Today I am giving a keynote at the 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology, presenting some of the outcomes of the IEEE FDC Symbiotic Autonomous Systems Initiative.
Here a summary of the points I am making.
We have experienced a significant evolution in the capabilities of machines (artefacts) over the last 250 years with an incredible acceleration in the last 50 years, thanks to electronics and software. This evolution is going to continue, and accelerate, in the coming two decades leading to machines as “smart” as humans.
At the same time the human species has augmented its capability in various areas, more than doubling life expectation over the last 100 years and individuals have learnt to leverage machines as never before to improve their life, their performances and extend their knowledge. This is also expected to progress in the coming two decades to the point that the boundary between humans and machines will become, in many instances, fuzzier and fuzzier, partly thanks to the growing use of digital twins.
The progress seen in the last decades and the one expected is reshaping the idea of transhumanism and it is making it much more concrete.
The IEEE Future Direction Committee had an Initiative, Symbiotic Autonomous Systems, that worked on these aspects and that is now taking further steam by joining the Digital Reality Initiative aiming at fostering the Digital Transformation in its many facets.
As a matter of fact the Digital Transformation is shifting the focus from a micro to a macro view of business, hence taking a global view at machines involved in business (production, transportation, delivery… and end user) processes. Whereas in the past the innovation focus was on a single machine, the Digital Transformation shifts the focus to the overall process, to the many machines involved, their mutual interactions and the interaction with humans.
The resulting effect is that the augmentation of a machine is no longer an internal aspect, rather it derives from its interaction with the operational context (and other machines/humans active in that context).
Although hardware improvements remain important, they are more an enabler than the actual reason of machine augmentation. This latter is depending more and more on software, data analyses (includes artificial intelligence) and communications.
The hardware is getting better in many aspects, from the raw materials that are no longer taken off the shelf but designed to deliver certain characteristics to the production processes, like additive manufacturing, making able to create structures that were simply not possible in the last century.
New “hardware” is also multiplying the number crunching capabilities, stretching the Moore’s law to its physical (and economic) limit and circumventing it by moving to different computational architectures and new processing substrata. In turns, these ever increasing number crunching capability coupled with the ever increasing volumes of data enables data analytics, reasoning and the emergence of “intelligence”.
This leads to smarter machines embedding awareness and intelligence, able to share and learn through communications and to evolve through adaptation and self replication.