1. Bill Clark Knowledge for Development Seminar September 25, 2003
Knowledge Systems for Development: A Survey of Core Questions, Tentative Answers
Bill Clark
Knowledge for Development Seminar
September 25, 2003

2. The Problem
Growing (recurrent) recognition that development "is built not merely through the accumulation of physical capital and human skill, but on a foundation of information, learning and adaptation…” but
Relevant knowledge is underproduced, underutilized, unevenly distributed…
(World Bank, World Development Report: Knowledge for development. New York: Oxford University Press).

3. The Problem (cont)
Even the knowledge that exists is seldom integrated into systems that can support decision and application on the ground.

4. The world almost certainly under-invests in knowledge…
Technology (“the growth of knowledge”) is dominant engine economic growth (Solow)
Marginal social rates of return to R&D v high…
Eg. In Ag, 40% to private, 70% to public R&D (Ruttan)
But private investments lag, in part because of large public spillovers, property rights issues…
Public investments static or falling due to perceived irrelevance, ineffectiveness of results (ICSU/TWAS/ISTS)
Social rates of return from Ruttan, 2001, pg , citing initial work of Griliches, later reviews by Evenson, Alston.

5. Perceptions of the utility of R&D
Researchers are dissatisfied “because they are not listened to” while decision makers are dissatisfied “because they do not hear much they want to listen to…”
Lindblom and Cohen, 1979, Usable knowledge
Decision makers see the R&D community as problem-raisers, uninterested in solutions
ICSU/TWAS/ISTS, 2002, S&T for SD

6. $/M people
Inequalities in the capacity to create knowledge (4x greater than inequalities in income)
World Bank, World Development Report, p. 2.
(Source: WB, 1999)
$ (1987)

7. How to better harness science & technology to support decisions for SD?
Many policy measures being advocated…
“Send more money…” (Sachs)
Fix intellectual property rights (including TRIPS)
Build capacity (Johannesburg Summit)
Do more research (World Acads of Science)
Better monitoring and reporting (World Bank)
Reform institution X (UNEP, CGIAR, UNDP, WB…)
Probably all useful… but random and not obviously complementary or prioritized

8. Decision-support /Knowledge systems…
Need to understand the “knowledge systems” that support decisions through…
set priorities, mobilize funds, do the R&D, review publications/promotions, facilitate practical application and reinvention…
Recognize these not designed from scratch, but evolve through time…
Example of a “knowledge system”…
The international agricultural research system

9. S&T in the Agricultural R&D System
Specific Example
Agriculture System
General “Layer”
Farming
Locational learning
User adoption
Managem’t advice
Extension
Information system
Plant varieties
Agroindustrial dev
Commercialization
Plant breeding
Technology devel
Invention
Plant genetics
Agricultural res
Applied research
Botany, Biochem
BioSciences res
Basic research
Vernon W. Ruttan Technology, growth, and development: An induced innovation perspective. (NY: Oxford Univ Press), pg Adapted from W.E. Huffman and R.E. Evenson Science for Agriculture: A long term perspective. (Ames IA: Iowa State Univ Press), pg 43.
Ruttan, from Huffman and Evenson, 1993

10. Examples of other (relatively) effective knowledge systems
Agriculture: CGIAR commodity programs
Environment: ENSO applications programs
Health: WHO malaria campaigns
Military: US Smart weapon systems… …
Fortunately, we have examples of such research systems. Among those that have been relatively effective in meeting such goals are

11. Learning from experience with knowledge systems?
What distinguishes more from less effective knowledge systems? What can be learned about improving performance from comparisons?
We don’t know…
Little systematic research within problem areas
No comparison across problem areas (“Island empires”)
Yet some core challenges beginning to emerge
Goal of of our work is to explore these…

12. Useful knowledge for decision support?
Knowledge that is used is perceived by decision makers to be simultaneously salient, credible, legitimate… not just one of these
Saliency (Is it relevant to decision making, to changing needs of specific users, producers?)
Credibility (Is it technically believable, endorsed by relevant evaluative communities?)
Legitimacy (Is it perceived to be politically fair, respectful, evenhanded by stakeholders?)

13. How can knowledge systems be designed that better…
Empower end-users in setting priorities for R&D?
Create “location-specific” knowledge needed for decision support?
Integrate “basic” and “applied” approaches to produce “user-inspired basic research” (Stokes)?
Incorporate both tacit knowledge of practice and global knowledge, technology in local solutions?
Integrate public and private needs and capabilities?
Foster “boundary spanning” organizations to connect knowledge and action in pursuit of the above?

14. For further information…
On the general challenge of harnessing science and technology for sustainability
On knowledge systems research seminar at Harvard University

15. END