Blog: The politician, the scientist, the stakeholder and the Babel Fish

Geoff Mulgan wrote a fascinating and important piece on ‘Experts and experimental government‘ about how evidence is used (or not) to make key decisions, particularly in the context of government policy design and implementation. Please do follow the link, it’s a very good read (but read this post first, in case you get enticed by Mulgan’s links and forget to come back!)

It made me think of Herbert Simon, the first Nobel Prize winner in economics. In the mid-80’s Simon gave a lecture at Stanford on the progress of critical thinking about complex social problems. He made the (perhaps surprising) point that he thought the greatest invention of all time was the computer-based mathematical model. Why? Because it offered the first opportunity for groups of people to think collectively about very complicated problems. Individuals can model parts of the problem and then combine their knowledge with that of other people in a logically consistent way. He went on to make the point that mankind has never before had this capability, of creating a ‘meta-neural network’ to capture information that can be worked on by many brains in parallel (across the globe in principle).

There is another point to make here, and that’s where the Babel fish comes in (you did wonder, didn’t you?). Some of you will remember this creation of Douglas Adams, the fish that when inserted in the ear can translate automatically from whatever language it hears into the language of the ‘wearer’. This is another feature of a software model, it can act as the translator between the different languages used by politicians, scientists and other experts, and stakeholders, including the general public. You may wonder why this is necessary, given that they all speak English (or whatever common language they have). The catch is that they do speak in different languages, but don’t realise it. The words and phrases they each use have specific and different meanings to those in different communities. Just think about the difference in the implications of ‘uncertainty’ between a scientist and a politician – for the scientist it is a fact of life, and perhaps a number to be managed, whereas for the politician it is often simply a ‘bad thing’.

The good news is that the use of software models to help humans communicate is already well established, with applications including collective sense-making and collaborative decision-making. Decision Conferencing was introduced in the late 70’s by Cameron Peterson, and developed further through extensive use by Dr. Larry Phillips at the LSE. In the same timeframe John Warfield was developing what he called Interactive Management. These approaches are now in regular use in business and the public sector, and becoming even more necessary as the complexity of life continues to grow well beyond the complexity that can be managed in a single human head.

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