When Consensus is Conceded Innovation Isn’t Interrupted

What is the biggest hurdle for innovation to overcome? Consistent convergence. But how in the face of constant concern, even when it’s concern for what has already been done, when it’s still said it can’t be done ? Here’s how.

iGNITIATE - When Consensus is Conceded Innovation Isn't Interrupted
Design, Design Thinking, Design Futures, Detailed Design and Design Engineering is, together, the basis for, and most flexible tools of, constraint based morphing of input parameters into working end solutions. In other, what could be considered ” unhelpful ways ” we separately see the advent of Ai capabilities ( and especially as related to non-physics based output ) which can turn just about anything ( image and video wise ) into anything else and connect them together. It is here that the terms ” hallucinations ” for given data output from search engines / search engine data comes into being. It is also here where these Ai systems output demonstrate that the fundamental vocabulary ( and specifically via the multitude of search engine URL results produced ) can easily become obsurified and more, where In the past we saw a ( roughly ) well documented history of where data ” results ” came from, where now however the tables have completely turned. But how? And how can we utilize this for the further efforts of innovation activities ?

In the past the idea of innovation ( and again from the root definition of the word enumerated by Schumpeter ) we see that invention (conceiving a new idea or process – that works on a lab bench and as governed by the laws of physics ), turns into innovation (arranging the manufacturing and producibility requirements for implementing an invention – and where Schumpeter seems to have just redefined entrepreneurship in his original description ), and onto diffusion (whereby people observing the new discovery adopt [ purchase via entrepreneurship ] or imitate [ by copying to also sell for their own ] where Schumpeter has it correct ) seems now to have been upended. Ai and specifically generative Ai ( in many forms ) lets anyone jump right from invention to an infinite number of diffusions ( and call them all new ), and, at the expense of perpetuating concern for adoption which in fact is the exact limiter to innovation as discussed above. That which is not known for long enough to be encoded with the guise of safety is quite [ as the baby is ] often thrown out with the bathwater as the saying goes and where innovation fails.

When time frames for diffusion ( as in the above definition ) are extended and slowed down, when users are unable to discern viability and usability easily, it is here that the limiting factor to uptake is effected and thus barriers are further created that is at the constant forefront of innovation efforts. It is here where it is necessary to diverge from Schumpeter’s definition of ” innovation ” as the entrepreneurial process, and, a more accurate form of the definition of innovation comes into play: the effort of diluting and dispersing concern so as to actually reach consistent consensus and thus increasing the capability for value in a new something to take hold. Simple examples are that of the Xerox / xerography photo copying system started several years before 1938 when the technology was finally made to ” work ” in 1938 and thus the lab science / bench science invention phase was completed. It wasn’t until 1944 that it was ” noticed ” as important and where it took until 1948 where it was deemed a ” successful ” development effort ( most likely due to the innovation phase to be able to work within the context of a large manufacturable manner was completed ) and yet not available for sale until 1950, possibly 15 years after it’s conception, design and initial ” working ” mode. It is here we see the efforts of consistent consensus even after the math and physics were validated. Was it consensus pressures leading groups to reject this useful ( and thus patentable ) idea rather than move forward with them the issue? In many cases absolutely and as detailed in Greater Variability In Judgements Of The Value Of Novel Ideas in Nature Magazine. How then can these situations be mitigated so as to close such gaps in a better way? Interestingly it is as simple as unwavering concession.

Design and thus it’s constraint based counterpart, concession, is inherently limited by ( as in the case case of raw physics ) the necessity that some configurations of materials cannot operate in a way that may have been initial conceived – ” there are somethings you just can’t make plastic do ” as Steve Jobs famously said. However when it’s possible to keep 5000 things in play at the same time and still be able to reach functionality that increases usability and within the context of efficient manufacturability we see 2nd order breakthroughs / usability and the elevation of concern happen. And, it is this relentless process of configuring and re-configuring constraints that ultimately allows innovations to persist in the face of ” concern ” being often veiled within individual confidences of need that may not ( and often are not ) a form of the actual evolution of innovation to be addressed and delivered upon. Regardless these hurdles cannot be ignored and thus it’s Design, Design Thinking, Design Futures, Detailed Design and Design Engineering the bring about the quickest convergence capability to occur.



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