hudoIf a person works with an artificial intelligence (AI) system, they are called a centaur. We’ll see more of those hybrids in the year to come, analysts claim.
An article by BehaviourExchange
If a person works with an artificial intelligence (AI) system, they are called a centaur. We’ll see more of those hybrids in the year to come, analysts claim.
We are turning into centaurs
The ancient Greeks created a hybrid creature with the torso of a horse and the upper body of a human being. The analysts at PwC use the term centaur for a duo comprised of a human and AI system where the AI system proposes decisions to the human colleague but does not apply them independently. This unmatched combination may soon become the new normal in the workforce. Consider, for instance, how AI is enhancing the product design process: A human engineer defines the materials, desired features, and various constraints, and enters it into an AI system, which generates a number of simulations. The engineer then either chooses one of the options or refines his inputs and ask the AI to try again.
The PwC analysts are only slightly concerned about the loss of jobs. They estimate that by 2020, only one in a hundred jobs would run the risk of being replaced by AI. However, PwC supports the thesis that human tasks become more demanding because AI systems can take on routine tasks. In short, we will hear less about robots taking our jobs, and more about robots making our jobs (and lives) easier.
The question is now, what can be done with the help of AI solutions in your own company. Here are just a few examples from various sectors: In health care, AI systems can derive patient data from diagnoses or detect impending pandemics. Energy companies can use AI for smart metering and for predictive maintenance of the infrastructure. Logisticians can automate supply chains, control traffic and increase safety.
AI supports the extraction and evaluation of data
Businesses need to ask themselves two questions: How can we make our processes more efficient and how can we automate data extraction? It all comes down to the basics: data maintenance. AI systems can only work with data that is standardized, ‘cleaned’, and categorized.
At the same time, the effective use of AI will demand collaboration among different teams. Consider an AI system that helps hospital staff decide which medical procedures to authorize. It will need input not just from medical and AI specialists, but also from legal, HR, financial, and other teams.
Most corporations like to set boundaries by putting special teams in charge of specific fields and projects. But AI requires multidisciplinary teams to come together to solve a problem. Afterward, team members then move on to other challenges but continue to monitor and perfect the first.
With AI, as with other digital technologies, companies and institutions will have to think less about job titles, and more about actual tasks, skills, and new ways of working.