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Last fall I had the opportunity to attend the EmTech conference at MIT Media Lab in Cambridge Massachusetts. Aside from the usual great talks on everything from wind power to space exploration, there was a specific talk that stood out to me.

Professor Hugh Herr, the Co-director of the K. Lisa Yang Center for Bionics at MIT, presented his personal experience using prosthetic limbs and the role of AI in creating an optimized experience for its users.

At the conclusion of his discussion, he discussed the road ahead for prostheses and his own ambition as its beneficiary. Using an analogy of autonomous vehicles, saying: “I don’t want to drive the car. I don’t want to be a passenger in the car. I want to be the car.”

The road to today

Euphoria for new technology will ebb and flow. In the early days of AI, it was widely believed that we could build artificial general intelligence (AGI) which mimics the biology of the human mind and its synapses. In this form, the artificial “brain” could grow and adapt based on its own experience and outcomes.

In those days, the computing power was not adequate to come close to this vision, and we passed into what was considered an “AI winter” when funding (especially government funding) was significantly cut in favor of more achievable pursuits.

Later innovations in AI followed a path closer to the mathematical structures of the logic and circuits upon which modern AI was eventually built. These generated optimizations through techniques like gradient descent (to reduce error in supervised learning) and distances as a measure of similarity (to define clusters in unsupervised learning). Upon these foundations we’ve since built recursive and ensemble approaches with great complexity such as neural networks that are now coming close to achieving “human-like” outcomes.

At this moment, when AI can effectively drive our cars in many if not most circumstances, and (through new technologies like ChatGPT) seem to think, feel and empathize, AI is often passing the Turing Test–passing as a human in an interaction with a human. It’s forgivable then for one to think that we might be approaching a moment when AI can surpass human intelligence, an oft told trope in the daily media deluge on the topic of AI.

Pairing AI with Humans

However, in practice today we see something dramatically different. Having the benefit of working at a global consulting firm, where we address the AI needs and strategy for our global clients in various industries from retail to agriculture to healthcare, we see how AI is being adopted in meaningful ways with stakeholders who require market validation on a daily basis. In not one of these projects over the past 25 years) have we seen AI “replace” humans. In fact, the primary predictor for the success of AI is its ability to integrate into organizational processes and human activities.

Human+AI systems are outperforming any system using one alone. For example, a human radiologist is limited by the number of cases she can evaluate in a day. AI is not. However, AI cannot make a final decision with regards to a course of care. Therefore AI operating as a classifier for medical imagery can greatly reduce the workload of a radiologist by removing all but the most challenging diagnoses, albeit with a high rate of false positives by design (better to flag a tumor and be wrong than not flag a tumor and be wrong.) The medical expert can then focus her energies on the more challenging cases, and be more productive in the validation of true positive classification. Human+AI wins the day and saves a life.

Human+AI systems are seamless. Just like Hugh’s vision for the future of bionics, the advantages of AI within the system should integrate in a way that does not disrupt the goals of the human. The attention should remain focused on the outcome and not require a complete overhaul of the existing system, which inherently contains known (and even unknown) benefits based on the organic nature of its development. AI should be invisible from the outside in the context of the Human+AI system.

Imagining a future state by looking back

In an October address, acclaimed Stanford professor of computer science and Co-Director of the Human-Centered AI Institute Fei-Fei Li summarized this concept succinctly: “AI should be augmenting and not replacing human capabilities.” Looking at AI through this lens, AI becomes, even in fully automated systems, the recommender, giving its human trainers and operators the final say, all the while endowing humanity with the ability to increase both the velocity and quality of our endeavors.

In this regard, augmented reality (AR) and virtual reality (VR) may have been false starts. While there are certainly practical applications for these technologies, they do not represent the end state for Human+AI systems, rather just one use case, by adding information to the human field of view (AR) or offering an alternate viewing space (VR). With AR, we can see buildings that don’t yet exist or additional information about the built world in the context of reality. With VR, we can defy the limitations of physics and reality to be nearer to those we work with and access worlds limited only by our imagination. However, these scenarios are primarily focused on consumption, whereas most enterprise applications are in the domain of creation. For enterprises operating in the real world of creating and delivering products, services and experiences, Human+AI systems that truly deliver, are those that snap seamlessly into existing processes like demand forecasting, resource management, manufacturing, shipping, maintenance, customer support, and more.

At the advent of the internet in the mid-nineties, companies were grappling with how to integrate the web into their existing businesses. Analog incumbents in retail scrambled quickly to build an online presence to combat the increasing market share of online-only retailers. E-commerce was seen as an additional revenue stream vs. the traditional brick- and-mortar sources. Today, we rarely differentiate e-commerce from commerce. It’s just commerce.

Similarly, cell phones were initially an additional way to communicate (albeit more expensive) than traditional landlines. Now, we don’t differentiate between cell phones, they’re just phones.

What's next

As we head into 2023, we can see a similar pattern emerging for AI. Instead of artificial intelligence vs. human intelligence, the focus should instead be human + artificial intelligence. Or perhaps, just intelligence.

Beyond AI, we will no longer think of AI-enabled and non-AI enabled. Recent advances in cloud computing and publicly available AI models and services make the very best AI solutions available to everyone, from consumers to businesses of all sizes. It will be expected (and required) that AI be integrated into all of our transactional systems, entertainment, and day-to-day activities upon which we base our lives.

Intelligence can be held to a higher standard through the integration of technology. Soon, we will be neither the passenger nor the driver of AI.  Beyond "artificial intelligence", this will just be "intelligence".

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