Innovation: How to “generate” new ideas?

This is courtesy a tweet from my “Twitter-mentor” Prof Soren bentzen:

The linked write up from Nature is here.

Prof Paul Nurse writes:

I have a different view: description and data collection are necessary but insufficient. Ideas, even tentative ones, are also needed, along with the recognition that ideas will change as facts and arguments accumulate.

Why are researchers holding back on ideas? Perhaps they are worried about proposing an idea that turns out to be wrong, because that might damage their chances of getting promotion or funding. But as Charles Darwin put it: “False facts are highly injurious to the progress of science, for they often endure long; but false views, if supported by some evidence, do little harm, for everyone takes a salutary pleasure in proving their falseness; and when this is done, one path towards error is closed and the road to truth is often at the same time opened.” To wit, it’s important to get the facts right, but new ideas are useful, as long as they are based on reasonable evidence and are amenable to correction.

(emphasis mine)

The classic conundrum: How to generate ideas to spur innovation? The problems are hiding in plain sight. We are buttressed by traditional mores of “hiring” and assessments of “academic metrics” and beholden to p-values. Long before, I had realised that an integrative approach will break down silos. What I failed to realise is silos exist in the mind and are refractory for identiication. So far, I have made over twenty attempts (and counting) to get into academia and put my ideas to practise!

I have extensively written on innovation and “curiosity driven research”. As much as I wish to get into academia, institutions of higher learning are more focused on “market-driven agendas” and burnishing their credentials to run expensive Zoom classes.

Here’s what I wrote on ET Prime last year (it’s behind the paywall but I’d include the relevant parts):

Innovation and decline of research and development have become a hostage to the quarterly profits and loss statements, as the metric of a company is adjudged on financials alone. For example, Airtel as a telecom behemoth used to manufacture push-button telephones, but it morphed into the pure-play services side and did not venture into manufacturing again. The real beneficiaries are the third-party manufacturers outside India. I’m mindful of the fact that research in corporations is challenging to manage, as it usually involves a complex interplay between various departments. Research projects have long-gestation period with a few intermediate milestones that can be understood meaningfully by non-experts.

I wrote further (though in generic terms):

Huge endowment funds bankroll universities abroad, especially in the US, with parallel-track financing (through private charities) or establishment of chairs that usually leads to an agenda-driven research protocol. The applicability to solve the problems is an open-ended question. While it is tempting to eulogise their publish or perish culture, tenure tracks have become rarer with an increasingly mad scramble for the grants lottery.

The way forward (also as advocated by Prof Paul Nurse in the linked Nature article) is as below. I wrote on ET Prime article:

This an opportune time for India to reboot a hybrid model of industry and university-based research (with all the above caveats) and provide equitable access to academic resources. It would also be prudent to push an open-source, and an open-access model, free of proprietary controls. This model should also be outside the self-appointed academic gatekeepers. There has to be a policy push towards a systematic and structured approach to address the crisis in higher education, employability of graduates, and a gradual depoliticisation of campuses.

(emphasis mine)

There are several financing models for science – I’d include the blog posts subsequently. I am studying the venture capital “style” funding model with a designated ROI built in to make it financially self-sustainable. Beyond the optics, innovation requires disruption to traditional academia. Ideas need precedence. It is again one reason why I blog extensively, because it gives me enough leeway to zoom in and out of perspectives and observe how ideas are interlinked.

Innovation won’t happen with pure data pipes. It will happen with a re-look at the way we hire, assigning leadership goals towards defined end-points and allow ideas to be “attacked”. To this point, I remain committed to having my own “innovation-lab” where every idea is welcome. The way to work them forward is to design internal teams and compete for the same set of resources. A Darwinian evolution framework will emerge to push them forward and make them sustainable. It does away with the idea of a “grant lottery” and tap into funding mechanisms outside traditional academia. It requires a vision to behold beyond the “points of failure” and allow failure to happen as a routine.

That’s what science is all about. Success is usually an outlier. Perhaps we have become too averse to failure.