Overcoming cognitive architecture paradigms for the evolution of decision science

Few problems present themselves as complex, in the real world, as decision-making, opening up a large field of opportunities and threats for organizations, which need decisions to be increasingly effective so that their strategies generate the expected return.

In this sense, decision science, much more than data science, seeks a new generation of technologies based on the recent evolution of artificial intelligence, opening doors for investments in structures oriented to continuously and increasingly improve collective intelligence and reasoning.

However, I think that there are several scenarios and options for the decisions of choosing building blocks and decision science tools, which are a paradox because if there are limits and paradigms at the origin, it is difficult to find new ways for the participation of machines at the autonomous decision level in the processes, especially when they involve a more general view of problems.

For instance, there are several limits imposed by the perception that copying brain structures, even when we reach the level of neuromorphic computing and spiking neural networks can lead to better cognitive architectures, mainly considering that we are on the path that corresponds to human cognition.

Therefore, it is necessary to find new ways to overcome the paradigms of the cognitive architectures for the evolution of decision science, including in terms of models of neural networks.

One of my proposals in this regard is the creation of networks with multiple propagations, not only in the training stage but since its construction, in order to open doors to break the brain and mind paradigm.

And, in practice, the collective intelligence processes are facilitating components for this, since they open doors to new types of reasoning, both in a hybrid way and independent of the current patterns based on models that only imitate the structures of our neurons and are adjusted to meet specific machines representations with better quality.
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By Rogerio Figurelli at 01/16/2021
Senior IT Architect & Solutions Consultant
https://www.linkedin.com/in/figurelli/