Where machines and people merge
How humans and technology co-exist in the workplace continues to confound
September’s theme looks at interactions between technology and humans
The ways machines substitute for or supplement labor is evolving rapidly
Societies are struggling with aging populations & shifts in employment models
Machines and humans have different strengths and cost structures to consider
There is a key philosophical divide between augmentation and automation
Different decisions are inevitable and vary by industry, society, and culture
Machines and humans in the fast food industry
Ahead of Labor Day, this week the California Legislature passed a bill targeted at improving worker pay and conditions in the fast food industry. If signed by Governor Gavin Newsom, it will be the first law of its kind in the United States that creates a council to regulate wages and working conditions in the fast food industry. The bill, which was supported by labor unions and opposed by business interests, proved divisive as it passed the Senate with the minimum number of votes required. It is targeted to help labor advocates gain ground in their efforts to support over 500,000 non-unionized low-wage workers in the state. Originally sweeping in the conception of its powers, the proposed council’s scope was narrowed through negotiations in an attempt to address some of the concerns raised by the businesses impacted. Supporters point to the need for California to address concerns over wage theft; opponents point to the increase in costs that will add to already high inflation.
What is missing from this debate is a discussion of what the future of work in the fast food industry will look like. As with virtually every industry, the increasing sophistication of technology and changing consumer preferences is changing the nature of work itself. I recently took my daughter to breakfast at the McDonald’s near her school and we used touch screens to place our order. After making our selections including customizations, we took a number tent and cups to fill our drinks at the beverage stand, then waited for our food to arrive. Someone brought us our food and we enjoyed our breakfast, cleaning up our table after and disposing of our trash. The interactions we had with workers was literally two seconds during the entire visit.
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Artificial intelligence vs. intelligence augmentation
I recently read the book Machines of Loving Grace by author John Markoff, who has chronicled decades of news and change from Silicon Valley. In the book, Markoff focused on the ever-evolving relationship between machines and humans in the workplace. He distinguishes between two camps who have been working on advanced technology for decades: artificial intelligence (AI) and intelligence augmentation (IA). Simply put, the main difference in the approaches is the role that humans play: in Markoff’s depiction, IA firmly emphasizes the need to “keep a human in the loop” and design machines to support or “augment” human intelligence. By contrast, AI seeks to replicate the sophisticated mental reasoning that humans are capable of in technology, but does not explicitly carve out a role for humans.
A good example of the difference between IA and AI is work that has been done on driverless vehicles. Initial efforts focused on having a driver present in a supervisory role, ready to take over if the technology failed. Later models have advanced capabilities along the 6 levels of vehicle autonomy to achieve Level 5 fully autonomous vehicles which require no human intervention. Earlier this year, the National Highway Traffic Safety Administration (NHTSA) in the U.S. legalized the use of self-driving cars and trucks with no steering wheels or pedals on American roadways. While none of these fully autonomous vehicles are yet available to the general public, the move by NHTSA provides guidance to manufacturers on the required safety standards and paves the way for when advancements in technology reaches maturation. Fully autonomous vehicles highlight an AI approach, while the Advanced Driver-Assistance Systems (ADAS) common in vehicles today showcase an IA approach.
Where do you put the people and the machines?
Increasingly, advancements in a range of technology solutions in a wide variety of contexts are forcing organizations to contemplate radical changes in their workflows. One of the most pressing questions that companies must answer today is: where do you put the machines and where do you put the people? Both are still needed - and will remain relevant for the foreseeable future - as humans and machines have different strengths. Machines are terrific at computations and never lose productivity from fatigue. By contrast, humans have amazing visual perception and spatial awareness as well as providing empathy and context. Humans are remarkable at identifying patterns based on their perceptions and using context clues; machines have made remarkable advances over the past decade in finding hidden patterns in large amounts of data. Machines are getting much better at using unstructured data such as images and videos at scale to quickly detect common features. Robots are being deployed beyond traditional applications in manufacturing, moving into service industries such as caring for the elderly in Japan that have historically been the exclusive domain of humans.
Much has been written about the interaction between technology and humans in general, particularly over the past decade, but there is little consensus on what the future holds and how it will develop across different regions, industries, and demographics. The idea of ignoring a person at the register in favor of impersonally ordering my desired food items at a touch screen would have seemed preposterous to me two decades ago, yet to my daughter it seems natural as she interacts with touch screens throughout each day. Different generations are adopting technologies at different rates, and different cultures also impact differences in views on the tradeoffs involved in the AI vs. IA disputes. These unknowns make it challenging to fully assess the implications of business decisions and policy perspectives such as the California fast food bill. Will it better protect workers or hasten the adoption of machines to replace them? As wages rise and the cost of technology falls, will this hasten the replacement of humans by automation or the augmentation of their roles? Across all aspects of society, we will return to the fundamental question of where we put the machines and where we put the people continually over the years to come.
How has the adoption of technology changed your work recently? How do you evaluate and decide which technologies to adopt? What do you see as the strengths of machines and humans? Where do they work well together in your view? How often does your organization re-examine the mix of machines and people and reallocate? Do your people need additional training so they can better leverage new technology? What preconceived notions do people in your organization have on the tradeoffs involved? What examples have you seen where technology is doing work you thought a human would always perform?