Volti, Unit 1 information, chapters 1-3

• The Nature of Technology• Winners and Losers: The Differential Effects

of Technological Change• The Sources of Technological Change

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Forecasting• Any individual or organization affected by

technological change inevitably engages in forecasting (financial, economic, etc.)

• Goal is not always to predict future• examine trends• predict likely scenarios• develop contingency plans

Methods of Forecasting

• Summarized from Martino’s Technological Forecasting: An Introduction handout (PDF available in Course Documents area)

• Examples may overlap with more than one method

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Extrapolation• Projecting a pattern that has been found in

the past, to anticipate potential outcomes in the future

• Examples: Moore’s Law / El Nino• Examples?

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Leading Indicators• Using one time series to anticipate / obtain

information another time series

• Assumption is that both time series share similar behaviors, but with a time-lag

• Example: “What the barometer is doing today is what the rain clouds will do tomorrow”

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Causal Models• Finding cause and effect relationships • Contextualizing first two methods• Example: understanding why the barometer

itself works, in order to better understand why there will be rain clouds tomorrow.

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Probabilistic Methods• Forecasting using any combination of the first

three methods, then arriving at a range of possible values

• Example: 70% chance of showers

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