The Age of Augmentation and Cyber-Physical Fusion

Today’s tech news cycle is inundated with speculations about both the potential and the consequences of Generative Artificial Intelligence (AI). Reports on this new technology center around its ability to answer questions in a near-humanistic form and do things that were once the sole purview of people. Generative AI can code computer languages, solve math problems, write essays and poetry, and replicate and produce new art in ways that incite fear about the value of human beings in productive and creative domains. This has logically led to concerns about human replacement in jobs, and even about our outright existence.  

Innate fears run deep in the minds of many who take a deterministic view of AI development and see it as a super being leading to the obsolescence of mankind. Stoking these fears is today’s Generative AI and other forms of AI built on Artificial Neural Nets (ANNs), designed to mimic the structure of the human brain, appearing intelligent in their interactions and behaviors. Experts say that if a person talks to AI long enough about particular subjects, the AI will become moralistic and begin to lecture. They add that, at times, it mimics human beings by confidently presenting patently wrong answers. Many believe that AI will be able to pass the Turing Test in our lifetimes. But not all scientists and technologists are fearful, and some new models are being proposed that offer visions of hope. 

The theory of Human/AI Fusion proposed by Dr. Marty Trevino, a cognitive neuroscientist and technologist designing novel Human/Technology and AI fusion models, is being regarded by many as a new center of gravity for future business models, innovation, and solutions to some of today’s unsolvable problems. Trevino says it marks a transition from the Age of Information to the Age of Augmentation and Fusion, explaining that the mating of human beings with technology and AI will produce massive advances in innovation, problem-solving, and wealth.  

“There is a mass incorrect framing of what we call AI—it isn’t Artificial Intelligence in the way that Hollywood portrays its potential, nor does it capture how the human brain functions,” says Trevino. “What we call AI is advanced information processing, synthesizing, and production systems. Artificial Neural Nets (ANNs) only resemble the structure and functioning of the neocortex of the human brain at the highest level of abstraction.”  

Trevino’s theory states that the key to the future is innovation and problem-solving through novel models of human/AI fusion intelligently constructed to enable each to do what it does best and complement the other in a near-symbiotic relationship. At the center of his theory is what he calls The Central Tenet, which argues that the human brain and AI as we know it today are intrinsically different, yet uniquely complementary.  

“This has never happened before in human history—(neither) the Agrarian Revolution, Industrial Revolution, or Information Age offered humanity this unique relationship upon which to build,” he says. 

Trevino also says his take on the human/AI dynamic also extends to Data-Driven Decision-Making (D3M), which has been a coveted goal of many digital transformation efforts, although few if any firms achieve it. He says it has remained elusive due to the over-emphasis on the data, math, and methods of data science vs. a deep understanding of the cognitive neuroscience of decision-making.  

“As we integrate our cyber/physical worlds, we are advancing analytics and machine learning along with a deepening understanding of how our human minds make decisions with data,” he explains. 

The integration of Natural Language AI, coupled with three and two-dimensional immersive visualizations, enables UX/UI design to further the brain’s situational awareness and understanding in natural ways, he says, citing: “Among the novel things we are experimenting with are unique combinations of Spatial, Geo-Temporal 2 and 3D UX/UI designs to enable the human brain to learn and validate its internal models in natural ways such as learning through movement, and the visualizing hierarchical relationships of things and events.” This and other cutting-edge work focused on altering the sensory experience in data and analytics, he says, is offering forward-leaning firms opportunities to create value through data and new models of human/AI complementarity. 

One field of particular importance to human beings’ quality of life and happiness is medicine. It is here that Human/AI models of complementarity arguably offer the clearest path and greatest benefits from novel thinking about humans and AI. The National Academy of Medicine, in its efforts to address barriers and facilitate the clinical adoption of AI in medical diagnoses, states, “AI approaches, specifically machine learning (ML), are especially well suited to the problems of clinical diagnosis, shortening the time for disease detection, diagnostic accuracy, and reducing medical errors. By doing so, AI diagnostic decision support (AI-DDS) tools could reduce the cognitive burden on providers, mitigate burnout, and further enhance care quality. Ultimately, the purpose of AI-DDS tools is to augment provider expertise and patient care rather than dictate it.”  

The integration of AI in the field of healthcare has shown potential to augment and enhance providers’ performance. This is where Dr. Trevino’s central tenet comes into focus, stressing that the unique complementary dynamic between the brain and AI can create an order-of-magnitude improvement of a single human’s expertise by performing tasks that do not require human-like cognition—processes like data analysis, cyber security, translation, customer relationship management, and repetitive tasks. By contrast, the human brain performs correlations and identifies critical correlations, time-based relationships, and other abstract concepts, which only the human invariant memory can do. 

“Many are missing the mark regarding their DX and designing firms of the future by missing this central tenet and focusing on replacement vs augmentation,” Trevino says. “Replacement will largely only result in incremental gains where the augmentation of humans with AI will yield quantum leaps in innovation and problem-solving and organizational valuation.”  

“Replacement of people in jobs will occur and is not to be discounted,” Trevino continues. “But it is novel workplace models of Human/Tech/AI Complimentary that will yield order-of-magnitude leaps in innovation and problem-solving and, as a result, be at the top of the valuation power curve.”  

Experts are generally unified in their beliefs that Generative AI and other more singularly focused AI, such as those intended to drive cars, run manufacturing equipment, and the like, are genuine breakthroughs that will profoundly impact our way of life. But are we entering an age where humans compete against AI? Can we compete with something that can do a billion or trillion calculations a second?  

“Many people mistakenly compare the human brain to what we call AI today, and it’s an incorrect comparison,” Trevino explained at the How AI Will Disrupt Data Science event during Los Angeles Techweek. “Of our large artificial neural nets, none of them function in the way the human brain does. They are not intelligent, do not possess knowledge, and do not learn. The human brain is the only general-purpose intelligence machine we know of, and it solves problems in vastly different ways than AI.”  

Next, he’ll expand on his theories at the Mission Matters MxM Future of Healthcare Talk, exploring how, along with more and better data and algorithms, a more precise understanding is needed of how the human brain trusts technology and makes decisions with data.  

Trevino says he’s found that trust in data is categorized differently in the brain than trust in people is. “AI has now become capable of functioning as a complimentary partner to us in solving problems, creating value through innovation, design, and increasing our productivity,” he says. “Regarding human and AI complementarity, we have to develop a deep understanding of how we trust data and technology and how this trust influences our decision types, as not all are the same and the degree to which we accept data in those decisions varies greatly. The implication is, we have to ask bigger questions than how to simply increase sales through data or recommend more items to the buyer.” 

“We are at an inflection point now,” he continues, noting that we’re being given “deep insights into the human factors enabling novel Human/Tech/AI workplace models to be designed. It is these models that will drive humanity’s greatest gains for decades to come in problem-solving and innovation, but it begins now with a central tenet and elegantly simple premise.”