AI empowers the workforce

Standardization is essential to the broad adoption of AI technologies

By Natalie Mouyal

Artificial intelligence (AI) is one of the big buzz words in the tech industry. From robots to self-driving cars, digital twins and medical diagnosis, AI promises to deliver innovation on the scale of the discovery of fire and electricity, as one Silicon Valley chief executive officer (CEO) has put it. While it is not yet clear if this is truth or hyperbole, technical advances are coming rapidly.

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The term artificial intelligence is generally understood to refer to a machine that can replicate cognitive functions such as learning and problem-solving. It is a broad concept that encapsulates ideas ranging from Frankenstein-like robots to voice assistants for smart phones and other devices.

AI depends on the gathering, analysis and sharing of great volumes of data which are exchanged between applications. Machine learning algorithms enable the data to be processed and interpreted to provide patterns on which to base a prediction. Deep learning is the most recent AI technique to find real world applications. It mirrors the neural networks of the human brain to create transistor connections that can be strengthened or weakened depending on whether the data is interpreted correctly. As new data is received, the machine is trained automatically to perfect its predictions. As a result, machines are now able to recognize and respond to images and voices as well as to beat human competitors in games such as chess and Go.

AI takes a seat at the management table

Artificial intelligence represents the next digital frontier in the evolution of information technology (IT) in the industrial and commercial sectors. Initially viewed as a tool to increase efficiency within organizations, IT has since become an essential part of measuring an organization’s performance against key performance indicators (KPIs) established by its management team. The advent of the industrial internet of things (IIoT), in combination with AI applications, has further enabled IT to deepen its connections with management by providing insights that can be used to help determine future goals.

In the financial sector, AI is used extensively for trading, detecting fraud and communicating with customers via chatbots. AI technology provides data intelligence and automation for the manufacturing sector. Processes are automated to increase efficiency while data analytics and predictive algorithms enhance operations and strategy. In healthcare, AI technology can detect anomalies in medical images and undertake semi-automatic tasks during minimally-invasive surgery.

Using AI for digital twinning

Named a top trend for 2018 by Gartner, digital twins are transforming manufacturing. Defined as the virtual representation of a product, including the elements and dynamics of how it is made and how it operates throughout its lifecycle, digital twins influence its design, manufacture and operation. Gartner forecasts that digital twins will represent billions of things in the near future.

This technology is an integral part of the Siemens factory in Amberg, Germany. The factory in southern Bavaria has a digital twin that is identical in every respect. It is used to design and test products as well as to plan the manufacturing process and programme machines. Once an efficient working model has been developed and all glitches have been ironed out, the physical factory begins production.

According to Siemens, the defect rate at its Amberg plant is approaching zero, despite the fact it manufactures 1 200 different products on the same production lines. Digital twinning has also allowed the factory to scale up production to 15 million units a year, a 13-fold increase since 1989, without hiring more people or moving into larger premises. 

IEC work in AI

Digital twins rely on AI technologies made possible by the prevalence of sensors, networks for the reliable transmission of data and intelligent systems for processing and making decisions. In 2017, IEC and ISO became the first international standards development organizations (SDOs) to set up a committee to carry out standardization activities for artificial intelligence. Subcommittee (SC) 42 is part of joint committee ISO/IEC JTC 1.

According to Wael William Diab, Chair of SC 42, "One of the unique things about what IEC and ISO are doing through SC 42 is that we are looking at the entire ecosystem and not just one technical aspect. Combined with the breadth of application areas covered in IEC and ISO technical committees (TCs), this will provide a comprehensive approach to AI standardization with IT and domain experts."

Diab explained the importance of taking a horizontal systems approach to standardization. SC 42 will work with other JTC 1 SCs such as those addressing the internet of things, IT security, and IT governance, as well as the IEC Systems Committee (SyC) for Smart Cities.

Another key area Diab highlighted is manufacturing and the use of robots in factories. AI technologies have a ubiquitous presence, from the robots in the production line to the deep data analytics. Within this context, IEC TC 65, which covers industrial-process measurement, control and automation, will be another potential group with whom to liaise in terms of AI and industrial automation.

SC 42 has set up a working group on foundational Standards to provide a framework and a common vocabulary. Several study groups (SGs) have been set up to examine the computational approaches and characteristics of AI systems (SG 1), trustworthiness (SG 2), use cases and applications (SG 3) and big data (SG 4).

"It stands to reason that AI will be one of the most crucial enabling technologies in our lifetime. JTC 1/SC 42 is looking at the entire AI ecosystem from an IT perspective. Combined with the breadth and depth of application areas covered by IEC and ISO, the resulting standardization efforts will not only be fundamental to practitioners but essential to all stakeholders interested in the deployment of AI", Diab concludes.

Keeping AI safe and secure

While the introduction of new AI technologies has generated much excitement, it also raises concerns over security and the protection of data.

The ubiquity of connected devices that are able to communicate with one another increases the number of gateways that can potentially be used to breach a system, whether at home or in a factory or car. Cyber attacks can have disastrous consequences, causing production in a factory to shut down or a car to provoke an accident.   

Data protection is becoming increasingly important as connected devices collect vast amounts of information about their users on a daily basis. Within a home, these devices can store details such as favourite songs and television shows, but also the times of day when the home is empty. This raises considerable concerns regarding privacy that will need to be resolved.

International Standards are essential tools in the battle to provide information security and protect data against a cyber attack. ISO/IEC JTC 1/SC 27, IT security techniques, has developed the ISO/IEC 27000 family of International Standards for information security management systems (ISMS) to enable organizations to keep their data assets secure. The IEC 62443 series of Standards provides security for industrial automation and control systems, including all critical infrastructure such as energy, healthcare and transportation.

Gallery
AI_management_table_shutterstock AI helps managers define their strategy
Digital twins bring efficiency and productivity to manufacturing Digital twins are more and more used in manufacturing to increase productivity and efficiency (Photo: GE)
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