César Hidalgo discusses the benefits of academics working closely with business.
I’ve spent the past 16 years at US universities, and the last decade leading MIT’s Collective Learning Group at Cambridge, Massachusetts. The campus is a highly ‘entrepreneurial’ environment that encourages academics to push out their ideas by either spinning out their own start-ups, or by working in collaborations with private companies.
Spinning out an idea from a university is a very difficult process, and is also unlikely to happen using an academic paper as the only vehicle. Knowledge is in the authors, not the papers, so knowledge transfer requires frequent contact and collaboration among people in and out of campus. Indeed, I could recount many stories here intertwining academic labs and private sector companies, especially in sectors such as biotech, pharma, robotics, and software. Many of the most highly regarded professors, like George Church or Robert (Bob) Langer, are known for having begotten dozens of companies.
But this can only happen in an environment in which you reward researchers for having impact in diverse ways. Admittedly that impact might sometimes only be tied to publications, but sometimes there is a demand for more applied knowledge. Personally, I think some models of research are too narrowed down on the narrative aspect of research, even though I love writing. But there is much impact that also can be achieved through ‘doing’.
Applied thinking
Alliance MBS has a long tradition of applied thinking and being a leader in thinking about innovation and on science and technology policy. This is just one of the reasons why I am delighted to be taking up an honorary position at the School as part of a wider move to Europe that involves me also taking a Chair in the South of France at the Artificial and Natural Intelligence Institute (ANITI) at the University of Toulouse.
ANITI is a new research organisation created as part of France's strategic plan to compete in the field of Artificial Intelligence (AI) and is focused on the fundamental and applied aspects of technological, human, and social intelligence.
My move to Europe will allow me to collaborate more closely with Manchester and researchers in other European hubs working on AI, economic complexity, knowledge diffusion, and data science. I also plan to continue splitting my time between academia and business as I get a lot of ideas for research from the interactions and lessons I learn from my business activities, and vice versa.
Data
In terms of my business activities, seven years ago I founded Datawheel in the US, a company that has professionalised my research on the creation of data distribution and visualisation systems.
The rationale behind the business is that most companies generate vast amounts of data but that data is frozen, as if hidden under an iceberg, in storage and operational platforms. Datawheel’s solutions are all about helping business leaders thaw that iceberg, making the data easier to manage, explore, and visualise.
A lot of the value of data comes from having good interfaces and being able to interact with them. On its own, data is raw and arid. But if you take the cliché of data as the 21st century ‘oil,’ then the value comes from refining it.
End-to-end solutions
In particular what we have been working on are new end-to-end solutions to integrate, organise, and visually distribute many data sets. At the back-end we have created methods to create highly expressive Application Programming Interfaces (APIs) which automatically produce every possible ‘endpoint’. We then use this hyper-specific ability to link to data to create expressive visual resources, like DataUSA (datausa.io) or the Observatory of Economic Complexity (oec.world).
These public data projects have allowed us to research different ways to organise data and helped us discover a modular stack of software that we can now use to quickly build platforms of this kind.
Power of research
Trying to do this research with private data would have been hard, but by researching the development of public data distribution platforms we’ve created a capacity that works well for the creation of private sector platforms.
Some might argue that it should be only up to businesses to develop such interfaces, but I believe academics can explore ideas that are often further ahead by focusing on more ‘altruistic’ or ‘curiosity driven’ projects. The goal is to create projects with the hope that the world can catch up with the imagination, and it is at that point that research gets applied.
Academics are not able to compete on scale, distribution, or product reliability, but can compete on speed, creativity, and prototyping. That requires a creative branch of academia. If academia is simply limited to commenting and critiquing, those creative outbursts may not happen.
