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Automation without Orchestration?


AI Operates in an ecosystem; not Automated in a Factory


Approaching the topic of Artificial Intelligence needs clarity. Apparently, Stephen Hawking, the Nobel Laureate Physicist told BBC in a 2014 broadcast Program that “The development of full artificial intelligence could spell the end of the human race.” We really don't know the context of why he said what he said, but without trying to make too much meaning into it, on the surface, it is a good thing if he meant the end of the human race as we know it today. A race that has more often destroyed than created sustainable ways of improving the Quality of Life in the history of this planet.


What if, the entire focus of artificial Intelligence, was regulated and limited to Applications that respond to Creation censuring the applications that could potentially lead to destruction.

In order to even get there, shouldn't we have a commonly agreed definition of what Artificial Intelligence is? The very approach to Artificial Intelligence from a financial perspective first rather than a human perspective is a real problem. We need to reverse that to see a more creative advancement of Artificial Intelligence adaptation. The four commonly accepted approaches that have evolved to the adaptation of Artificial Intelligence (AI) are:

  1. Machines replicating human behavior (EX: Robots).

  2. Human - Device Interaction that alters the method of Computing (EX: Automation / Robotics).

  3. Machine Learning / Deep Learning to drive decision making in Automation (EX: Pervasive Computing)

  4. Collective Intelligence to alter human behavior (EX: Augmented / Virtual Reality).

What is a common factor to all the above four approaches is Computing. And Computing is facilitated by processing chips essentially driven by Logic and Rules of a Process. Which in turn drive Programs. The challenge is to make these Programs operate on dynamic code; not static code.


As Science should precede technology, we need to understand that the human brain which is an engineering marvel computes based on the neurological impulses it receives (Sensing / Logic) and altering its established patterns ( Habit / Patterns / Rules). It will probably be well nigh impossible to reverse engineer the human brain but definitely possible to complement it by increasing the Computing / Processing Precision, Accuracy and Efficiency mimicking the neurological responses (Logic & Rules) any computer would need to create Intelligent Process Response.


The biggest fallacy in the understanding of Artificial Intelligence is that it is a mechanism for Automation. Quite to the contrary, it is a mechanism for Orchestration. It is Orchestration that will lead to successful Automation and not vice-versa.

The first principle in Designing & Architecting the success of Artificial Intelligence (AI) is making a distinction between Systems and Objects. This will help realize the difference between the Engineering that Purposes Solutions in a System and Industrialization that Proposes Applications in the form of Products and Services (Objects) to Segmented and/or Cohort of Customers / Consumers.


The former Visualizes and Connects the Life or Human Ecosystem; running the process of Education, Ownership & Commitment with Customers / Consumers Catalyzing them through Alpha, Beta and Theta states. The latter inherits and Connects Systems and Shapes the Industry and Customer Ecosystems; continuously improving the Rate of Institutionalization / Innovation.


The purpose of AI is to bridge the gap between Potential & Performance of Human Endeavor


Learning is and should always be at a Systemic Level (Free of Constraints) while Training and Practice will be at a Systems' Level (Ability to understand and relate to the constraints). The Fusion between the Systemic and Systems' level is also the Fusion (Not Integration) of People and Technology to enable Innovation; where AI can help in the process of overcoming the constraints (Risk of Failure) and increase the threshold of Capability (Risk of not overcoming the constraint) and thereby contributing to Sustainable Innovation.


It is essential to understand that Systems Connect Ecosystems dynamically through the Fusion of People & Technology because the Logic inherits Learning and Rules inherit the logic to drive Training & Practice; fusing People with Technology. Objects on the other hand Integrate People & Technology statically because the hardwiring of object configuration.

BMW Visualizes a Pathway, a Locomotion Experience, a Lifetime Engagement of Attracting, Interacting, Contracting, Servicing, Retaining its Customers & Consumers on a Lifetime basis. Only then does it even consider the Engine, Components, Connectors for that Locomotion Experience & Engagement builds its assembly lines for Manufacturing & Distributing Product and Services.


We crave for intelligence to reduce the Variability at meeting Life's Aspirations at a Conceptual Level and increase efficiencies at the Industry level. Variability is a foe when one thinks of everything from a financial ecosystem perspective and a friend when one starts using it from a human ecosystem perspective. The entire debate on Artificial Intelligence must therefore boil down to the following three P's:


  • Profiling: Is necessary to create Sustainable and Consumer / Customer Lifecycle Products. But the data collected must be owned by the individual to whom it belongs.

  • Personalization: This must be from the Lifetime Value of the Customer Consumer intersecting the Lifecycle of a Product / Service and not the other way round; as is prevalent today.

  • Preferentiation: The device, channel and medium independent engagement must truly liberate Consumers / Customer from the bondage to branded experience and access that is independent of ownership.


Here are examples of understanding the three examples of ecosystem mentioned in this article and how fusing People and Technology with Intelligence can improve the Quality of Life:

  1. Music Conceived, Created and Consumed in a Digital World Collaborating & Sharing across an Ecosystem of Team Members, Consumers (Clients), Customers (Producers / Distributors), Vendors, Shareholders, Stakeholders, Business Partners (Promoters) Society (Regulators, Government) and Machines (Computers, IoT, Wearables, Devices, Digital Display Boards, Sensors, etc.).

  2. Music is aggregated for Production & Consumption across device, channels & mediums is an industry ecosystem.

  3. Musical Experiences are converged with Music Aggregation and Music Creation are Digital Life Ecosystems that bridge the Physical & Virtual divide.

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