Biology seems the next natural step for computing. It’s inevitable that we’ll try to model computers on biological systems. Today I followed a link from Rachel Armstrong to The BioBricks Foundation. In their own words:

“Using BioBrick™ standard biological parts, a synthetic biologist or biological engineer can already, to some extent, program living organisms in the same way a computer scientist can program a computer.”

It’s not quite genetic engineering for casual dilettantes, but you can order your own assembly kit for $235.00. From the sound of it you need an advanced degree in biology to use it.

So, Frankie Stein’s monster has been on my mind mainly because I’m taking Affective Interaction as a module option next term, and I’m reading (in preparation) a book called Affective Computing. Frankie’s monster, Monnie, isn’t a computer, but she seems to symbolise the way the field is going.

Affective Computing

This book introduces the bold idea that computers should have feelings. This is contentious in a field that has a reputation for cool, detached rationality and logic. The last thing you’d want your computer to do is have a tearful sulk after it corrupts a file, right? But what if it responded to your irritation by “feeling bad”, and learning to avoid future mistakes?

Picard makes a convincing case for designing computers that have empathy and evolutionary qualities.

One thing Picard mentions is the little smiling Mac icon that appears when you boot your Mac. A person might look at that and think (either consciously or unconsciously) “The computer is happy because I’m fulfilling its goal of me using it.”

This is an act of projection: of course my Mac doesn’t have feelings or emotional awareness. If my Mac actually had moods, emotions, and emotional awareness, it would drastically change how I interact with it. I’m fairly certain I wouldn’t like it.

Would computers with high emotional intelligence still be good? Would they still execute programs on command? Would they fall in love with its user? Would they rebel? If you dropped it by mistake, would it decide to punish its user by deleting files? (Etc.)

To break from the trend of grad studies posts, I want to recap the story of one of my favourite books. It is actually not unrelated to my studies, and I’ll explain why in my next post.

The Monster Garden (Vivien Alcock)

Amazon UK. I first read this book when I was eight or nine, a few years before I got a computer. In the days before I got a computer I used to read a lot of books. The story remained in my head and heart for years, and I love it; possibly because I empathise with Frankie: scientist family, geeky child. No test tube monsters though. Unfortunately…

The Monster Garden is about Frankie Stein, the alienated daughter of a genetic engineer. She is teased at school for having an unfortunate name, and because her father works in a secret lab. There are rumours that her father works on contentious  genetic engineering projects like germ warfare. Although he says he works for the good of mankind, Frankie and her brother are suspicious.

In order to find out what their father does, Frankie’s brother steals a test tube from the laboratory. They split the contents of the test tube between them.

Frankie takes her portion away on a glass slide, as her brother would not give her a petrie dish (“my monster would have to rough it”). Her brother also refuses to give her blood agar to feed the living cells, so Frankie uses her own blood. She leaves the glass slide on the windowsill.

Overnight, there is a terrific thunderstorm. Frankie wakes up to find bites taken out of a pot plant, and the culprit: a small monster that’s grown out of the cells on the slide.

The benevolent monster, Monnie, drinks with its foot, whistles, and brings Frankie small gifts. Frankie ends up loving the weird monster, in spite of its strangeness.

Monnie’s description:

I laughed. I expect I was hysterical. Or mad. I can’t think of any other reason why I did not scream and run from the room, like any sane person would have done. I just sat on my bed and watched it.

It was playing now. It sat in the upside-down lid as if in a boat, and rocked backward and forward until the lid tilted too far and tumbled it onto the floor. It seemed to enjoy this and did it several times.

Then it looked at me. Its eyes were very round and a clear, light crimson. Quite a pretty colour, really. It began twisting its slit of a mouth in a most ridiculous manner. Now it would bend the corners down until it looked like a croquet hoop; now into a capital U. Once it even managed to twist it into a figure eight. I couldn’t help laughing at it. It did not seem to know what a mouth was for. It never opened it, not once. Perhaps it was not a proper mouth at all.

Feels a bit foreboding, to be honest. It took me a while to fall into a pattern of productive working and now I’m optimally suited to self-directed work. Except that reading week is over. I can haz another week, pls?

I have a handle on my coursework papers and managed to do plenty of relevant reading. I’m bemused by Usability Evaluation Methods generally: it’s a very different approach to intuition and creativity that guided my designs at Reading University. It’s very scientific. Then again, I’m very absorbed by these ideas of, for example, the differences and misfits between user concepts and system features. I’m actually finding HCI very deeply compelling.

I’m also intrigued by think-aloud testing and the level of attention academics give to spoken narratives. It reminds me of analysing stream of consciousness style modernist texts: Beckett, Joyce, Woolf. Verbal protocol analysis and grounded theory are examples of this kind of close analysis. These ideas are both borrowed from psychology.

As well as being academic, it’s mucky. Talking to users is messy, and both verbal protocol analysis and grounded theory involve, first of all, gathering data and talking to real people. Second, you must roll around in that data and try to make sense of it.

Tomorrow is exciting as there will be presentations for each of the option modules for next term. I’m currently leaning on something to do with the emotional aspect of design and something to do with group-working systems.

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In other news: I’m amazed by this plug design. Mind-blowingly brilliant.

Last night I went to toast Laika, the first dog in space with the brilliant people at BERG. Old Street definitely has an interesting crowd and I’m glad I’m here, even if living in Shoreditch was pure chance. Apart from the occasional outing, I’m not really living the life of a stereotypical student and waking up in a pile of sick every day. I’m actually working quite hard. The pace of the course intensified in the last few weeks, which goes towards explaining the paucity of updates.

Next week is reading week. Translation: next week is a week of no lectures and no labs. Just catching up on papers and core texts. UCLIC places great emphasis on reading, and we have been instructed to learn how to read fast and to always have something on the go. I have two pieces of coursework to do for Physical Ergonomics and Usability Evaluation Methods, so I suspect my reading will focus on that. I’m also working on a project for Design Practice, which is going to focus on tempting commuters to modify their routines.

I’m enjoying the course. It is really making me think about design from the perspective of the user. I’ve been aware of user-centred design for a while, as it’s something I learned about as an undergraduate; but I think user-centred text design is a bit different from three-dimensional products, services, and systems. Physical ergonomics in particular forces you to focus on the user in detail, as the user has got to be able to comfortably turn a handle, push a door, and walk through the door frame. Not just a single user, but the widest possible range of users. You can’t really get deeper into user-centred design than anthropometry and ergonomics.

So, the study of people and physical things is changing the way I think about software. I’m learning tonnes! But I also have a growing awareness of: a) how much I don’t know; b) the pitfalls of academic tunnel-vision. I’m reminded of Jorge Cham’s graph (PhD Comics):