3 min and 8 sec to read, 785 words

Introduction

Here is an interesting policy exercise: assume that you had to talk about artificial intelligence and machine learning, and how it will change the way we work, do research, learn and so on in society – but you could not use the concept of “artificial intelligence” at all, but had to speak about the coming technological, possible transformation more broadly — what would you do then? This short note suggests that one way of thinking about this is to think about it as the building of a cognitive infrastructure in our society.

A cognitive stack

The idea of a cognitive infrastructure as a key element in our society could build on the old distinction between data, information, knowledge and wisdom — but we would shift the last layer here, and call it decisions instead. The reason for this is that this last layer is an activity – a flow – rather than a stock. Data, information and knowledge are all there to help us make decisions and ultimately to learn about the world we are in. And our decisions are a part of an adapative pattern, and allows us to deal with the complexity that we have created in pursuit of progress and welfare.

Cognitive infrastructure, then, is the kind of infrastructure that underpins this stack. It covers practices for collecting and curating data, structuring and interpreting it, interpreting and learning from information, and making decisions with the resulting knowledge. At all layers in the stack, there are infrastructure investments needed, and an organization or a country will only be as good as its cognitive infrastructure allows it to be.

Investing in cognitive infrastructure: data

If we want to make public investments in our cognitive infrastructure, we need to ensure that we do not treat this as something separate to our overall social and economic activity. It becomes important to ensure that we really embed this stack thinking in all of our policy decisions.

For data that could mean that just as we present consequence analysis for the environment or entrepreneurs with all new policy proposals, we should make sure that all public investments and policy proposals also come with a plan for the collection and curation of data. This will ensure that we build data in from the beginning, designing with the data we may need – and hence also with the kind of information, knowledge and decisions we want to make – from the start. This – learning by design – is a key stance that we all – whether public sector or companies – benefit from taking.

This is where we figure out what the statistics agencies of the future should look like – and if they should be stand-alone agencies or embedded functions in all public bodies and institutions.

Investing in cognitive infrastructure: information

The next layer is information – here we are concerned with the structuring of data into information that can be interpreted and learned from. This is where we need to ensure that there are standards, structures and research into how we best structured data. Benchmarks, tests and long term curation of the data also goes here.

Traditionally this is where we have had libraries, and where we now need to build next generation libraries and invest in educating librarians, experts in structuring data.

Investing in cognitive infrastructure: knowledge

Knowledge is the product of learning, and when we are trying to build out this layer we want to make sure that all our of institutions, organizations and groups have learning practices in place. Actively collecting and distilling what we have learned requires also setting up experiment infrastructures that allow us to test the knowledge we think we have. In many ways this is about building out science to a socially shared and participatory activity.

Investing in cognitive infrastructure: decision making

The final layer is one in which we document, follow up and analyze our decisions – and apply all the knowledge produced in the cognitive infrastructure to ensure that we make decisions that are the best possible given the time / data and resources we believe a decision merits. Decision making is in many ways at the heart of our societies and for far too long decision making has been left to hunches and intuition only (even if these continue to play a role in decision making under different kinds of uncertainty.

Conclusions

As this quick sketch suggests, the notion of a cognitive infrastructure may help us think more about what we want to use technology for, rather than focus on the technology itself. It can be built out and explored more in detail – of course – but there is a thread here to pull on.