The nature of work is changing. The most important skill workers need is the ability to work well with others. Soon that will include the ability to work alongside autonomous machines and algorithms. Welcome to the new diversity.
Diversity and inclusion remain key to business success, and to social justice. Savvy companies are working hard to make their workplaces more inclusive. They understand the benefit to maintaining their market relevance and to boosting their speed of innovation, benefits that go way beyond any government requirement to meet a statistic. Despite efforts, many industries still suffer a great lack of workplace diversity, whether you consider the dimensions of gender, race, age, or sexual orientation. And we should remain focused on all these dimensions of inclusion. But we must now add another dimension when we think about workplace diversity in the future: non-humans. The most effective teams of the future will not just include more women, more people of color, more LGBTQ, and people of all ages; They will also include robots and algorithms.
You are your network
Prior to the industrial revolution your value as a worker was pretty much related to your physical ability: your strength, stamina and dexterity. With the coming of the Information Age, people were not only valued for what their bodies could do; their value was now measured by what they knew and how well they could create and process information.
We now live in the Network Age. Knowledge is being commoditized and your value is less related to what you know, and more related to who you know, the strength of your relationships, and how well you are able to leverage your personal network to get things done. And that network is now extending to include non-humans.
A considerable amount of human knowledge is now just a click away on any computer. And experience on the job is losing relevance too. Rapid change is making some experience obsolete. And in many areas human judgement made possible by decades of experience is being replaced by learning algorithms that make better quality decisions than humans ever did.
Consider the "merchant prince" in apparel companies. This person uses their experienced 'gut' to decide on the new clothing line that best anticipates next year's fashion trends and the best way to display and market merchandise. These people are already being made obsolete by predictive analytics. The decisions these people make affect the actions of many, many people in a clothing company. Now all those people are essentially being guided by algorithms.
As a result of this commoditization of knowledge and experience, your ability to collaborate on a team becomes more important to an organization than the knowledge you have rattling around inside your head. It's not to say that knowledge no longer matters. Physical attributes like stamina still remain relevant too. But your ability to network, and to put that network to work for you, will be your most vital skill.
The Network Age is upon us. Knowing how to collaborate to find the information you need to get something done is what matters. In many cases, algorithms will provide much of that information to us.
The new diverse work team: humans and digital intelligence
Getting along with other humans has always been important. To be successful in the workplace of the future, we will all need to be comfortable working alongside digital intelligence too. This includes both autonomous machines and algorithms, respectively the physical and non-physical instantiations of digital intelligence.
Smart managers will resist the temptation to simply find ways to replace humans with robots and algorithms as technology advances. I know this temptation is strong in some sectors of U.S. industry right now as bean counters brace for the arrival of the $15 minimum wage. Companies risk stripping out the humanity from their operations, and thus their brand, if they blindly take this approach. Every brand has a human element at its foundation.
Leaders should step back and consider ways to optimize their labor force by forging partnerships between humans and machines (or humans and algorithms). Humans and machines each have different strengths and weaknesses.
Robots vs humans vs algorithms
Machines have many advantages over us humans. Robots are much stronger than us. They also have endurance and speed on their side. Algorithms, analytics and A.I. can spot complex patterns in vast seas of data that humans just cannot see, and they operate at incredible speed.
Don't panic. All is not lost for humanity. We humans still excel in many areas where machines will remain weak for the foreseeable future. Our skills related to creativity, dexterity, and adaptability are fine examples. Most of us also have strong empathy for other people, a vital skill for all aspects of customer service. We are of high value just by virtue of our humanity. After all, nobody wants to be told they have stage three liver cancer by a machine.
Technology will do best at repetitive tasks (even very complex ones) that can be learned by analyzing huge data sets. These are tasks that are repeated over and over again and that have a measurable outcome. Radiologists are highly-trained and highly-skilled. But if you show a deep learning algorithm enough CT scans and X-rays of potential tumors and then tell it which ones are positive and which are negative results, you can teach it to be a very effective radiologist. The diagnostic component of other jobs such as doctors and mechanics will go the same way. So too will the jobs of CPAs, insurance underwriters, and auditors. Expect algorithms first to show up as assistants, working alongside the human experts, advising and offering an expert "opinion". Once the machine's accuracy outstrips that of the human, the human will be freed to take on more of the tasks that machines can't do, like spending time face-to-face with patients. The machine becomes a partner to the human, enabling them to achieve far more in a single day and to focus more of their time on what they do best: interacting with other humans.
Augmenting human capabilities with digital intelligence
Managers will need to learn how to think through business processes and design their teams so that tasks are intelligently split between human and non-human labor. (Non-human labor is really capital if you ask economists, but let's set that aside for now). Managers will need to think through which tasks are best handled by humans, which by robots, and what role algorithms, analytics and A.I. can have to help the humans do a better job.
As an example, consider the service a sales associate gives in a high-end clothing store. When you want to try on a few items, he or she takes the garments from you, finds you an open fitting room, and then carefully lays out all the clothing in the room ready for you to try. What you might not be aware of is that the associate is also eye-balling all your choices to understand your size, color preferences, and general style. Once you are safely installed in the fitting room they run off back into the store to gather matching items you might also want to try. As well as providing a valuable styling service, this is also a way for the store to sell-up and increase revenue. To do this well, the sales associate must a) have a good sense of style, b) accurately remember your size and all the garments you picked, c) know the inventory of the store and what is in stock.
This business process can be parsed into two pieces: a human piece, and an algorithmic piece. RFID sensors in a smart fitting room can read RFID tags on items to figure out what garments the customer took in with them, including their exact size and color. A wifi sniffer can recognize the MAC address of a customer's phone and look up previous purchases if they have previously downloaded and used the store's app. All this information can be used as input to an analytics engine. Using a "goes with" database, created by a designer, the algorithm looks up each item the customer has in the changing room to find other items that it can suggest will make nice outfits: shoes, accessories, and so on. The algorithm checks which items are in stock and where they are located in the store. It plots the optimal path to pick all the items from the store floor and sends this information to the store associate.
The store associate, guided by the algorithm, then whizzes around the store and picks out the clothing items and accessories and returns them to the fitting room to give to the customer. Their dexterity and visual abilities mean this job is best done by a human, not a robot.
This partnership of human and algorithm gives the highest-quality result for the customer, maximizes the chance of selling up (and thus perhaps the chances of boosting the sales associate's commission), and saves the associate time, enabling them to serve more customers. The styling component of the service becomes automated which means even associates with poor fashion sense can deliver terrific service. It is the associate's ability to interact with the customer and provide friendly, speedy service that matters most. Something a machine just can't do.
The robots are coming. Analytics and AI will transform every sector of industry. Every business will need to find the optimal pairing of human and machine. And we will all need to learn to work for, and alongside machines.
Leaders will need to learn how to examine each business process and understand the best way to split tasks intelligently between humans and algorithms. They will need to build high-functioning teams that include humans, robots, and algorithms. Smart leaders will resist the temptation to blindly try and replace labor with digital intelligence and will instead find ways to build strong partnerships between the humans and non-humans in their organizations.
If you need help to build a strategic plan for the future of human and machine partnerships in your organization please contact me at www.baldfuturist.com to talk about doing a futurecasting workshop.
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