Computational Thinking Creates ? It Can.

Being creative assumes a substrate that never fails: a good spoon always stirs boiling pots. But what about when there is no spoon ?

When the medium of an artist's studio is a canvas and that canvas turns into a machine with a screen, when we dig a little deeper ( and in Computational Thinking in Science where Peter Dennign weaves together how if biology ultimately becomes an information science, and where computational Simulation always starts as something as simple as estimating how to catch a ball ) we see how our world views are radically changing. We see how in past computational thinking using machines with a screen in specific ways is where now entirely different thought processes and interactions with alternative computing models is allowing us to break free from step wise systems of envisioning, and, all in one shot.

When companies begin to ask ( and after having design thinking being embedded in all aspects of an organization ) how can non-typical computational thinking allows Designers to ignore the mapping of what needs to be physically made into the real machine ( at the physical hardware of whatever computing system XYZ level is in use at the moment  ) and where an almost all of a sudden, radically new model of non-computational thinking emerges. The medium is the message / the message is the system and all ( almost ) cases we see this via data sets. Will this then allows us to be released from systems / the mentality of simulation first and yet this can be that even more doors are beginning to swing wide open in firms and organizations that are growing and evolving with this new capability: raw data ( in so many formats you can't even count them ) first. Design is becoming data. Any data. Raw repositories.

How many designers ( and separate from the engineering mentality ) then become almost intricately connected to the level of abstraction necessary for the computational tools that are used to create &  think ? It is where design itself becomes part of a computational substrate and thus allows a user to directly effect creativity itself via environments or data that can be just loaded into an XYZ system that re-interprets at will. These new inflection points can be where breakthroughs begin to emerge in firms and organization structures and where unexpected efforts begin to grow at exponential rates in ways never expected of before.

Computational thinking then can be looked at not as a simulation job ( and which software engineers - those writing the substrate of the verbal and logical interfaces to the assembler of the microprocessor on which programs run )  but ultimately an exercise where computational systems no longer need to be thought of as linear canvases. We see this in the current capabilities of neuromorphic computing and even stable diffusion Ai systems where designing via completely new ways of thinking emerge quickly and where the output from that effort comes at incredible rates as well. In many cases these also do not requiring humans with their bare ( computer enhanced ) hands to re-invent via a one after another model.

Does this mean that there is an entirely new way of looking at creative computing itself and/or even a possible entire re-assessment of computational thinking / systems thinking as a way of working ? Is it then that within the context of being able to develop the mental skills that facilitate the design of automated process: now today referred to as creating " the algorithm " where we exactly see the possibility to unembed this aspect of the fabric of digging for novel capabilities and functionalities first and which many casually refer to as " innovation " and in some cases ' innovation science ' if such a thing can be said? We can then also see how computational capability and computational thinking can be ( at this moment in time with the machines that we have ) a fully integrated piece of an entire organizations ethos and why it's possible how specific R&D efforts lead the way in determining next generation products yet to be uncovered and where other methods produce radical departures from existing ways seeing and producing all together.

                    

   

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IP Integrity = Intentional Innovation

At the push of a button ( and all systems today allow it ) infinite content (URL) production occurs but how can IP integrity be maintained? Here's how.

When specific design goals, articulated engineering, and laser guided intent are the core focus of a known and maintained collaborative participant R&D based, bench to board room effort, and, when long standing and well established intellectual property protection is enabled so as to be the precursor to any and all accidental efforts to effect said output, this, is when innovation effectiveness is maintained and succeeds.

Implemented by all long standing organizations and efforts are the capabilities of design and engineering output where in verbal forms, low-performing groups that don't use multi-modal IP protection efforts were more likely to conduct R&D activities improperly vs. those that work with specific discernible outputs and with all authorized members connected to said efforts. This means delivering functional effectiveness of new product development takes place properly and rapidly. More we see in a recent and well established industry study which has been widely accepted, it becomes clear that Design for Complex Thinking and Ideathon Using the Transition Design Approach is but just one mechanism to protect decades of years ahead efforts in the substantiation of engineering and design efforts for innovation 1st based organizations.

More specifically we see the see the use of intent based Collaborative pattern analysis ( and sometimes within the context of Ai capabilities ) and execution by existing and long standing intellectual property owners to be the driving factor in the complexity of collaboration with specific focus to bring advanced new product development efforts into the real world. Where the protection allowed via these systems creates an exact and rapid awareness of changing landscapes, unauthorized use of intellectual property, and the necessary next steps to maintain the defensive postures to for the smooth flow of innovation activities, we see the essential foundations for further ground breaking labs based and R&D oriented efforts to continue in the systems necessary for this to take place.

 

                    

   

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Ai Driven = Ai Derived ? Not for a Da Vinci Determinate

When the hard stop of intellectual property protection is thrown by the wayside due to infinite " uniqueness " at what point does collective knowledge co-construction mean limitless innovation derivation ? It may be close to 100% thanks to Ai.

With an incredibly and over simplistic timeline lens of, say, just the last 4000 years ( plus or minus 2000 years on the standard Zero AD western calendar ) when we examine previous generations of tool making, design, and thus engineering capability, we see specifically, throughout the evolution and acquisition of ( say artistic, mathematical, etc ) skills the capability of specific designs and engineering functionality to be recognized and protected with a very high bar. To become a master took incredible time, patience and resilience. To create something unique and usable an even longer time. To have said efforts and outputs put into production and so to increase a users natural human capabilities even longer.

Sans digital tool creation and usage, and only focusing on physical object creation and production and specifically within the context that Ai-Driven Learning And Complex Adaptive Systems may in the future have the ability to create incredible jumps in end functionality of physical goods, one of the biggest explosions of creativity is taking place right under our noses. Driven by a factor that is uniquely overlooked ( the size of your mailing list / active social media users ) means it is  ( and not even by the end user sometimes ) the end producers that are driving what is possible for end users to enjoy and have in their lives. Think something as simple and elegant as the Eames Chair designs.

With the capability of " the master " mindset ( and certainly within the aspects of visual creativity being a button push away ) the idea that a Da Vinci mindset and personal capability to produce specific and unique output is now almost a side thought. The ability to have a Da Vinci determinate or timeline from creation to ownership is now ( via a typical 1st created, prototyped and manufactured model - and as always somehow within the context of the 4 year lab to real time window ) we are beginning to experience the technological capability of Ai to completely take over the idea of creativity as a value based exponent for new product development efforts. What does this mean? That an infinite creativity capability means that the idea of uniqueness may all but be over, that small changes to any existing X means the original ( no matter how " unique " ) can be determined to be not similar in any way to new productions and thus indefensible.

How this becomes factorized into the way where " new " and " unique " outputs are delivered, and especially within the context of physical products could be that medium-performing ( complexity ) groups - those who are more likely to involve and reply on online behaviors may be substantially more productive at avoiding specific cases of similarity to per-existing manufactured products versus situations where low-performing ( complexity ) groups and who likely to conduct design and new product development activities through verbal discourses and intense conversational efforts, may, no longer be rewarded for " uniqueness " not generated by Ai systems. The reliance on " activity " in the creative process ( and where generative Ai output is used to evaluate and increase " uniqueness " ) regardless of exact uniqueness becomes an issue.

Where specific and known product development lifetimes ( of use ) and value were previously well know ( and in some cases lengthy ) the time window for " newness " to leap over existing XYZ new product development efforts is shrinking at an incredible pace. Why? Because uniqueness ( in many aspects ) can no longer be protected and where generative Ai becomes both the emancipator and the limiting factor to ownership of breakthroughs.

 

                    

   

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Does Innovation Theater + Innovation Choir = Innovation Compounding ? Often.

For almost 25yrs, a simple seminal study tied innovation ( and in it's loosest definition ) to the capacity that in order to increase the acceptance of what was considered " breakthrough "  when future backward consistent group coordination was at play, the reality became that this is innovation compounding. And, when it's executed as a group multiple ecosystem effort where this can signal a dilution often it becomes a further concentration of said breakthrough / collapse of value chains thus very closely mirroring the exact definition of innovation. Most of the time.

In Competition, Innovation And Increasing Returns we see the underpinnings of the reality that ( and from many other past articles about similar topics ) that the idea of consortia, vertical ( and known ) where specific functional user groups that share a collective need and also acceptance of risk in the face of future specific 3, 5, 10+ year time frames, mean category-defining transformational capabilities have a tendency to become real world applicability much sooner than expected. With Futures Design tools and foreseen futures that codify the barely define into future functionality that is buildable ( if not fully usable ) today the process feeds upon itself if and only if end users see " the inevitable " that is on the way, eg. connected computing, wireless communications, neural networks, non von Neumann computing architectures, leading in no short form to synthetic biological computing.

Where this has been referred to as Skunkworks Singularity efforts, it is the capability and necessity to broaden and codify the unknown into the shortly doable ( even in it's most rudimentary forms ) that allows a choir of similar voices ( and which can easily be competitors ) to push acceptable use into broader awareness. What become particularly interesting is how organizations ( internally as in the capability of intrapreneurship ) also past a certain size become, themselves ( due to their reach across multiple and diverse areas of industrial reach ) become a choir of their own coordinated capability.

In the case of  Amendola, Gaffard and Musso's findings we see that this can not only be something that takes place inside one organization but sometimes across multiple organizations and even when incrementalism is lauded as breakthrough but only when ( seemingly ) these innovations are consistent. Consistency itself becomes a form of innovation realization., What can be ( and is often the case ) ignored are how these " breakthroughs " are a function of acceptable ( in relation to Physics ) doable output that can be tricked out as if a golden path were already laid. Examples of this can not only be seen in the evolution and adoption ( in the sense of the long tail model that is investigation and discovery ) of neuromorphic computing ( a completely different form of the current, silicon based, von Neumann computing architectures ) and, clearly, the use of standard silicon based computing architectures. Where Neuromorphic computing diverges from the standard paradigm a new future, a wholly, self contained 3rd self operating system ( and the hardware to support it ) is just one example of the compounding that that is present and evolving as we speak.

 

                    

   

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Collaborative Cognition = Unblocking Uncertainty

When the absence for consensus becomes the limiting factor to hurdling innovation roadblocks, what other mechanisms ease collaborative cognition ? Here's several for innovation plasticity.

In the race for interconnected innovation instances that continually lead to further convergence ( as divergences are a daily occurrence and also part of the design, engineering and innovation process ) we see that so to enable alternative mechanisms for lab based breakthroughs and to make it past the gauntlet of ( within large organization processes ) well honed, ' hold on, explain how that will work with / within my group ' situations, the key to success often resides in not only collaborative underpinnings but also the unblocking of known or subconsciously accepted risks. This is often separate and unrelated to enumerating the steps and changes necessary to make a specific modules work, solving technically ( and temporarily ) " impossible " situations and dealing with lab bench challenges. It is the steps in-between lab bench science and manufacturable usability that these challenges ultimately rear their ugly head.

Where we see this particularly well articulated is how Systemic Innovation Designers Through Informal and Collaborative Activities drive formal and specific processes which allows for the quantization of ever changing user attitudes often reflected as ' needs ' in certain circumstances: sometimes early on in the design processes. This is embodied in the further process of transversal competencies mediated by digital tools: telepresence, simultaneous collaboration, and synchronous and asynchronous communication which ultimately ( if done properly ) lead of convergences through a systematic peristalsis. When pushed or more aptly in today's language, " enabled " through effort.

This has been echoed for more than 20 years ( ten proceeding the original publication and then after ) where in Facilitating Innovation Through Cognitive Mapping of Uncertainty we see the systematic need for specific Skunkworks frameworks that can encompass the incredible level of uncertainty in early stages of defining breakthrough efforts ( from lab bench science ) through the engineering process. This mixing and cognitive separation, refinement, leads to the formation of what to do, what not to do weavings allowing the underpinning of what some have referred to as likeness lillypads - allowing the further connection between what has worked, may work, cannot work, and will not work environments. Moreover we see how an originally seemingly impermeable footpath to alternative future scenario directions can and often does allow for existing and transitionary system to take hold to forge those paths, and which some refer to as innovation plasticity.

With the notion of breaking barriers ( both conscious and unconscious ) in not only end users but to those involved in the delivery of specific components / end user products as the key factor to fostering the highest levels of convergence capabilities inside and post lab bench science validation, it seems there are many keys needed to increase the unblocking of uncertainty and which means an adherence to the need to foster ( at every level of the innovation effort ) a constant and clear mode of collaboration as well as a willingness to bend the rules - yet another type of innovation definition.

 

                    

   

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