Cognitive Worker Amelia Could Transform Oil, Gas Operations
Since late last year, Royal Dutch Shell plc and Baker Hughes have been testing out Amelia, a cognitive knowledge worker developed by New York-based IPSoft. According to the firm, Amelia – a new artificial intelligence (AI) platform – could industrialize on a widespread basis functions around IT in the oil and gas industry that are primarily addressed through human labor.
Shell and Baker Hughes are using Amelia to deal with accounts payable in their customer service area. However, the potential for how Amelia can be applied is very broad, and she could indeed support operations out on oil rigs.
“For example, an engineer could interact with Amelia in order to speed up diagnosis and resolution of problems with machinery,” company spokesperson Sean McIlrath told Rigzone in an interview. “Understandably, however, even pioneering companies who are early adopters of cutting edge technology want to build familiarity with its capabilities in controlled environments first.”
At Baker Hughes, Amelia is being trained to interact with the companies suppliers in order to answering their invoicing queries, a time-consuming task due to Baker Hughes’ thousands of suppliers. By year-end the company hopes to be able to share data about how great an impact that Amelia has had on Baker Hughes’ operations, said McIlrath.
Unlike Watson – a supercomputer whose capacity is being tapped by Australia-based exploration and production firm Woodside Energy – Amelia is not meant to crunch data or perform analytics in a way that a human couldn’t do. Instead, Amelia is designed to do human work, and to learn through repetitive tasks, said McIlrath.
The impact of Amelia on human labor costs can be massive. Instead of involving human labor and using thousands of hours to close out tickets events, Amelia can handle tickets and events in a few minutes, said McIlrath. AI systems like Amelia are able to carry out many of the repetitive tasks that take up huge amounts of time and free up the workforce to apply its minds to more complex tasks.
“Importantly, we’ll leverage technology to change the way we want to run a process and invent new processes.”
AI won’t remove the need for human labor altogether, but will transform how human workers work, McIlrath noted. AI will allow accountants armed with spreadsheets and calculators to be productive in a way that they could not be when working with an abacus. “As machine technology evolves, the cost and design of the items we manufacture is transforming and the people involved in designing those products and running those plants are developing their skills all the time.”
While digital labor could transform a company’s operations, the inherent problem that has prevented companies from driving automation in digital labor is the lack of visibility across an enterprise and a lack of connection between differing systems. The Amelia platform effectively unifies all these systems, McIlrath noted.
“Everyday people use smartphones to gather information or make a transaction that was not even imagined 50 years ago – we’ll be using AI to redefine how we run operations in the same way. As we embrace and master this technology it will impact the skills we deploy across organizations,” McIlrath said. “The more we digitize the more we are able to analyze and act on the intelligence we extract from that data – this will permeate across the organization and affect all functions, not just IT.”
“The greatest benefit is being able to make sense out of all corporate data to make intelligent business decisions,” said McIlrath. “For example, in the case of data pulled from in-the-field sensors, intelligent machines/big data can help companies intake, analyze, process and output recommendations and insights that cannot be easily replicated by a human labor force because they must manually comb through all the data. Executives can get more accurate answers faster to make quick decisions that benefit the business.”
Understanding How the Brain Works
Developing the technology behind Amelia took time, said McIlrath. To create a technology capable of mimicking the human brain, the company’s research and development team spent a decade studying how human brains actually understand. Researching all aspects of how the human brain functions allowed IPSoft to define the right strategy for developing an artificial intelligence platform capable of understanding the meaning of what is communicated in natural language. This research also enabled IPSoft to learn how to follow a process and learn through observation following natural language, and independently being able to determine the steps needed to solve a problem.
“Once we developed the approach, we began writing the code,” McIlrath said, comparing the work to develop the technology to man’s ability to fly. “For hundreds of years, man could not fly because we were copying the movement of birds. Once we went deeper and actually understood the science of flight, however, we began building plans that could transport us over greater distances than ever before.”
Within IT operations there are highly defined processes, McIlrath said. The tasks that need to be fulfilled by IT engineers have been broken down into a virtual assembly line of operations so that the simplest and most repeatable tasks are performed by one group and as more complex tasks and exceptions are handled by other groups.
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