Beyond Automation

Article from Harvard Business Review by Thomas H. Davenport and Julia Kirby

Some pointers that I've got are:

Augmentation -  It stands in stark contrast to the automation strategies that efficiency-minded enterprises have pursued in the past. Automation starts with a baseline of what people do in a given job and subtracts from that. It deploys computers to chip away at the tasks humans perform as soon as those tasks can be codified. Aiming for increased automation promises cost savings but limits us to thinking within the parameters of work that is being accomplished today.

Augmentation, in contrast, means starting with what humans do today and figuring out how that work could be deepened rather than diminished by a greater use of machines. Some thoughtful knowledge workers see this clearly. Camille Nicita, for example, is the CEO of Gongos, a company in metropolitan Detroit that helps clients gain consumer insights—a line of work that some would say is under threat as big data reveals all about buying behavior. Nicita concedes that sophisticated decision analytics based on large data sets will uncover new and important insights. But, she says, that will give her people the opportunity to go deeper and offer clients “context, humanization, and the ‘why’ behind big data.” Her shop will increasingly “go beyond analysis and translate that data in a way that informs business decisions through synthesis and the power of great narrative.” Fortunately, computers aren’t very good at that sort of thing.

Intelligent machines, Nicita thinks—and this is the core belief of an augmentation strategy—do not usher people out the door, much less relegate them to doing the bidding of robot overlords. In some cases these machines will allow us to take on tasks that are superior—more sophisticated, more fulfilling, better suited to our strengths—to anything we have given up. In other cases the tasks will simply be different from anything computers can do well. In almost all situations, however, they will be less codified and structured; otherwise computers would already have taken them over.

Five Steps to Consider

Step up

Your best strategy may be to head for still higher intellectual ground. There will always be jobs for people who are capable of more big-picture thinking and a higher level of abstraction than computers are. In essence this is the same advice that has always been offered and taken as automation has encroached on human work: Let the machine do the things that are beneath you, and take the opportunity to engage with higher-order concerns.

If stepping up is your chosen approach, you will probably need a long education. A master’s degree or a doctorate will serve you well as a job applicant. Once inside an organization, your objective must be to stay broadly informed and creative enough to be part of its ongoing innovation and strategy efforts. Ideally you’ll aspire to a senior management role and thus seize the opportunities you identify - “people who can go really deep in their particular area of expertise and also go really broad and have that kind of curiosity about the overall organization and how their particular piece of the pie fits into it.” That’s good guidance for any knowledge worker who wants to step up: Start thinking more synthetically—in the old sense of that term. Find ways to rely on machines to do your intellectual spadework, without losing knowledge of how they do it.

Step aside

Stepping up may be an option for only a small minority of the labor force. But a lot of brain work is equally valuable and also cannot be codified. Stepping aside means using mental strengths that aren’t about purely rational cognition but draw on what the psychologist Howard Gardner has called our “multiple intelligences.” You might focus on the “interpersonal” and “intrapersonal” intelligences—knowing how to work well with other people and understanding your own interests, goals, and strengths.

If stepping aside is your strategy, you need to focus on your uncodifiable strengths, first discovering them and then diligently working to heighten them. In the process you should identify other masters of the tacit trade you’re pursuing and find ways to work with them, whether as collaborator or apprentice. You may have to develop a greater respect for the intelligences you have beyond IQ, which decades of schooling might well have devalued. These, too, can be deliberately honed—they are no more or less God-given than your capacity for calculus.

Step in

Those capable of stepping in know how to monitor and modify the work of computers. Taxes may increasingly be done by computer, but smart accountants look out for the mistakes that automated programs—and the programs’ human users—often make.

Here you might ask, Just who is augmenting whom (or what) in this situation? It’s a good moment to emphasize that in an augmentation environment, support is mutual. The human ensures that the computer is doing a good job and makes it better. This is the point being made by all those people who encourage more STEM (science, technology, engineering, and math) education. They envision a work world largely made up of stepping-in positions. But if this is your strategy, you’ll also need to develop your powers of observation, translation, and human connection.

Step narrowly

This approach involves finding a specialty within your profession that wouldn’t be economical to automate. 

Those who step narrowly find such niches and burrow deep inside them. They are hedgehogs to the stepping-up foxes among us. Although most of them have the benefit of a formal education, the expertise that fuels their earning power is gained through on-the-job training—and the discipline of focus. If this is your strategy, start making a name for yourself as the person who goes a mile deep on a subject an inch wide. That won’t mean you can’t also have other interests, but professionally you’ll have a very distinct brand. How might machines augment you? You’ll build your own databases and routines for keeping current, and connect with systems that combine your very specialized output with that of others.

Step forward

Finally, stepping forward means constructing the next generation of computing and AI tools. 

Stepping forward means bringing about machines’ next level of encroachment, but it involves work that is itself highly augmented by software.  If this is your strategy, you’ll reach the top of your field if you can also think outside the box, perceive where today’s computers fall short, and envision tools that don’t yet exist. Someday, perhaps, even a lot of software development will be automated; but as Bill Gates recently observed, programming is “safe for now.”

Why Employers Love Augmentation (or Should)

For augmentation to work, employers must be convinced that the combination of humans and computers is better than either working alone. That realization will dawn as it becomes increasingly clear that enterprise success depends much more on constant innovation than on cost efficiency. Employers have tended to see machines and people as substitute goods: If one is more expensive, it makes sense to swap in the other. But that makes sense only under static conditions, when we can safely assume that tomorrow’s tasks will be the same as today’s.

Yours,

Something Small Thinking Big