Sunday, January 29, 2012

Delphi Methods (i)

Revised 8/29/17


Reminder: HW1 due by midnight

      Confusions?
      Questions?


























































Postscript: I tracked it down!







Way back in 1995:

-Their team toured the U.S.

-Met with me as part of their consultation process

-Produced "Future Technology in Japan: Toward the Year 2025"

-Sent me a copy of the previous edition:
    "Future Technology in Japan: Toward the Year 2020"

They produced a set of predictions every 5 years

    ... ended with the 2035 predictions

    ... we could try searching for it to see

    ... 2035 seems unavailable

    ... earlier editions may still be available






















You could consider using
your question and the
results in your term
project











































Wednesday, January 25, 2012

More heuristics for foreseeing change

"Shift Happens"
  - youtube video
we'll watch later...
but first...



Heuristics

What is a heuristic?


Last time: curves

   We saw
     linear,
     exponential,
     S, and
     plateau curves

     Recall:
     each approximates
     a small piece
     of the one after


Are those curves...
    laws?
    heuristics?
   
Today -

   A grab bag of
      heuristics
  for predicting

  (What was a heuristic again?)


Next time -
  Delphi methods

To prepare:
  think of one question
  about the future of
  something of your choice

     In class, we will use
     Delphi methods to
     apply our
     collective wisdom
     to your question


(Also, HW 2 is due in two classes 
- questions about it?)




Let's check two versions of 
the youtube video 
"Did you know?"
(ref: http://thefischbowl.blogspot.com/)


2006: "Did You Know":
http://www.youtube.com/watch?v=cL9Wu2kWwSY


2009: "Did You Know 4.0": 
http://www.youtube.com/watch?v=6ILQrUrEWe8


How would you compare them?


Should they do another one for 2012?


But first, let's make a grid on the board for:

Statements in the video (rows)

Believability (column)

Implications (column)

Hidden messages (column)

Connection to methods of prediction (column)




Now the videos, 
then we will
analyze more...



Let's apply some of the following methods to something in the video!
(Some of these are from Peter Bishop's Futuring: An Introduction to the Study of the Future)


   Extrapolation

   Theoretical limits

   Paradigm shifts

   Adam Smith's "invisible hand"

   Cause and effect

   Foresight instead of forecasting

   Vision

   Expectations make it so?

   Risks & possibilities

   Can the future be controlled?

   Simulation/gaming

   Scenarios

   Oracles

   Psychohistory?

   Leading indicators

   Science fiction

   Road mapping

   Metrics


Monday, January 23, 2012

Trajectories of the Future (& Overpopulation on Mars)

An Example of Extrapolation:
Overpopulation on Mars

Suppose we started a
self-sustaining colony
on the moon
(see http://www.youtube.com/watch?v=EgOg0mzqGAM)
or Mars
(see http://mars-one.com)

100 colonists

What is your estimated
rate of increase per year?

What is the total population
capacity of Mars?

     Earth surface area = 510,072,000 km^2
     Earth land area     = 148,940,000 km^2
     Mars surface area = 144,798,500 km^2

                                     (0.284 of Earth)

How long do you think it will take
for Mars to overpopulate?

We can check this using a spreadsheet!

Just have the rows represent successive years
Each year has x% more people than the previous
See how many years go by until overpopulation!

Making and Discuss Predictions with Trajectories

       Method: Trajectories of change

. . . in the short term, change appears linear













Example 1:

  • Last year you used 1-2 e-books and the rest paper


  • This year you will "probably have 1-2 more" 


Example 2:

  • This year maybe (???!) 1 or 2 of you have cordless chargers


  • Next year 1 or 2 more will?

Example 3:

  • Can you think of any other examples?










Example 4:

  • Last year you had 1 or 2 compact fluorescent bulbs


  • This year you will "probably have 1-2 more"
  • This example used to work 
    • but no longer does!
    • Why?


In the longer term,
change often looks
exponential


Lightbulb example:

. . . you start with 1-2, but then accelerate

. . . the rate of increase increases

. . . if you look at an exponential curve with a microscope, what does it look like?

. . . "Exponential": complicated word, tricky math, simple concept

. . . . . . goes up faster and faster

. . . . . . has a doubling time

Exponential curves explained

. . . Popular example: Moore's Law

. . . . . . (# transistors on a chip doubles every 1 1/2 to 2 years)

. . . Similar law proposed for digital camera resolution

. . . . . . (includes 7-second video)

. . . Suppose something doubles every 3 years

. . . new value after t years is original value, v, times 2^(t/3)

             Let's try that for, say, 3 and 6 years:

                   What should happen? What does?

. . . f(t)=to * 2^(t/3)

. . . . . . where does the "doubles" appear?

. . . . . . where does the "every 3 years appear?

. . . . . . so it works for
            any factor of increase and
            any time constant
            What formula gives tripling time?
            What formula gives doubling time of 1.5 years? 10?

The hockey stick fallacy


. . .Exponential curves are
     a kind of "hockey stick curve"
. . . . . .Why?


. . .Why and how shall we pick the key point?

. . .Surprise! The curves are for the same function
. . . . . .x-axis: n
. . . . . .y-axis: 2^n

. . .All I did was s t r e t c h and  >squeeze<  it!

. . . . . .My super-fancy graphical editor: MS Paint

. . .An important lesson:

. . . . . .the hockey stick "knee" is not a mathematical property

. . . . . .it is a purely graphical property! 

. . .Let's try another example...


. . .Where is the "knee" this time?






. . .Surprise! This is the exact same function:
                            y=2^x

. . .This time I just graphed it out to bigger x

. . . . . .spreadsheet automatically squeezed it downward more

. . . . . .(otherwise the graph would be way higher than the roof)

. . .One last example:


. . . . . .the two curves are the same size and shape
. . . . . . . . .(because overall graph size/shapes are the same)

. . . . . .they have different knee locations

. . . . . .they graph the exact same function

. . . . . . . . .one is graphed for x from 1-20

. . . . . . . . .other is graphed for x from 21-40

. . . . . . . . .curve shape & knee location vary with scale

. . . . . . . . . . . .scaling defined by width, height, & axis numbering

. . .Conclusion: 
     The hockey stick "knee" 
     is an optical illusion
     (for exponential curves)

. . . . . .It doesn't really exist

. . . . . .exponential curves accelerate
. . . . . .smoothly at a constant rate


Longer term, things "Level Off": the S-curve


Also called "logistic curve"

Sort of "linear" early on

Then looks "exponential"

Then levels off

Justified by many, many diverse phenomena modelable as:
       Malthusian scenarios
       Constructal Theory scenarios
           A. Bejan and S. Lorente, The constructal law origin of the logistics S curve, Journal of Applied Physics, vol. 110 (2011), 024901, www.constructal.org/en/art/S-curve.pdf.


Do you think 
an even longer-term view 
will look like a 
plateau curve?

Think about transportation by horse,
pencils, compact fluorescents, etc.










.

.




What do you think of these curves?




There are other views of trajectories...

Gartner Hype Cycle











.


(Source:
http://en.wikipedia.org/wiki/File:Gartner_Hype_Cycle.svg)


How might this apply to some of our topics?

There is also the Technology Adoption Life Cycle

There are also other relevant curves for
"thinking quantitatively about technological progress"