What will be the impact of Artificial Intelligence (AI) on people, organizations, and society? In a previous article on this blog, my colleague Paco Bree described five schools of technological thought that try to answer this question from different perspectives. One of the most important dimensions in this discussion is the impact of artificial intelligence on employment, the new skills required, and the new forms, processes, and organizational structures required to organize ourselves.
While we need much more research and much more evolution to achieve a more solid understanding of present and future scenarios, I would like to position myself, this time, closer to the school of optimistic realists: “[…] Smart machines will be able to stimulate technological gains creating new jobs, but the difference between high and low-skilled jobs could be accentuated. There are no simple solutions, more research will be necessary to discover the true relationship between productivity and employment, and to achieve effective responses to the challenges ahead.”
Personally, I position myself more as an adaptive optimist. In other words, I believe that Artificial Intelligence will bring a better future and humanity will adapt to achieve a mutual balance between technology and humanity, between productivity and employment, and that it will bring more gains than losses. It will be very challenging and uncertain.
Under this optimistic and adaptable perspective, one of the most relevant concepts is the augmented worker. Perhaps, more than a concept, it is an example. As Daugherty & Wilson put it in their Collaborative Intelligence article, humans and machines are joining forces to work collaboratively and in newer ways. This is changing the nature of work and, requires new managerial skills.
Artificial Intelligence will bring a better future and humanity will adapt to achieve a mutual balance between technology and humanity
Let’s take as an example the use of cognitive technologies that are helping doctors in cancer hospitals. In the case of a patient to be treated, doctors can rely on cognitive technologies that allow them to “augment” their experience and expertise to design and provide evidence-based therapies and care. AI is able to analyze the evidence of hundreds of thousands of cases in the historical data of an ecosystem of cancer hospitals, reduce the evidence to a list of options and propose effective therapies for each patient (case).
At that time, we could say, the doctor of that shift (and that case) becomes the most experienced doctor in the world, capable of providing a personalized and effective solution for the patient in question. It is as if Doctor Gregory House were available to every hospital in the world, and without the need for so many tests and trials.
In other words, in addition to achieving a personalized solution, this solution is generated with minimal friction or waste. Some studies have compared the recommendations of these cognitive technologies with those suggested by oncology specialists, and the concordance percentages are between 70% and 90%. Of course, more advances are necessary, but for many doctors, these technologies are very helpful, increasing the capabilities of the medical team. AI is not replacing doctors, but rather amplifying and collaborating with them to achieve productivity improvements that were not possible before.
As Daugherty & Wilson describe, humans will continue to be responsible for activities and tasks where they are better (for example, empathize, create, manage ambiguity), machines will continue to be responsible for activities and tasks where they are better (for example, transactions, prediction, data analysis), and humans and machines will need to collaborate with each other to complement and / or increase their capabilities (for example, machines will amplify human abilities, and humans will train and supervise machines). In other words, an organizational setting where humans and machines work collaboratively. In future articles.
Humans and machines will need to collaborate with each other to complement and / or increase their capabilities
I would like to continue delving into new processes and skills that will allow organizations and their managers to capitalize on collaboration between humans and machines.