can find a bucket load of research into self-reconfiguring modular robots. If the robots where made small enough then millions of them working together could become self-reshaping materials.

Xerox PARC’s Lattice is another example of interesting early stage research into modular robots for smart materials (esp. Proteo). If you have a chance play around with the Proteo RDSim (Rhombic Dodecahedron Self-Reconfiguration Simulator). The researchers who created the simulator were trying out different techniques for enabling lots of small robots to form themselves into different shapes.

To play with the simulator your web browser needs to run Java. When the simulator loads click on “New Goal”, then select “Disk”, set the Radius to 4, click “OK”, then click “Start Run”. In the main area you’ll see a flat disk form out of the white cubes. The white wireframe is the target shape the cubes are to self-organise into. If you’re feeling brave you can new try another “New Goal” of a Cup, try with a Radius of 6.

Another more recent simulator, which I haven’t tried yet, is DPRSim: the Dynamic Physical Rendering Simulator from Intel Research. DPRSim is a platform on which Researchers can develop and test new distributed algorithms for large ensembles of Catoms. Catoms are tiny robots with no moving parts that have internal computation and magnetic actuation.

Finally, if you want a quick review of previous modular robot research have a read of the review paper Design of a Modular Self-Reconfigurable Robot.

In the above photo you can see an example where a streak of lightening can be seen on a model’s t-shirt when the t-shirt is viewed via a mobile phone camera. The lightening is printed on her t-shirt but the “colours” (wavelengths of light) used for printing aren’t perceivable by the human eye but are picked up by digital cameras. There’s more details about the technology here.

There’s a number of usage suggestions for the techology on the kameraflage website. You could imagine extending their idea but without digital cameras. Imagine multiple people sitting around using a shared surface computer (such as a DiamondTouch). Each person is wearing glasses with slightly different colour tints, so each person would be able to view a “personal” image on the surface that the other users won’t see. Or you’re going to the cinema and depending on which glasses you wear the film has a different age rating because different parts of the film are “cleaned up” for younger age groups. Alternatively wear these glasses during the film and get in for cheaper because you’ll see inserted advertisements on-screen?

During the talk he discusses the implications of some experiments which demonstrate that giving people choice doesn’t necessarily lead to increased satisfaction, and can even have the opposite effect. More choice may impact upon the formation of Synthetic Happiness.

In one (free-choice paradigm) experiment people were given a choice of six Monet prints. They had to rank the prints according to desirability. Then they were told they could have one of prints ranked third or fourth. A few weeks later the same people were asked to re-rank the same set of prints. Lo and behold the print they had was ranked higher than the one they originally preferred most!

They were happier with what they had than what they didn’t have. Some follow on research established that if there was the possibility they could change their choice they would be less inclined to be happy with what they had.

In an Introduction to Cognitive Dissonance there’s a more detailed description of the first free-choice paradigm experiment run by J.W. Brehm in 1956. If you’re interested you could have a look at the related “spreading of alternatives”.

I wonder what are the implications of a malleable world for the generation of synthetic happiness? Will people be more dissatisfied because they constantly have a choice about altering the physical and functional form of their objects (e.g. phones, door handles, etc) and tools?

In the Wired article “Where’s My Personalized Medicine?” you can read more about existing methods that enable personalisation of drugs. In the longer term it should be feasible to create drugs that are optimally adapted based on individual differences in genetic makeup (Pharmacogenetics).

Most of the research and projects I’ve mentioned so far have tended to enable the user to have more freedom by giving them more control. The user is in charge of personalising and adapting.

In personalised medicines we find an example where it probably isn’t feasible or acceptable to let the user design and adapt the (non-recreational) drugs. Are there certain objects that should be adaptive to the user without letting the user explicitly adapt them? Are there certain things that should be fixed in form and function? If so what are the characteristics of adaptive (that which adapts to the user) but not adaptable (that which the user can alter) objects?

On a separate but related point: I wonder what home medicine cabinets will be like in the future? Will they have a spit here slot which when used causes the cabinet to quickly sequence your genome and then pop out some individualised pills? Or could it be far more subtle where when you use the restroom the toilet paper gets automatically infused with personalised medicines? Wipe your way to a healthy lifestyle!

A few years ago I came across “User analysis in HCI: the historical lesson from individual differences research” by Andrew Dillon and Charles Watson, which was published in 1996 in the International Journal of Human-Computer Studies 45, 6, pp 619-637. The paper reviews key findings in 100+ years of Differential Psychology (Individual Differences) while discussing the relevance of individual differences research to Human-Computer Interaction.

A quote I particularly like is “One implication of all these analyses and re-analyses is that measures of ability can account for approximately 25% of variance in performance. They are not unduly limited by situation specificity and thus can be used for most selection applications with appropriate caution. ”

For me this paper raises lots of interesting questions, esp. when thinking about cognitive & physiological individual differences applied to users creating and shaping their interfaces and their tools. A few questions that spring to mind are:
1) Will users tend to adopt and create designs that cater to their individual differences?
2) How can we help users to know their individual differences, to know their strenghts and weakness’?
3) Can we guide users towards creating designs that take advantage of their individual differences?

In an attempt to tackle these kinds of questions I’ve spent the last few years focusing in on understanding individual differences in the human eye while trying to tease out how those differences could guide the creation of individual centered information visualisations.