1. chapter structure
   1. introduction
   2. places where prediction could be useful
      1. brief building
      2. simulation and verification of somewhat developed designs
   3. methods of forecasting and their values to architecture
      1. Parallels between 'design stages' and methodologies
      2. heuristics & biases, calibration, knowing
   4. discussion of uncertaintly
   5. future trend recap
      1. //very// brief rundown of the major forces that are predicted to shape the future.
   6. case studies
      1. business
      2. design - ideo or philips perhaps
      3. architecture - building futures?
      4. my own - dissertation title modelling
   7. problems of prediction for architects
      1. is forecasting valid in a reactionary industry
         1. what other reactionary professions/industries are there?
         2. what do I mean by reactive?
         3. Maybe the architecture profession/building industry is only reactive because we consider each building anew. If they were thought of as a continuum then R&D becomes more of a useful idea.
         4. if R&D feeds future (R&D models, inhouse vs buying startups) (//also, find the report that says that R&D breeds more successful business//)...
            1. how much of a company's income should be spent on R&D?
            2. in a 'practice' based (//what does that mean?//) profession, does it make sense to separate R&D from practice?
            3. I'd say yes, but why? insulation from risk vs pressure and funding from projects? ask Judit.
            4. how do 'future' and 'practice' interact?
         5. are we right to think of ourselves as apart from the building industry?
      2. brief discussion of new business models
         1. 'buying in on risk' / owning risk
         2. project agency - cloud of skilled people vs tight team - existing company model.
      3. data
         1. if future prediction is a projection based on past events, then knowing about the past is required.
         2. We know very little about absolute metrics of the build environment, [[http://www.bre.co.uk/carbonbuzz/|Carbon Buzz]] is about the only project that is collating an open database for verification of data ([[http://www.digital210king.org/|the digital 210 king project is getting there, but isn't quite there.]])
   8. conclusion
2. Rationality
   1. Anthropic Bias: Observation Selection Effects in Science and Philosophy N Bostrom
   2. Judgment under Uncertainty: Heuristics and Biases D Kahneman, P Slovic, A Tversky
   3. People
      1. Robin Hanson
      2. John Broome
         1. Podcast
   4. lesswrong.com
3. statistics
   1. Bayes theorum
      1. An Intuitive Explanation of Bayes' Theorem
   2. people
      1. Eliezer S. Yudkowsky
      2. NN taleb
   3. books
      1. The Black Swan NN Taleb
      2. Innumeracy JA Paulos
4. simulation
   1. where does the point of unpredictability come?
   2. visualisation
      1. search space visualisation
         1. how to do this if there is more than one output metric
   3. vulnerability
   4. agents
      1. modelling hierarchical subs systems
      2. as agents or for agents?
   5. Robustness
   6. monte carlo
5. scenarios
   1. people
      1. Rafael Ramirez Said Business school’s scenario planning dude.
   2. disaster
      1. post apocalyptic urbanism
         1. A rapid event (several weeks) that causes a 90% drop in global population. What are the consequences of this? Social collapse, or united by a common cause?
            1. how rapid is rapid?
            2. something like a month?
         2. A slow event that will eventually have the same effect, but over a much longer time frame. For example, as a result of anthropogenic climate change in a positive feedback loop, tundra melts, and the Wilson ice shelf majestically slides into the water.
            1. less than 30 years?
         3. To prevent further loss, a group enter a refuge for 200 years to ensure safety. What happens upon emerging from the refuge to retake an earth devoid of human civilisation? At what point can a small group claim to be a civilisation? How could we give them tools to expedite their rise from hunter gatherers to urban beings again? What are some of the moral implications if we do?
            1. peter thinks that the idea of an emerging religon would be interesting
            2. should we bootstrap?
            3. does the human race 'deserve' a second chance?
            4. or should we be selfish and say that they made it, so tough luck
            5. should we allow a civilisation to emerge or should we bootstrap it?
            6. what about the memory of the 'old world'?
            7. would an emergent one be free from our adiction to fossle fuel, or just make the same mistakes as before
            8. how can we pass on the knowledge that we already have?
            9. editing
            10. can it be?
            11. should it be?
            12. wikipedia religeon
            13. andrewBurrow's idea of 'priestly class' that has the obligation of reviving knowledge
            14. images from city of ember
            15. scenario focus
            16. should i be focused on making 'real' architecture
            17. some of this for ds9
            18. or on the social and moral implicaitons
            19. I'd say that given the prediction based focus of the thesis that this is the better fork to take
   3. utopia
      1. Do I need to make a utopia scenario?
   4. books
      1. future factual
         1. Global Catastrophic Risks N Bostrom & M Cirkovic
            1. Artificial Intelligence as a Positive and Negative Factor in Global Risk
         2. Our Final Century M Rees
         3. The Meaning of the 21st Century J Martin
            1. what comes out of this?
            2. technology enabling education
            3. eco affulence
      2. fiction
         1. Island A Huxley
         2. Drowned world JG Ballard
   5. websites
      1. Shell - What are scenarios?
      2. Wikipedia Scenario planning
         1. Set the time and scope of the analysis.
         2. see my comments here
            1. Scenario planning has grown out of military inteligence i.e. what is my opponent going to do next.
            2. Scenarios are like games. They can be ‘played’ by changing the rules or by changing the inputs.
            3. “The games combine known facts about the future, such as demographics, geography, military, political, industrial information, and mineral reserves, with plausible alternative social, technical, economic, environmental, educational, political and aesthetic (STEEEPA) trends which are key driving forces.”
            4. In business the game is less against another human/organisation, and more against nature (how about a game with nature - is an opponent needed? more game theory work needed) Systems are often involved in scenarios as often models have hierarchical parts and feedback loops.
            5. “Systems thinking used in conjunction with scenario planning leads to plausible scenario story lines because the causal relationship between factors can be demonstrated”
            6. It is useful to attempt to test situations that are on the limits of possibility, ones that feel uncomfortable. this might show up annomalies in the model, or potentially annomalies in real life!
            7. Scenarios are used to find areas of the solution space/input space (interesting distinction?) are the most likely to cause big responses.
            8. wikipedia's take on how military scenario planning or scenario thinking is done
            9. Decide on the key question to be answered by the analysis.
            10. Set the time and scope of the analysis.
            11. Identify major stakeholders
            12. Map basic trends and driving forces
            13. Find key uncertainties
            14. Check for the possibility to group the linked forces
            15. this seems excessively reductionist, but I suppose it would make for a more manageable set of outcomes (smaller solution space)
            16. Identify the extremes
            17. disequilibrium looks interesting - i.e. do any actors in the scenario have a desire to move to a different state? and how can they influence other actors?
            18. Define the scenarios
            19. Write out the scenarios
            20. Assess the scenarios.
            21. Identify research needs
            22. Develop quantitative methods
            23. Converge towards decision scenarios
            24. so I suppose to summarise even more: Build a scenario that you think is plausable, pump some data through it, and then see what happens, then revise the scenario.
            25. simple scenarios made by accountants are often pretty good, but they don’t take into account any changes in outside forces, so they fail
      3. What is Scenario Thinking? scenariothinking.org
      4. so it seems that scenario planning is most closely analogous to sketch design
         1. that allows for multiple scenarios to be tested against a model that can be built robust enough to handle all of them
         2. scenatios tend to come in multiples of 3-4 where as sketch designs are individual. is this throwing out useful info before its time?
   6. actors in scenarios
      1. AI
      2. environment
      3. nano tech
      4. enhancement
         1. genetic enhancement
         2. cognative enhancement
            1. drugs
            2. training
            3. computational implants
         3. physical enhancement
            1. training
            2. prosthesies
            3. plastic surgery
      5. economy
      6. politics
         1. democracy
         2. dictatorship
            1. are there alternative dictatorship models?
            2. bdfl
            3. decentralised dictatorship is that just feudalism?
         3. Futarchy
   7. papers
      1. scenario planning: A tool for strategic thinking Paul Shoemaker
      2. Towards Agent Based Scenario Development for Strategic Decision Support
      3. Developing Scenario Laboratories with Computer-Aided Morphological Analysis
6. philosophy
   1. Hume
   2. Labyrinths JJ Borges
   3. Bacon
7. ethics
   1. divergent society
   2. playing god
   3. books
      1. The Case Against Perfection M Sandel
         1. Sandel's Rieth Lectures on the BBC
      2. What Sort of People Should There Be? J Glover
   4. people
      1. Julian Savulescu
      2. Janet Radcliffe Richards
         1. Kidney Sales and Moral Argument not really relevant, but an excellent example of how to structure an argument
   5. neglegent to NOT take full advantage
8. post/trans humanism
   1. Human Enhancement J Savulescu & N Bostrom
   2. Ethics of Human Enhancement: 25 Questions & Answers
   3. People
      1. Nick Bostrom
         1. letter from utopia beautifully narrated
9. skills
   1. very short introductions
      1. logic
      2. mathematics
      3. game theory
      4. choice theory
   2. writing
      1. The Economist - Style Guide
      2. Penguin - Punctuation
   3. structure of arguments
10. systems thinking
    1. Notes On the Synthesis of Form C Alexander
    2. General Systems Theory L v Bertalanaffy
    3. Systems thinking chapter from The Handbook of Sustainability Literacy
    4. people
       1. Professor Patrick Humphreys from LSE he seems to be more into descision theory stuff i need to read a few of his his papers
       2. Jerry Ravetz generally interesting guy inside the James martin school. Intersted in systems amongst many other things.
          1. Global Systems Failures
             1. reflexive systems A system is reflexive if SOME subsystems have functions AND purposes
             2. functions serve the super system
             3. purposes serve the system in question
             4. catabolic collapse (greer 2005)
             5. Every system contains a plurality of subsystems, and is also contained in a plurality or super-systems.
             6. Bacon made the deepest study in his theory of the four ‘idols’ or sources of error: that of the ‘cave’ is our own inherent weaknesses of perception, that of the ‘tribe’ is our unquestioned common assumptions, that of the ‘marketplace’ is our ordinary ideas about the world, and that of the ‘theatre’ is the teachings of the learned. To conquer these idols he offers an unlikely combination: puritanical solemnity of purpose, together with childlike innocence.
             7. Prediction is impossible; but as scientists know, chance favours the prepared mind.
          2. Emergent Complex Systems
    5. Symposium
11. Forcasting
    1. papers
       1. Futures thinking chapter from The Handbook of Sustainability Literacy
    2. methods
       1. prediction markets
12. discarded titles
    1. relationship between sketch design and scenario buiding