Before the advent of the internal combustion engine and the harnassing of electricity, individuals were not the sole proprietors of society. Prior to the mid-20th century, horses were ubiquitous, serving in tens of hundreds of thousands across various industries. In the United States, the number of individuals affected surpassed 24 million, a figure roughly equivalent to the current workforce in the healthcare industry.
The draft animal population, comprising mostly horses and mules, surged sixfold over the 60-year period from 1840 to 1900, expanding from a mere four million to an impressive 24 million. As the global population increased by just threefold over that period, this rapid growth far exceeded any corresponding expansion in humanity. By the year 1900, a remarkable ratio existed in the United States: approximately one horse or mule per every three individuals. Most working animals toiled away in urban areas and their nearby rural zones. The most effective utilisation of animal power was seen in agriculture and transportation.
Within urban centres, horses had long been the primary mode of transportation and mobility, serving as a vital lifeline for centuries. Prior to the advent of horseback driving itself, alternative transportation options existed in the form of public omnibuses, non-public coaches, and ride-for-hire taxi companies, with roots dating back as early as 1605 in London. These included four-wheeled hackney carriages and later, two-wheeled hansom cabriolet carriages, offering citizens a range of choices for getting around the city.
A shift from horsepower
By the early 1960s, the advent of the internal combustion engine had significantly reduced the number of horses of burden in the United States to a mere six million. Determined by estimates, the current population of working draft horses in the United States has declined significantly, now comprising around 1.5 million individuals out of a total equine population of approximately 10 million, with the majority being kept as pets or used for competitions.
In Europe, the narrative is eerily familiar. By the early twentieth century, England alone was home to over three million working horses. By the early 20th century, the global population had plummeted to roughly two million within a quarter-century, despite the significant impact of the First World War’s loss of human laborers and the devastating flu pandemic that ravaged the world between 1918 and 1920, claiming an estimated 25 million to 50 million lives.
A century later, by 2020, the estimated population of horses has dwindled significantly, now numbering around 160,000, with approximately 70% serving as beloved pets and the remainder primarily devoted to pursuits such as racing, mounted police services, and brewery haulage. Almost entirely absent from modern-day work, the horse population has plummeted to a mere fraction of its former numbers, with tens of hundreds of thousands once employed in various capacities.
So, what occurred? Automated motion occurred. Prior to the invention of the internal combustion engine, reliable technology did not exist for transporting and hauling hundreds of people or goods from one location to another, apart from by rail. In urban centres during that era, the most pressing threat to metropolitan life was the rapid accumulation of horse manure, a byproduct of the reliance on equine transportation. We swiftly transitioned to our cellular network via the in-car system at the earliest opportunity.
We’ve successfully proceeded to the next stage. We’re developing a comprehensive suite of applied sciences that enables vehicles to live up to their name with even greater precision and accuracy. “Initially, ‘auto’ referred to a self-propelled carriage, implying independence from horsepower.”
As automation takes hold, the term “auto” has taken on a new significance – no longer referring to the freedom from human control in cars or other machines, but rather signifying a state of independence from the shackles of human oversight altogether. It’s expertise by itself, operating below its personal capacity to produce meaningful results. As transportation continues to evolve, it’s becoming increasingly innovative. As the effects of this technological shift reverberate beyond the realms of travel and logistics.
From manpower to machine-power
Until recently, expertise was seen as a tool. One of the most significant benefits of human innovation is the creation of tools that enable us to perform tasks more efficiently, effectively, and quickly than would be possible without them. However nonetheless, we used expertise.
What’s new with AI is that we’re no longer confined to inventing novel tools to augment our capabilities and facilitate task execution. A robotic workforce is being developed to take on tasks and responsibilities previously handled by humans. The development of this pattern won’t be definitive, as we continually strive to build upon earlier scientific advancements that have already contributed to our work. For instance, manufacturing facility automation has its roots dating back at least two centuries. While we’re building a more affordable, prompt, and expandable workforce rather than a toolset, we must ensure that our approach is aligned with the evolving needs of the industry.
The emergence of a new workforce won’t lead to an immediate replacement of everyone in the near future. The fundamental reasons behind this notion can be distilled into two primary factors. While the excitement surrounding AI may have reached a fever pitch, it is essential to acknowledge that its current abilities are still largely limited to narrow, rules-based applications (for instance). Video games, where they can potentially excel beyond even the most skilled human players.
Specifically, this platform appears almost enchanting in its capacity to transform written content, images, and even video into engaging and shareable media. While AI’s inability to comprehend the nuances of its own output, coupled with the vastness of knowledge required to train its models and the sophistication needed to coach its designs, undoubtedly restricts it from fully replacing human workers.
As artificial intelligence capabilities continue to surge at an exponential pace, year-over-year advancements have become increasingly dramatic. Through strategic partnerships, companies make informed decisions that benefit both their bottom line, society, and the environment.
Notwithstanding these findings, only around 30% of top-tier executives reportedly harbor confidence in their organization’s transformation prowess. Few organisations successfully adapt to transformation. Combining AI with various methodologies proves potent, as it tackles the two primary hurdles hindering widespread AI adoption: knowledge silos and software integrations, ultimately yielding enhanced decision-making capabilities.
While AI’s potential to augment human capability is undeniable, the actual deployment of these technologies will be slowed by the time it takes for institutions to fully understand and integrate their applications? As the COVID-19 pandemic reached its peak in 2020, many college districts and companies were forced to shut down operations abruptly, despite having had access to online capabilities for over 15 years.
As laggard consumers hesitate to adapt until faced with an existential threat, their tardiness will reverberate throughout the system. Only approximately 16% of the 1,000 organizations examined by the marketing consultant distinguished themselves as leaders capable of effectively navigating the necessary changes required for AI adoption in a corporate setting.
As we navigate the transition, we can closely track the seamless incorporation of AI into the workforce, and ultimately, the predictable reduction in human staffing levels as AI becomes increasingly cost-effective, efficient, and accurate in performing various tasks.
While it is possible that AI may generate novel options beyond our current imagination, these innovations will not necessarily yield additional human equivalents. As emerging technologies rapidly unfold, we may witness a surge in job opportunities, as not all innovations will progress at the same rate and may require our expertise to function effectively.
The machine-powered ecosystem
Inevitably, a day will come when the autonomous era dawns, marking a turning point in human labor, with the measurement of productivity becoming as abstract as horsepower currently is.
Surprisingly, we’re likely to be taken aback by the sheer magnitude of a standard robot’s capabilities. As productivity metrics evolve, we’ll witness the dawn of a novel gauge: “machine energy” or its variants. This initiative aims to signify the unprecedented capacity for machines to perform tasks previously thought to be exclusive to humans – with greater precision, speed, and cost-effectiveness. As machines increasingly augment human capabilities, professionals will face an unprecedented array of complex tasks requiring heightened expertise, precision, and adaptability – with multiple variables to consider, intricate synchronizations to manage, and compressed deadlines to meet.
The advent of self-driving taxis marks a significant milestone in the evolution of the centuries-old ride-for-hire industry, which has transitioned from relying on human drivers and traditional “horse-powered” vehicles to embracing innovative machine-based technology. Managing independently owned and operated businesses will also be an option.
This shift may have profound and far-reaching societal repercussions, extending beyond the confines of this narrative. Ultimately, as a society that values progress and efficiency, we may find ourselves following the path of technological advancements like those that have led to the development of artificial intelligence and self-driving cars, which have revolutionized industries such as transportation and logistics. As the global population shrinks, individuals will enjoy longer lifespans and greater well-being. As soon as our employment no longer defines our path, we’ll need to seriously explore one “role” – finding a fresh sense of purpose and fulfillment.
As we collaborate with co-author of and , we’re developing a comprehensive framework for showcasing the diverse array of capabilities AI can demonstrate in achieving complete autonomy within an office setting. Within our existing autonomous driving infrastructure, we have been inspired by the SUDA framework, specifically its Sense, Perceive, Resolve, Act model, which was prominently showcased in our bestselling publication “Boundless”, and are integrating this framework seamlessly across all stages. The publication will take place swiftly on ZDNET.
