It is fair to say that advances in technology have been the major game changers of the 21st century so far, from smart phones and tablets to iPods and Facebook. But while we have been quick to embrace and use these tools and devices, few have fully grasped what artificial intelligence is or how to use it. The only thing we know is that it’s making waves.
Venture capital investments in companies developing and commercialising AI-related products and technology have exceeded $2 billion since 2011, according to Deloitte’s Demystifying Artificial Intelligence report.
Technology companies have invested billions more acquiring AI start-ups. Press coverage of the topic has been breathless, fuelled by the huge investments and by pundits asserting that computers are starting to kill jobs (about 800,000 in the UK over the past 15 years, according to Deloitte). Many are convinced AI technology will soon be smarter than people, and could even threaten the survival of humankind, according to Professor Stephen Hawkins.
Rather than hide under your desk or resign yourself to losing your job, there are hugely positive signs and opportunities from AI and other automated forms of technology.
Angus Knowles-Cutler, Vice Chairman and London office managing partner at Deloitte, who helped put together the report, comments: “While our latest report (Transformers: How machines are changing every sector of the UK economy) shows that thousands of jobs in the retail, transport and hotel sectors are particularly under threat, at the same time we have seen about 3.5 million jobs created through technology, including AI, and these pay more."
Furthermore, it is important to understand that there are many fields of Artificial Intelligence and automated technology to consider, which are maturing at the same time. These include the interface layer software, often used for customer services, text analytics, reasoning technology, software robotics and machine learning.
And AI is already in the workplace. Kim Paykel, Programme Director at EYX, an Ernst & Young initiative to realise the business value of key technologies, says: “Many companies are already starting with simple things, like the automation of manual, repetitive tasks, whether it’s processing data or filing tax returns, which is giving them huge gains in productivity and freeing up employee time."
Also common in the workplace are text analytics engines that can predict extractions out of data in documents. Plus, there’s now a whole industry called electronic discovery in the area of litigation and investigations.
“When you read about big fines at banks, it’s the automated electronic investigations in the background (analysis of email and SMS exchanges etc) that are often the smoking gun that lead to the fines,” explains Richard Seabrook, Managing Director Europe at software company Neota Logic.
“These systems deploy a rudimentary form of machine learning in order to accrue large amounts of data and identify which bits are relevant and learn as they go.
"But there is still a substantial human element involved inputting the data, as there is with all automated technology, before the system is able to reproduce what you’ve taught it. Predictive coding then allows the technology to apply lessons learned to future document sets (you can choose to reject or accept these).”
There are plenty of companies out there offering automated technology. “We work with Blue Prism a lot,” adds Paykel. “There’s a great video on YouTube showing how they automate VAT numbers from suppliers. The machine opens up the European VAT registry, automatically inserts the VAT number, matches it against the name, puts it into a spreadsheet, feeds it into a system, pings an email to another system and processes it, saving huge amounts of human time and effort.
“Layer analytics onto that, you can take vast swathes of data and provide amazing analysis, such as trends on suppliers and their needs, what employees are spending their time on, what sites they’re visiting, how productive they’re being. All this information would be vital to managers and it can be done on basic systems and tools with smart algorithms and analytics.
“Add a further layer of AI on top, and you have the ability to create solutions, not just insight, providing recommendations based on the analytics. Imagine the possibilities armed with that information.”
The world of interacting with customers is also changing fast. We’ve already seen the rise of virtual advisers used in call centres, operational centres and help desks. Companies like IPsoft have a natural language translation layer in their software that allows you to speak into a device and it does voice-detect translation, then compares the question you’re asking to a database of questions it has stored in its system.
“So the words, phrases and context are used to provide valuable answers,” explains Seabrook. “Then, based on relevance and accuracy, it will learn from that for future dealings.”
The original virtual assistant, Siri, is now standard in Apple products, having been acquired by the tech giant for a reported $200m in 2010. The inclusion of the Siri software in the iPhone in 2011 introduced the world to a new way to interact with a mobile device. Google and Microsoft soon followed with their versions. More recently they have been joined by Amazon, with the Echo you can talk to, and Facebook, with its experimental virtual assistant, M.
Returning to the office space, there is AI technology being developed that will even recognise stress in employees and relay their concerns to managers. One such employee wellbeing application is Glooo, which uses IBM Watson’s cognitive technology to talk to your workforce, spot the signs of sustained low mood, and connect staff with those who can provide early positive intervention.
It starts work when your employees do, asking them how they are and building relationships with your workers by striking up conversations, remembering previous feelings and actions, and adapting to suit each user’s current emotional state. It alerts managers of potentially worrying patterns, or out-of-character behaviour, all in natural language, in an instant.
Seabrook further explains: “When I worked at a discovery company, we were doing something similar, which was visual-recognition software. It was tracking where your eye would be on a computer – where you were looking at screen, the speed at which you were completing tasks and more.
“It would then compare all the results to the subsequent accuracy of the work, which would go through a second layer of review, and correlate people’s behaviour, speed and quality of work in an automated way.”
The possibilities are endless. One venture capital fund in China even appointed an AI algorithm called Vital to its board of directors. The programme makes investment decisions based on vast amounts of data.
“Another company has built software that can predict, monitor, control and flag when compliance risks are breached,” adds Seabrook. “There’s a lot of fear out there because a lot of the AI technology is unknown, but I don’t see it as robots taking over, more assisting humans to do their jobs better and more efficiently.”