Paul Daugherty, chief technology and innovation officer at Accenture, sees three myths surrounding artificial intelligence: Robots are coming for us, machines will take our jobs, and current approaches to business processes will still apply.
The three myths represent “conventional changes to linear processes,” he said. The reality is more transformative. An example: Newark, New Jersey-based AeroFarms grows seeds indoors without soil or sunlight. Seeds are harvested in less than three weeks and the process requires 95 percent less water than conventional farming methods.
plays a key role, Daugherty said. AeroFarms’ scientists monitor 130,000 data points, analyzing everything from light sensitivity to nutrient absorption. “How do we get the conventional mindset [of ] from beating Go to reimagining business?” he said. “That’s what we like to think about.”
Along with H. James Wilson, who leads Accenture’s information technology and business research, Daugherty co-wrote the book ” Human + Machine: Reimagining Work in the Age of .” The pair spoke May 9 in Simon Johnson and Jonathan Ruane’s Global Business of and Robotics class at MIT Sloan.
New executive, management roles
The increased use of for day-to-day business operations will force enterprises to create new executive and management roles, the authors said.
First and foremost is a chief officer, Daugherty said. This person will understand and manage an organization’s data and ensure that is used responsibly. The role will merge the skill sets of the chief information officer and the human resources manager, requiring a leader who is comfortable introducing people into a process that is heavily dependent on technology
Meanwhile, new management roles will focus on the use of data, though they will not necessarily be traditional STEM—science, technology, engineering, and math—roles, Wilson said. A data compliance officer will help a company make ethical decisions about how data is used, he said, while an An algorithm is a fixed set of instructions for a computer. It can be very simple like "as long as the incoming number is smaller than 10, print "Hello World!". It can also be very complicated such as the algorithms behind self-driving cars. forensic analyst will explain the data models to internal and external stakeholders.
However, as with previous technology trends—client/server, internet, cloud, mobile, cybersecurity, and so on— will be so firmly integrated into the business that it will be a priority for all executives. “What we learned from digital transformation is that it requires CEO and board-level sponsorship,” Daugherty said.
New concerns about responsibility
Executives managing must ensure the validity of the data sets that systems use, the authors said. The MIT Media Lab’s Algorithmic Justice League has demonstrated that biased data sets can lead to biased results, whether companies realize it or not.
“You need data custodians and stewards, algorithm evaluators, to make sure they don’t amplify biases that were inherent in the data,” Daugherty said.
After realizing that even a multinational firm does not have enough recruiters, Unilever has automated the first two rounds of its interview process, he said. can do the initial vetting and sorting of candidates, which shortens the timeline and also allows Unilever to draw candidates from a larger, more diverse pool. […]