Economic Indicators

Jim Spohrer on The Entrepreneurial Future In A World With Cognitive Assistants

Few people can be said to be the originator of a new science. Jim Spohrer is one of those rare beings. The science he originated is Service Science. You can read about the origination process at IBM Icons Of Progress (Mises.org/E4B_117_Icons). Jim currently is the Director of IBM’s Cognitive Opentech Group (COG). On the E4B podcast #117, he shares some of his knowledge and insights, especially on the subject of the wonderful new directions in which the combination of service science and artificial intelligence is going to take entrepreneurship in the near future.

Key Takeaways And Actionable insights

A new science of service.

Service science is combinatorial innovation: it combines service innovation, technology innovation and business model innovation. At the time of its origination it was also a challenge to the then-dominant logic embedded in the product mentality; that is, what is produced in the economy is products. As services began to take over the economy, the kinds of assumptions inherent in goods-dominant logic needed to be changed. The famous 1994 paper by Steven Vargo and Robert Lusch (Mises.org/E4B_117_PDF) was one of the sparks that lit a fire of change.

Looking at the world through the Service Science lens means seeing things differently, seeing all the knowledge that is embedded in products and services and people and exchange, and seeing that what is produced is a value experience for customers. This view opens the door for service innovation, serving people in better ways by facilitating more preferred experiences.

Service systems.

Just as Austrian economics is a systems-based view of the economy — with a diversity of interdependent consumers and entrepreneurs interacting and adapting to each other in the co-creation of value — so Service Science is a systems-based view of service. A lot of people, processes and technologies have to come together and interact to generate service value. Service is no longer viewed as one person helping another. Service systems consist of responsible entities interacting across networks to co-create value.

Service systems are people. Service systems are businesses. Service systems are governments. These are value networks. But these systems can become smart, and ever smarter, by the application of new technology.

Technological agency.

Just think how many service offerings might be limited by the number of employees with the requisite skills that can be deployed. And now think about how A.I. and automation and new technology could supplement human capacities.

One of the most significant new and accelerating capacities of technology is to act. Given a certain input (such as a service request) a technology or software can act in response, and deliver the requested service to the customer. We don’t need a librarian to retrieve a book for us, or a checker to check us out of the store. Perhaps in the future, we won’t need a doctor to diagnose our condition, or a driver to drive our Uber. We’ll rely on technological agents.

And, in turn, the technological agents will change people’s skills.

All kinds of innovation.

But technological innovation is not the only source of service innovation. Business model innovation is just as important. How do we pay for something? How do we recruit employees? There are existing models for these systems that can be innovated.

Institutional innovation is also going to be taking place, including in the operations of government.

At all levels — services, business models, institutions — systems are going to become smarter, which means using resources more efficiently, and getting results with less material, less effort, less time, and less use of space.

Smart systems can become wise systems.

If we add artificial intelligence to systems and human beings get dumber as a result, is that wise? No it’s not. For entrepreneurs, this means thinking through the delivery of betterment to the customer on a long term basis, thinking through all the secondary and tertiary effects, and aiming at long term benefits.

This thinking also embraces ethical considerations and the impact on future generations. Systems should become both smarter and wiser.

Cognitive assistants and cognitive mediators.

A.I. brings us cognitive tools. A tool typically does one thing, but an assistant can do many things. And perhaps the cognitive assistant can become a coach, and then perhaps a collaborator. Perhaps the best collaborator is one you can debate with, in order to sharpen your ideas. IBM is investing in debating technology so that, in the future, you can have a good debate with your cognitive collaborator.

One way to think about this is that the hundreds of apps we have on our smartphones grow up and become digital assistants, and the human owner of the smartphone is the manager of all these assistants.

The next step, perhaps 20 years into the future, perhaps more, will be to a cognitive mediator, an artificial intelligence you trust to make good decisions on your behalf. Perhaps it can negotiate better than you can. Perhaps it will know you better than you know yourself. Some innovators refer to the idea of a cognitive mediator as a “digital twin”. It’s possible today to have a digital twin for a piece of equipment. Tomorrow there may be a digital twin for all responsible entities, including people, businesses and even government.

All of these developments will have profound effects on service science, and the kinds of services we can imagine, design and deploy. And they’ll have a profound effect on identity — who we think we are, and how we think of ourselves.

Trust, Emotion and Empathy.

Trust in a digital twin takes us into the world of emotion and empathy. We all wonder if artificial intelligence can ever have empathy. Empathy is a way to unlock the ability to see the problems others are experiencing and to identify ways to solve them. A.I. will be able to build models of any particular individual, using data about the individual and data that the individual has generated. Amazon is already building a model of your preferences and Facebook is building a model of your social interaction.

Perhaps individuals will build data twins of themselves, and perhaps there will be a way to monetize the digital twin. There will be many, many new opportunities in evolving service science and the kind of value co-creation that is possible. So empathy comes down to digital twinning. Empathy is having a better model of others. Innovative entrepreneurs will tap into the best digital models they can of their prospective customers.

Parallel entrepreneurs replace serial entrepreneurs.

When we are all managing 100 digital workers on our smartphones, we’ll be able to initiate multiple innovations in parallel. This suggests we are on the verge of profound entrepreneurially-driven change. To do this wisely will require trust in artificial intelligence and trust in our digital twin. It will require an understanding of our own biases. And perhaps the digital twin will be able to point out these biases and correct them. If we trust it to.

Billions of responsible entities, trillions of strategies, higher aspirations.

W. Brian Arthur talks about complexity economics (Mises.org/E4B_117_PDF2) and a future in which the multiple strategies of billions of individual entities can be run in a simulation to see how they interact and what outcomes emerge. Such capabilities enable us to raise our aspirations to higher levels. What innovations can one entrepreneur introduce? How about 1,000 entrepreneurs or 100,000 entrepreneurs, or 500,000 entrepreneurs each with 100 digital assistants? We shouldn’t be thinking of mundane trivial things in this context. We must find higher aspirations. We should be thinking about augmented reality, new energy systems, biological innovation, institutional innovation and new mindsets to go with our new skillsets.

Our best selves can become better. For each of us, our future self is our customer. How do we make the future better for ourselves? How does that kind of thinking change the decisions we make every day? How does a business become a better future version of itself? How does an institution do so? How are businesses creating new customers by making them better future versions of themselves?

The best way to answer these questions is to be an entrepreneur and start, grow or re-purpose a company to do so.

Additional Resources

T-Shaped Professionals: Adaptive Innovators by Jim Spohrer: Mises.org/E4B_117_Book

“T-Shaped Individuals” on Slideshare: Mises.org/E4B_117_Slides

Service Thinking: The Seven Principles to Discover Innovative Opportunities by Hunter Hastings and Jeff Saperstein: Mises.org/E4B_117_Book2

IBM Icons Of Progress: Mises.org/E4B_117_Progress

Welcome To The Cognitive Era (PDF): Mises.org/E4B_117_PDF3