The Onward March of Artificial Intelligence

The Onward March of Artificial Intelligence

More than just ordinary tools, in most cases your electronic devices can perform a series of tasks better than you can. Computers gain competencies daily in a variety of fields. Autonomous software agents trade on the floor of the New York Stock Exchange. NEST security cameras distinguish between faces as they sort familiar features from unfamiliar ones. Precision agriculture combines data collected by IoT (Internet of Things) sensors with real time analytics to offer management recommendations within a matter of seconds. Machines are becoming so good at a diversity of jobs that before long, one might slip discreetly into your desk chair at your office.

But wait, we are not there yet! Authors Paul R. Daugherty and H. James Wilson in their 2018 book, Human + Machine, recognize the mix of sentiments triggered by the ubiquity of machines: on one level dread, at another level, measured anticipation. From a historical perspective, the authors identify three “waves” of machine involvement in modern life. The first wave brings to mind Henry Ford’s assembly line; the era ushered in the standardization of rote tasks. The second wave, capitalizing on the advances of IT, introduced automation to more processes within a company, leading to greater efficiencies and growth. The authors describe the third and present wave as one where human and robot work in partnership. Each takes advantage of the strengths the other brings to the workplace. The authors call this the new “renaissance of human labor.” They claim the company that explores the potential for collaboration between robot and human will reap competitive advantages in the 21st century.

The Power of a Well-Trained AI System

The beginnings of artificial intelligence (AI) can be traced back to the 1950s when the Department of Defense trained computers to simulate very basic human reasoning. The “personal assistants” that share our lives today in the form of Alexa and Google Home originated some fifty years ago when DARPA (Defense Advanced Research Projects Agency) produced robots with similar, albeit less developed, capabilities.

AI refers to a computer’s ability to replicate some of the processes typically associated with the reasoning and problem-solving abilities of a human being. A computer with AI, specifically machine learning (ML) capabilities, has the cognitive ability to process large quantities of data, analyze past and present experiences, and adapt its behavior or outputs to new information. Equipped with deep learning algorithms, massive data sets and the sensors that allow them to work in closer proximity to people, the manifestations of AI on the factory floor take multiple forms. The “self-adapting assembly line” becomes more versatile, able to customize the work process and react on the spot to new directives. Simultaneously, process engineers and managers are able to devote more time to higher level tasks and analyses.

AI in Partnership with a Professional

Many have pointed out that AI’s strength lies in its ability to complement another core set of skills. Erik Brynjolfsson of MIT sees the potential for partnership between an experienced professional and a highly trained AI application. AI does not have the ability to ask questions, prioritize using a value system, or deliver a persuasive argument. However, AI can deliver real gains in terms of sorting and analysis of data, trends, processes and reports. It provides a third “eye”, an independent stream of information, and insight to complement and inform the next level of analysis. This is where the authors claim the real magic begins. The main question Human + Machine wants you to consider is this: “what happens if you completely rethink your processes around ultra-smart systems? What kind of growth, services, and products become possible?”

An Engineer… With Superpowers

The authors visualize several “fusion skills” that result when robots and people collaborate. In a process described as “holistic melding,” the skill of a trained profession is augmented with AI. Machines learn from the skilled professional and incorporate this expertise into their own knowledge base. An experienced surgeon uses his skill and knowledge to direct a surgical robot during complex surgery. Machine-human teams operate NASA’s exploratory rovers. A civil engineer sorts through AI-generated site designs and injects an additional criterion for analysis. The work product of a smart machine combined with the judgement of an experienced professional can lead to a higher quality product (or design) and outcome.

Managing the Machine

But what about knowing when to step back in? Machines can take a human out of the process, but another necessary skill requires knowing when to bring the human back in. Obviously, machines are capable of complex analysis, but they have limitations in their ability to read all situations. People are needed to provide a framework of oversight, questioning and probing the accuracy or biases of the system. In fact, the authors devote a large portion of the book to describing the many new positions that will need to be created to oversee a greater machine presence at work, from the “sustainers” that know a machine’s limits to those that review the quality of the data and the decisions made.

Imagining the “Sweet Spot” of Human, Machine Collaborations

Don’t fear the robot occupying your desk chair in your office, he isn’t there. Rather, make AI enabled machines and applications into indispensable agents within your company. Daugherty and Wilson’s main point is that collaboration between robot and humans will launch a new age, complete with new jobs, industries and reconfigured business models. Neither the machine nor the human is as effective as when both merge strengths for a single purpose. The real goal is to look for these opportunities. Capitalize on the skills of each and use this synergy to grow your business in revolutionary ways. Age-old business models may topple as companies rethink how best to press forward. But the authors argue that this is ultimately a good thing.

References

Daugherty, Paul R., and Wilson, H. James (2018). Human + Machine, Reimagining Work in the Age of AI, Boston, MA, Harvard Business Review Press.

About the Author Chris Maeder

Chris Maeder

Chris is an experienced civil engineering and software technology leader, with over 30 years industry experience. With proven expertise in global software development, he has built engineering teams that adapt quickly, focus on what’s important and, most importantly, deliver. He is a licensed professional civil engineer with extensive experience in water resource engineering. He has performed and supervised engineering projects in urban stormwater drainage, transportation and roadway drainage, storm sewer design, detention pond design, stormwater quality, green infrastructure, watershed management planning, wastewater sewers, water distribution networks, pump stations, FEMA flood studies, bridge and culvert design, bridge scour and armoring, dam failure analysis, seepage and groundwater modeling, and environmental permits.