Artist seeks Scientist Newsletter 2.

Meet the artist: Heike Introduction Hi there, I am a research technician and budding street-painter. I am fascinated by visual perception and would love to understand how the brain works, how do we respond to beauty.

Artist or scientist?

Leave it to others to decide

Research interests?

Nature of light, photosynthesis, Arthur Eddington, chemistry of pigments...and anything that unlocks the secrets of visual perception...

Looking for…

Inspiration, interesting conversations....who knows what will come out of it...

Dear all,

I hope that you all had a fantastic summer and are

feeling refreshed and ready for more meetups.

Whaaat?? You don’t remember Artist seeks Scientist?

Well here’s a reminder with contributions from group

members. Many thanks to Heike, Paul and Alex Jean.

I hope that you enjoy it, and that you feel inspired to

contribute to the next one, or at least to join us in our

upcoming events, or online discussions.

Also please feel free to suggest events and activities

(Juliet, you are a gem for suggesting the Big Ideas

Debate), and of course I am happy to receive feedback,

criticism and comments.

Our next meetup will be October 6th at GV Art. I hope

to see many of you there

Houda

What we got up to before the summer break*

*by popularity

Biologically inspired computing By Paul Coker Soon after the first electronic computers became available to the academic world,

researchers started to use biological analogies in their computer programmes. As early as

the 1940s, John von Neumann was working on Cellular Automata. He worked to mimic the

way a single cell could multiply itself and form various useful structures. As computing

power increased, other researchers were able to create real time life-like behaviours in such

systems. A notable example being Conway’s ‘The game of life’, that showed how a set of

simple rules could produce life-like behaviours in a computer.

The field, named Artificial Life by Langton in 1986, started to distinguish itself from AI research.

A-life researchers started to look to more complex forms of life for inspiration. This often

started with known problem solving systems, such as ants, bees, birds. They wanted to

encode in a computer various, relatively simple behaviours observed in nature, such as the

way an ant uses pheromones to lead others to food, the way a beehive is organised, or how

herding and flocking behaviours are advantageous. This kind of work may also have been

driven by the need to produce knowledge with useful outcomes. Just being able to mimic

biological behaviour, for some, was not enough.

Researchers working with virtual ants started to solve complex water and telecoms routing

problems. Others using flocking simulations were able to handle and coordinate millions of

pieces of data. Soon these techniques started to migrate from being purely university-

based research to becoming implemented systems in the business world. Satnav routing

systems were created, online data searching became available, and computer games started

to adapt to an individual player.

At the same time, other researchers were trying to copy biology at the molecular level by

creating some form of gene in a computer. They would use all the known biological

mechanisms that drive genetic evolution, and convert it to suit digital genes. Some

mathematicians saw the use of electronic evolution merely as another space-exploring

algorithm. Others saw it as a way to find unique solutions that were not immediately

obvious. Solutions to real world problems such as ‘The multi-dimensional travelling

salesman problem’, ‘network routing’, ‘work flow and bottlenecks’, ‘gaming strategies’,

were being investigated using genetic algorithms.

However, the two main problems of employing genetic algorithms in real-world situations

are firstly mapping the problem’s parameters to a gene-type encoding. The second and

often more complex problem is creating a way to evaluate the various gene- based solutions

to determine which should be used. Promising genes are then allowed to ‘mate’ by code

swapping with other high-scoring solutions. The offspring are then tested and the process

continues. Thus a random, high-fitness controlled walk occurs through the problem space.

By way of a very simple example, take the travelling salesperson problem. He/she has to

visit, say, six cities in the shortest time possible. The travel time is known between all cities

and so the optimal route needs to be found. The bases of a gene could be encoded to

represent the cities. The order of the bases then represents the route encoded in that gene.

After randomly producing, say, 100 genes, the time score of each possible solution can

easily be calculated. The top 50% solutions are retained and allowed to mate, swapping

bases with other genes to form new routing options. Random mutations are also

introduced. These new, baby, solutions are then tested. This process continues until a near

optimal solution is achieved. Bear in mind that this illustrative problem is very simple, and

could be more easily solved by writing a few loops of code and checking all the possible

routing combinations until the best, quickest route is found. However, this number

crunching approach stops being useful as the dimensions of the problem increase. Imagine

that the salesperson must also visit certain clients on certain days, or that hotels cost more

to use on one day than another, or that fuel charges must be factored in. Then apply that to

a one million-destinations problem. If each possible solution takes one second to evaluate,

the number crunching approach becomes unworkable. Instead, a gene-based search will

allow a near-optimal solution to be found within a reasonable amount of time.

Over the last 15 years, artificial life solutions have become accepted and their use has

grown. Often the main problem faced is the difficulty of explaining why a particular result is

the best option. Unlike a purely human-derived solution, it is often impossible to work out

exactly what the evolved solution is doing. Why did it take one non-obvious course mid-

route? This is especially true if the solution seems far beyond the accepted norms for such

problems. This has delayed the uptake of many systems in the real world. Alternatively,

proposed solutions are just used as starting points for human experts to explore the

problem and come up with a considered and more explainable solution. This human need

to know how something works may be the controlling factor for the future growth of such

techniques.

As the power of computing grows, complex biological behaviour will be readily simulated in

real time. Real world versions of ‘sim-life’ could allow us to explore natural systems, to

foresee outcomes from current behaviours. Similarly, work on the future effects of climate

change may bring more meaningful conclusions; the spread of new viruses may be better

understood. The extinction or overpopulation of a species could be predicted. Robots could

start to develop more life-like behaviours…

For me there is also a beauty in this form of research. It can be an art-form in its own right.

The intricate patterns in ‘The game of life’, the developing patterns of behaviour in a

simulation, colours changing as grass gives way to trees, the biological expansions and

crashes caused by slight tweaks in the parameters, emerging flocks of data pitching one way

then another as the data sets change, fractal-like spirals replicating on the screen as virtual

bacteria interact, each giving an insight into the natural beauty that surrounds us.

The directions that this form of research can take are vast. It will be interesting to see where

they take us in the fast approaching future.

Interesting websites to visit for more information:

http://people.reed.edu/~mab/publications/papers/BedauTICS03.pdf (Good

detailed overview)

http://tuvalu.santafe.edu/projects/echo/ (A nice simulation tool to play

around with)

http://en.wikipedia.org/wiki/Artificial_life

http://en.wikipedia.org/wiki/Cellular_automaton

Individual Democracy By Alex Jean

Individual Democracy [ID] is a form of Direct Democracy, structured around electronic

internet voting, where the citizenry act as the executive, and the heads of the bureaucracies

are merit appointed, and politicized. With the advent of the internet and all it entails, we

can have a decentralised power structure with efficiencies of specialization.

There is a comprehension questionnaire that acts as a meritocratic filter against mob rule.

Mob rule is the largest objection to direct democracy, I believe with this filter, combined

with the structure of the bureaucracies in charge of information, identity, voting fraud and

security, would partly solve that major concern. As the heads of the bureaucracies are

politicized those that choose not to participate in the "executive", can still exercise their

vote.

As with any democracy the possibility of tyranny of the many, over the minority is a

possibility, which is why I would not recommend it for developing society. I have also

suggested such a high percentage of the population must vote on any change to the

constitution, as the minorities’ rights are protected as citizens’ rights in the constitution.

A point of interest is the proportionally larger vote for local district citizens, where bills have

specific local impact.

I tried to structure Individual Democracy, so that the society can decide if its "left" or

"right", so to create a more valid and current social contract between the citizenry and their

government.

ID dose not subscribe to proxy voting, or meta government, as in my belief corruption can

creep in between layers of government.

I am open to amending ID, as I do not believe in absolutism!

There is the short manifesto of 18 pages. I am still working on the book which backs up ID, it

contains examples of the comprehension questionnaire, statistics on reading speeds,

recommended structures for social cohesion and a reward system for positive social

behaviour.

It contains the formula for two alternate currencies [or point systems] that will run along

standard currency, one based on rarity value/social value/time, the other is a reward system

for positive behaviour [ie kindness].

Can technology become part of our bodies?

By Houda

We seem to become more and more reliant on technology as increasingly sophisticated

devices are being churned out. What if, instead of being

produced for our phones or tablets, these technologies

were developed for our bodies? Would you use a machine

that affects your perception of colour, or wear a dress that

reacts to your emotional state?

Artist Neil Harbisson is completely colour-blind, he can

only see shades of grey. However, a device attached to his

head translates any colour in front of him into a sound. In

other words, he hears colours; colour and sound are

exactly the same thing to him. He can “see” 360 colours, including infra red, and expects to

add Ultraviolet to his list. Imagine being able to hear UV light, with the sound getting louder

(or higher pitched) as their intensity increases, a kind of alarm that forces you to get out of

the sun before you fry your skin!

And imagine painting with a sound palette instead of a palette of colours. Neil Harbisson’s

art includes sound portraits; specific chords that combine the sounds of a person’s hair,

their skin, eyes and lips. Conversely, he converts sounds, musical compositions, or even

famous speeches into “colour scores”. Here is his story on TED.

Then there is Lucy Mc Rae, a body architect passionate about “merging biology and

technology in our own bodies”*. Her ambition is to transform clothes into interactive

devices that respond to

subtle triggers like

sensuality, affection and

sensation. The Bubelle

Dress, pictured right, is

made up of two layers, an

inner layer containing

biometric sensors that

Colour score for Beethoven's Für Elisa

pick up a person’s emotions and projects them in colours onto the outer-textile-layer.

You can hear more of her ideas on TED.

If you could express only one emotion through your clothing, which one would it be? And

what would it sound like if these two people worked together? Let us know at your next

meetup!

*http://www.ted.com/talks/lang/en/lucy_mcrae_how_can_technology_transform_the_human_body.html

Wanted…

Pacorrossa is looking for a microbiologist for some insight on the world

of bacteria

Sebastian is looking for artists interested in experiencing the effects of a

neuro-stimulator lamp and translating their experience into a piece of art for a

group exhibition in December/January. This involves a two-day event on 2-3

October. Follow this link if you are interested (leads to our message board)

Adele Mills, a producer from BBC4 is looking for scientists who can (or

want to) tell jokes for an upcoming programme (Filming on October 18th in

London). Full details here

Houda is looking for course buddies to make up an Artist seeks Scientist

team. I have signed up for two of the Stanford University courses (Designing a

New Learning Environment, and A Crash Course on Creativity), and since they

are team-based, I thought it would be fun to have a meetup team, especially

considering that we all have such different backgrounds. The courses are free

but you need to register (click on the course titles for the link). Let me know if

you do register and want to be in the same team.

Artist seeks Scientist is looking for a new venue, since we cannot

use Waterstone’s anymore. Any suggestions/ideas are most welcome.

Some comments

Thank you, thank you, thank you for all the lovely emails, suggestions and comments! I

decided to share a couple with you

“I came along to my first Artist meet Scientist meet up on Wednesday. I really enjoyed it. I

didn’t know going to a museum could be so much fun. There was a great group of people at

the meet up. I haven’t had a conversation with anyone about science since I started

university…. I enjoyed the music talk. It would have been fun to go on the silent disco too.

The meet up has really encouraged me to read more into science and watch TED etc.

Look forward to the next meet up. Have you heard of the Cheltenham Science Festival? It

might be worth going there.” (S Basu, Science Lates)

“It was a lovely "Meet up", such an eclectic, interesting and friendly group, and I'm looking

forward to possibly collaborating with a few people I met :) (Alex, Waterstone’s Meetup,

Bring something you love/hate)

“My impression, having only just joined, is that the group, as per your Leonardo quote, takes

a narrow and rather literal brief, like most people thinking about consilience. Science-

relevant-to-art and art-illustrating-science.

Actually it should be science seeks art - for the arts depict major and vast, scientific, ( i,e,

truthful) dimensions and areas of the world that only images can reveal, and that science

hasn't yet got into and/or that complement science. Is anyone interested in this

philosophy/approach?” (Mike, message board)

That’s all Folks!

See you very soon