Autonomous systems may our innovation trump card

Innovation needs a PR rehaul. AI—somehow a black swan, grey rhino, and white elephant, all in one inorganic entity—is doing a fine job turning legions into futurology cynics. This should not be ignored. 

Neither should truly exciting innovation; in my view the most exciting upgrades to society today are down to autonomous systems. 

By definition these systems operate independently of direct human control. They are built to integrate intelligence and can adapt to changing environments, performing complex tasks and achieving goals without constant supervision. Self-driving cars are an obvious and increasingly visible example. Less visible but for more impactful, smart factories show the combinational power of parallel trends: AI models utilise advanced pattern recognition to diagnose issues in a machine repair assembly, before AI agents autonomously create repair plans, oversee quality checks, and order parts for repairs, and robotic arms independently perform mechanical repairs; AI, agentic AI, and robotics, within one autonomous system.

Extrapolate this into personalised medicine delivery, for example, or the “organic growth” of smart cities in regions of dynamic demography, and a vision for the future becomes that much more tangible. It is what  a futurist would call a systems-level reimagination. A lay person may simply call it decent change.

But accelerating autonomous system design and growth—generating more decent change—is not about more intelligent software. Quite the opposite. True autonomy is the product of that phantasmagorical brew of sense, connectivity, compute and control, in harmony. This harmonious quartet is also created as layered, secure, and context-aware. Ask your nearest systems engineer: these are six traits necessary for an autonomous system to perceive, communicate, be cognizant, and act. 

What they may not know is that the most advanced autonomous systems in the world is far closer than we think: the human body.

Human senses are machine sensors. Cameras, LiDAR, biosensors, tactile arrays, these all stream data that shape how machines perceive the world. Rich, multimodal input determines the fidelity of perception and, ultimately, the quality of decisions.

Connectivity forms the system’s nervous system. 5G and 6G networks, time-sensitive links, optical and in time quantum channels transmit information across machines and domains (securely, with low latency) enabling coordinated, distributed intelligence. 

Our brain is the system’s computing layer: where data becomes insight and insight, action. Distributed across edge, cloud and embedded systems, this infrastructure today draws on AI, neuromorphic processors and agent-based models to reason, learn and adapt in real time.

And robotic limbs and machine interfaces, which industry observers call actuators, carry out decisions. They are the system’s muscles, closing the loop physically between sensing and impact.

Autonomy, like its far superior innovation, the human body, is multi-disciplinary. To build it, we require skills in wireless, AI, edge computation, control theory, robotics and security. Based on how we need it to scale I would argue we also need bio-engineers, neurologists and anthropologists. 

This type of industry-wide proactive bio-mimicry isn’t just good design practice based on sound and observable data. It brings together very different types of skill sets that will be needed to help society reorganise itself in the intelligent age. 

What’s more, how elegant and right it is to be reminded that one of the surest ways to design a better future for ourselves is to use our own human body as its model. I wonder what the futurist cynics would make of that PR pivot?