In the first of a two-part report, Chris Middleton looks at how organisations are innovating with artificial intelligence – and what the knock-on effects on our lives might be.
The rise of voice-based AIs such as Apple’s Siri, Amazon’s Alexa, and Google’s Assistant promises many things. Not least of these is a new era of ‘ambient computing’, in which our link with computers is no longer dependant on a screen and graphical user interface (GUI), but on intelligence embedded in the cloud, and in our homes, offices, public spaces, and cities.
Voice-activated AI moves computing much closer to how human beings communicate in the physical world – but also, it must be said, to how we compete for each other’s attention. An implicit risk in a voice-activated AI world is that our environments become increasingly noisy – in every sense. So it stands to reason that a fellow traveller on this journey will be apps that allow us to filter out messages that we don’t want to hear, so that we can focus on our preferences.
Of course, one advantage of AI is that it can learn our likes and dislikes, turning up the volume of the social echo chambers in which many of us already sit. Soon, many of us may live in a world that only tells us what we want to hear, regardless of whether it is true: signals tuned to us, with everything else as background noise.
But that means it can also deliver ultra-personalised content, so organisations can tell us what we need to hear: for students who are learning online, for example, each of whose needs may be different to their peers.
Either way, it is good to know that AI-powered fact-checking services are soon to be with us en masse, too: Google and Facebook are both investing heavily the technology, alongside startups such as the UK’s Full Fact, and the Le Monde newspaper’s smart search engine. Perhaps the era of ‘fake news’ and ‘alternative facts’ may be short lived.
Might AI force politicians to tell the truth? Or will politics and the practice of gaming smart search engines and AI applications become ever more closely intertwined – just as journalism, SEO, and advertising have in a publishing world that is driven towards clickbait and search-optimised marketing?
What news agency Reuters calls ‘conversational commerce’ will also be among us, as more and more chatbots enter our daily lives.
Reuters has produced a report on the new media technology landscape, the 2017 Digital News Project. Among other things, it predicts that, “a mix of storytelling, product discovery, direct purchase and customer service is seen as the likely path ahead for chatbots; making consumer engagement possible at a much wider scale than could have been achieved before.”
Innovations such as these – together with devices such as the Amazon Echo and Dot – throw down the gauntlet to marketers, who now have to compete for the attention of machines and AI assistants, rather than the impressionable humans that marketing has targeted for centuries. One business leader suggests that this is forcing some organisations to get out of traditional marketing entirely.
Josh Valman, CEO of rapid prototyping outfit RPD International, says: “It’s a problem that has particularly come up for one client of ours, which happens to be a British airline. They’ve basically said, ‘B*ll*cks to marketing! There’s no point anymore.’
“They’ve said, ‘We need to work out how these algorithms work and find better ways of winning the algorithm game. Because we’re never going to be the cheapest airline, we need to find other ways of getting to the top of the list’.”
Other sectors may rapidly be transformed by AI, too, alongside the parallel rise of automation and robotics (both software and hardware).
For example, the Financial Services market is in the vanguard of AI and automation, with several banks exploring robotic customer service applications. Bank of America’s investment arm Merrill Edge is trialling an AI investment platform, while UBS is experimenting with an AI system designed to help customers rethink their investment strategies.
A byproduct of this is that, in some of these companies, face-to-face customer service is becoming a luxury item, aimed solely at wealthy clients.
Like finance, the law is a set of enforceable, replicable rules, and so it is no surprise that AI lawyers are winning business alongside robot investors, while helping their human counterparts to discover and collate vital information from a mass of documents and case law.
Healthcare is another sector that may benefit from AI, as a complement to human doctors. Speaking at the World Economic Forum in Davos this year, Microsoft CEO Satya Nadella described AI as a transformative force, which will help oncologists and radiologists “to use cutting-edge object recognition technology to not only do early detection of tumours, but also to predict tumour growth so that the right regimen can be applied”.
Nadella intends to infuse every part of Microsoft’s portfolio with AI, and shared the story of how one of his employees has designed smart glasses that use object-recognition technology as an aid for visually impaired people. Innovations such as this will be a boon in countless ways.
IBM is also refocusing on the technology. The enterprise services giant made its Watson AI supercomputer available as a cloud service last autumn, enabling robots to have natural language conversations with people, enabled by vast datasets that no human being could rival.
Industry-specific data will be a major growth market in the next decade, with players including ‘cognitive travel agent’, WayBlazer. This group of technologies – Watson, datasets, and robotics – is being trialled by Hilton in the US, where it is placing humanoid robot concierges in hotel lobbies. Elsewhere, education giant Pearson is using Watson to help deliver personalised courses to students.
Also speaking at Davos this year, IBM Chair and CEO Virginia Rometty said that IBM is placing its “big bet” on AI – or what is calls ‘cognitive computing’: “The reason is that [people] would be so overwhelmed with information, it would be impossible for any of us to internalise it, to use it to whatever its full value could be. But if you could, you could solve problems that [are] not yet solvable.”
The enterprise computing landscape is certainly being transformed by this idea, with the technology increasingly being built into business applications, such as CRM, HR, and finance and accounting.
For example, Salesforce.com debuted its Einstein platform last October, opening up a world of smart image identification, marketing automation, predictive lead scoring, automated audience segmentation, personalisation, predictive analytics, and more.
So any organisation’s ability to deploy Einstein will – appropriately enough – be relative, in that it will depend on their ability to gather, store, and process enough high-quality data to make the application of AI and machine-learning meaningful.
AI is also being built into the fabric of Google itself, with CEO Sundar Pichai believing that it promises interactions that are more “natural, intuitive, and intelligent”. Voice already accounts for 20 per cent of all searches in the US, according to recent figures.
So: a transformed technology landscape, in which organisations of any size can innovate on a level playing field.
The demand is certainly there: a recent report by Computing found that AI tops the new technology wish list for IT leaders and strategists in medium to large organisations, above big data analytics and Internet of Things applications.
But might customers be rushing headlong into applying a technology that is still in its infancy? We’ll explore this in the next part of this report.
Minimum Viable Product vs Product Market Fit: which will move the needle in Financial Services?
AI: Friend or Foe? (Part II)
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