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Re- Designing the City of the Future

Re- Designing the City of the Future. LIFT 07 7 February 2007, Geneva Cockayne & Nova. Today’s Agenda. Working in the long-term future. Design. Research. Foresight. Critically explore assumptions, build models & develop questions. Develop strategies: Scenarios deep dives

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Re- Designing the City of the Future

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  1. Re-Designing the City of the Future LIFT 07 7 February 2007, Geneva Cockayne & Nova

  2. Today’s Agenda

  3. Working in the long-term future Design Research Foresight Critically explore assumptions, build models & develop questions • Develop strategies: • Scenarios • deep dives • Trend finding • Design for today’s future • Ethnography • brainstorms • - prototypes ambiguity Up to 4 years Up to 7 years time

  4. How to Think About the Future, generally • The future is a complex problem. • You can't predict the future, but you can invent it. • Use ‘data’ and analytical reasoning to discern what might exist and what we could build. • While predictions are foolish, there is value in the underlying discussions. • Focus on the questions generated, not ‘answers’.

  5. What is a city?

  6. A.D. 3000, Corbusier, Mumford, and Hall. • Did any of the authors did each guess correctly? • Why were some incorrect guesses so bad? • What seems to have changed the most over time? • Social or technical? Was it a driver or a reaction? Global or local? • What changed the least? • What types of major changes occurred?

  7. X X X X X X X Foresight Thinking

  8. S-curves product technology invention lab bench scientificbreakthrough scientificdiscovery idea

  9. X-Y

  10. White spots, hot spots

  11. When are the changes? X X X X X X X

  12. ? ? ? ? ? ? ? ? ? Foresight Thinking for Designing

  13. People • Think about Shakespeare (or the Greeks, the Romans, and anything else that seems “timeless”). • Think about people today and at the future time. • If you assume people will change, what’s the single most important reason (driver)? • When thinking about a change, what are the early indicators (triggers, incipients)?

  14. Analyzing and describing • Ideas are fine • Questions are more important • Assumptions are critical • Stories will tie it all together, even fractured ones

  15. ? ? ? ? ? ? ? ? ? Prototyping • Models are endpoints. The underlying assumptions, questions, and changes are more important. • Models can be used incorrectly. • The best models generate questions around the areas of highest change. • Make the model interesting, but not comical.

  16. Communicating • Stories (Short stories, Speculative fiction, Science fiction, Counterfactuals) • Scenarios • Personas • Movies • Corporate videos, commercials • Maps (Cross-impact, Trends, S-curves) • Objects (Wired’s ‘Artifacts from the Future’, Philips Design, Jason Tester @ IFTF)

  17. Viewpoints / ‘genres’ • Utopian / Realist / Dystopian • Malthusian / Growth / Accelerating • Technocracy / Democracy • Techno-determinist / Technophobic / Technophilic • Libertarian / Liberal / Communist / NWO / Fascist

  18. Futures and forward-looking data sources • Research Orgs (NAS, OECD, EIU, RAND, SRI …) • Futurists (IFTF, GBN, IAF, Club of Rome …) • Popular Press (Kurzweil, Toffler, Schwartz …) • Corporations (Shell, Philips, Microsoft …) • Popular Print (PopSci, TR, FT, Economist, WSJ …) • And for historical data (s-curves, stories) • ‘Invention & Technology’ the magazine • CNRI Infrastructure Series (rail, phone, nrg, cash, radio) • Popular Science / Popular Mechanics • Movies are not valid as ‘data’, but they are fun. • Science fiction is not valid, and even more fun!

  19. X X X X X X X ? ? ? ? ? ? ? ? ?

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