Automation and robots in manufacturing – think car production – have been slowly eating away at the number of blue-collar workers for years. The International Federation of Robotics (IFR) estimates that an annual growth of 14% between 2018 and 2020 will result in a worldwide stock of operational industrial robots of just over three million. In the US, for example, robot installations increased 14% in 2016, driven by the desire to strengthen its competitiveness overseas while aiming to keep manufacturing at home.
Globally, the use of robots is only going to increase with the advent of Industry 4.0 – connecting manufacturing with virtual reality – and analysts predict a rapidly growing market for robots that are connected to the cloud. Apple and Samsung producer FoxConn, based in China, replaced 60,000 factory workers with industrial robots in 2016. Research from the World Bank provides some stark predictions on the proportion of jobs threatened by automation: 77% in China, 69% in India, and as high as 85% in Ethiopia.
On the other hand, Japanese business supplies reseller Askul has embarked on a programme with robot manufacturer Mujin to introduce the latest robot technology in its distribution centres to combat a labour force in the country that is declining.
The Internet of Things (IoT) is helping to drive innovation for the use of robots in commercial, manufacturing as well as home settings. A study undertaken by Navigant Research reveals that devices, software and services for the Industrial Internet of Things (IIoT) – which offers businesses the opportunity to leverage technology platforms – will exceed $1 trillion over the next decade.
Navigant Principal Research Analyst Neil Strother says: “IIoT technologies support broad digital transformation initiatives within a business, enabling them to offer enhanced services and improved experiences to customers.”
The transformation is accelerating due to the pervasive nature of digital technology, and the growth in research in machine learning, along with the work being undertaken with artificial intelligence (AI). An important advancement is the increased collaboration between universities and some of the world’s biggest companies.
Nothing artificial about it
IBM has announced a ten-year, $240 million investment in a new lab with MIT to advance AI hardware, software and algorithms. The partnership aims to push scientific breakthroughs to unlock the potential of AI, especially related to areas such as deep learning, and to heighten AI’s impact on industries.
A major focus of the partnership is to encourage students to launch companies for the purpose of commercialising AI inventions and applications. IBM SVP Dr John Kelly says: “Today’s AI systems, as remarkable as they are, will require new innovations to tackle increasingly difficult real-world problems to improve our work and lives.”
In October, Chinese e-commerce giant Alibaba said it will invest $15 billion in research and development over the next three years. This includes the creation of an academy and open research laboratories in seven cities around the globe. Its research areas will cover data intelligence, IoT, human-machine interaction and quantum computing. Alibaba CEO Jack Ma explained that the focus will be on real-world applications such as machine learning, visual computing and natural language processing.
To demonstrate just how far AI has come, an algorithm for imperfect information, named DeepStack, has become the first AI to beat professional poker players. It uses ‘intuition’ formed through deep learning to reassess its strategy. According to a research paper published in Science magazine in May this year, “DeepStack allows computation to be focused on specific situations that arise when making decisions and the use of automatically trained value functions”.
Google acquired UK-based AI research company DeepMind in 2014, which also focuses on developing programs that can learn to solve complex problems without being taught. The recently opened lab in Edmonton, Canada, meanwhile, concentrates on reinforcement learning which functions similar to the way humans learn, trying to replicate good outcomes and avoid bad outcomes based on learned experiences.
In addition, major traditional tech manufacturers such as Samsung, HP and Panasonic, are busy acquiring AI and robotics businesses and investing heavily in this area to launch AI-based products.
Increasingly, AI is seeping into our everyday lives, much of it integrated behind the scenes to the point where the majority of people don’t even realise it is enabling their interactions through applications such as Apple’s Siri, Microsoft’s Cortana, Amazon’s Echo and Google Assistant.
Even the office products industry is jumping on the bandwagon. Australian office supplies reseller Officeworks recently announced that it has integrated Google Assistant, giving customers the option to shop and engage with the brand through voice activation.
Intelligent automation is becoming ubiquitous in most industrial and manufacturing sectors, whereas in areas such as banking and retail, huge opportunities are being created through the use of AI in the form of chatbots and virtual assistants, virtual checkouts and tellers. Embedded into specific applications, virtual assistants use AI engines and machine-learning technology to respond to queries.
NPD Group VP and Technology Analyst Stephen Baker says: “AI is already transforming offices and making workers smarter and more efficient. It is in a smartphone, email and in many of the products used at work today to help correct errors and understand the tasks at hand. But, like all technologies, the transformation will be slow and gradual as more tasks are improved and made more efficient by AI.”
A recent survey by Dimension Data on the digital workplace revealed that 53% of organisations say smart meeting rooms are central to improving business processes. 62% expect virtual advisors to have a place in their companies within the next two years, while 58% expect to start actively investing in technology that powers virtual assistants.
With the advent of AI, the consensus is that no market sector is immune. Rice University Professor and computer scientist expert Moshe Vardi told OPI that, so far, the main impact of automation has been in manufacturing, but that machine learning has been making dramatic advances over the past five years with serious implications for white-collar workers. “What the impact will be is anyone’s guess. Manufacturing workers have not adapted well. Many tasks that require human judgement will be replaced by machine learning-based AI. Will office workers be able to upskill and find other jobs?” he says.
The middle market such as travel agents have already been reduced substantially by the use of digital technologies, and now professional service sectors, including the financial, legal and accountancy professions are expected to be affected by AI and machines. In the future, this will likely expand to ‘cognitive’ jobs. We’re already seeing humanoid robots as receptionists; earlier this year, Saudi Arabia became the first country in the world to grant a robot citizenship.
In the workplace, automation, AI, machine learning, Big Data and the IIoT and IoT are expected to enhance productivity. According to Accenture’s Technology Vision 2016 report, while intelligent automation is enabling businesses to put more processes into smarter machines, it’s not just about making the same tasks more efficient – although the forecast is 30-40% employee productivity gains over the next few years. It can also fast forward the creation of new products and services on a scale not thought possible. However, Accenture points out that innovative companies using automation are creating a different and more productive relationship between machines and people.
The expected outcome is for mundane tasks to be automated, freeing up employees to be more creative, innovative and productive, skills that will be in high demand in the years to come. “In the long term, AI will help office workers to be more efficient in their roles by allowing them to concentrate on the hard people tasks ahead and divest the more mundane tasks that AI can handle without human intervention. But robots won’t be writing reports, analysing data or selling a client a new product anytime in the near future,” says NPD’s Baker.
Stanford University’s One Hundred Year Study on Artificial Intelligence, looks at AI and its influences on people, their communities and society. The study reveals that while AI is almost certainly poised to replace humans in certain kinds of jobs such as taxi driving, it is more likely that it will replace tasks rather than jobs – at least in the near term – and will also create new types of jobs. Additionally, AI is expected to lower the cost of goods and services.
Impact on the workplace
What this potentially means is that fewer workers will be found in the workplace. In fact, 37% of people are worried about automation putting jobs at risk, according to a PwC Workforce of the Future survey, although 73% believe technology can never replace the human mind. Meanwhile, although 52% of CEOs responding to the PwC 20th Annual Global CEO Survey stated they were already exploring the benefits of machines working in conjunction with humans, and 39% are considering the impact of AI and future skills needs, 52% were also planning to increase headcount in the coming year.
The jan/san industry has seen some action in the way of the emergence of robots and AI, but it is not currently widespread. Talking about the main impact of this technology in the workplace, ISSA Director of Market Research & Analytics Jon Adkins told OPI: “While the technology is in a nascent stage today, its potential could be significant in terms of efficiency and productivity gains for cleaning organisations. AI developers and robotics manufacturers must focus on ensuring safety for both cleaning workers and building occupants, particularly as this technology is employed in K-12 schools, industrial settings and sensitive environments such as health care.
“Change always brings about insecurity no matter the industry, but it can also create opportunities. For example, it’s entirely possible that if a robot takes care of a tough or dangerous job, it could free up cleaning staff to concentrate on tasks that are safer and potentially higher paying.”
There is likely to be severe disruption in the coming years to many industry sectors and consumer markets through the increased use of AI and its impact on research areas that include: deep learning, robotics, machine learning, computer vision, natural language processing, crowdsourcing and human computation; and IoT. At the same time, there are issues to deal with in terms of law and ethics, in particular privacy issues. DeepMind, for example, has launched an Ethics & Society research unit, and many governments are creating taskforces to investigate the potential risks.
The Stanford study further says that most AI applications are highly tailored to specific tasks, but expects future uses of these technologies to include self-driving cars, delivery options in the form of drones and robots, healthcare diagnostics and physical assistance for the elderly. The combination of AI and robotics will be used in areas struggling to attract a younger generation, such as agriculture, factories and fulfilment centres.
Despite the apocalyptic views held by Stephen Hawking, Elon Musk et al, reassuringly, Stanford found no imminent threat to humankind from AI as no “machines with sustaining long-term goals and intent have been developed, nor are they likely to be developed in the near future”. However, the report did acknowledge that there will be disruptions in how human labour is enhanced or replaced by AI, creating challenges for the economy and society in general.
This is a topic that OPI will keep a close eye on and in the words of perhaps the most famous robot, “I’ll be back” with future updates.
Definition: Artificial intelligence
The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and translation between languages.
Definition: Machine learning
The capacity of a computer to learn from experience, ie to modify its processing on the basis of newly-acquired information.
Definition: Deep learning
Deep learning is a subset of machine learning in artificial intelligence that has networks which are capable of learning unsupervised from data that is unstructured or unlabelled.
Definition: Intelligent automation
The combination of artificial intelligence and automation.
Amazon means business
At the sixth annual re:invent Amazon Web Services (AWS) conference in late November/early December, the online giant unveiled a number of initiatives to boost its artificial intelligence and machine learning progress. The biggest announcement was Alexa for Business, a service that provides employees with an ‘intelligent assistant’ designed to help automate tasks such as conference calls, controlling equipment and reordering supplies.
For the US market, AWS has teamed up with AT&T for the LTE-M Button which uses the AWS IoT 1-Click service. Basically, it’s a Dash button for the workplace that allows businesses to order office supplies or submit service requests, for instance.
AWS also released five new machine learning services and a deep learning-enabled wireless video camera for developers, as well as a number of IoT services designed to manage, secure and analyse the data generated by large fleets of devices. A new AWS Greengrass feature, meanwhile, lets application developers add machine learning to devices without the need for special skills.