Emotional AI – Getting Hyper-personal in the Travel Sector
From Science Fiction to Science Fact
Just a few years ago, artificial intelligence (AI) still seemed to be the stuff of science fiction. Today, the technology is being deployed for a growing number of applications in a wide range of industries.AI has become part of the fabric of our daily lives – in the form of Siri, Alexa, Google Home, and other voice-activated personal assistants, through to increasingly accurate online translation services that leverage machine learning hone their “skills”.
Biometrics is a term familiar to anyone with a passport or identify card. Since 2006, for example, all new UK passport photos have had to comply with stringent biometric standards that enable individuals to be identified and authenticated rapidly and reliably by simply scanning the holder’s photo.
In this blogpost, we’ll be looking at how AI and biometrics are being used in the travel sector – and how the convergence of the two technologies could open up new revenue streams for travel players.
AI + BB = Emotional AI
Emotional AI marries the machine learningbehind AI with behavioral biometrics (BB) to create a technology that can rapidly determine individuals’ changing emotions based on their facial expressions and gestures – and trigger appropriate responses.
While emotional AI is still at a comparatively early stage, it’s already being deployed in a number of real-world applications. For example, in China, the technology is being used to monitor the emotions of factory workers and train drivers to detect any changes that could jeopardize safety.
In the travel industry, emotional AI has considerable potential when it comes to delivering new types of value-adding services for customers, tapping lucrative new revenue streams. And, in some cases, the AI and biometrics foundations for these innovative solutions is already in place.
From ID Verification to Smart Assistance – Biometrics and AI in Practice
A number of airlines have already piloted innovative biometrics applications for passenger identification and authentication. Designed to minimize the number of times travel documents have to be presented, these solutions enable customers to pass through airport checkpoints faster and with minimum hassle. This not only enhances security. It also adds value for passengers and air transport players alike – because satisfied customers, who can clear airport checkpoints faster, are more likely to be in the mood to make purchases.
AI, too, is making inroads in the travel industry. Applications in this area include Voya, an AI-based personal travel agent that aims to streamline the booking process for business travelers with services delivered via smartphone, tablet, and computer. And the Destygo platform allows travel and hospitality companies to build an AI-powered assistant for their users.
Taking Service to the Next Level – Hyper-personalized Applications
But emotional AI offers opportunities that go far beyond identification and assistance. Combining AI and behavioral biometrics could enable carriers to offer hyper-personalized services – of the kind already familiar from online retailing platforms – in the form of interactions and responses tailored to customers’ changing emotions.
Let’s take one familiar scenario: Say a passenger sits back to enjoy their in-flight movie only to discover they’ve already seen it. Chances are they’re not going to be happy – and their facial expression will immediately reveal this. If detected by a camera and interpreted by AI, this simple change in expression could be used to immediately offer the passenger a choice of alternative movies. What’s more the movies proposed could be based on the preferences suggested by the passenger’s individual viewing history. And exactly the same approach could be used to tailor a wide range of products and services to customers’ highly specific needs.
Life and Death Decisions in the Blink of an Eye
Another potential use case is security. Let’s say a passenger is who he says he is – that is, his (biometric) ID documents are in order – but he has entered the airport or boarded the plane with the intention of committing a malicious act. Emotional AI could be put into play here to detect subtle changes in behavior that suggest something is not right, allowing airport authorities or crew to take countermeasures promptly.
What’s more, the very same technology as used in the security example could be deployed for a quite different purpose – to ensure passengers’ well-being. Using Emotional AI to monitor vulnerable passengers could help detect any changes in behavior – such as excessive sweating or other signs of distress – that could indicate potentially serious health problems, enabling crew to come to their assistance in good time.
The Technical Solution – Lessons Learned from Pure AI Examples
But while these use cases may sound viable, wouldn’t the investment required in the technical solution be higher than the additional revenue generated? Experience gained with “plain” AI solutions, like chatbots or other voice-recognition engines, strongly suggests otherwise. Most solutions of this kind entail a one-time investment in an intelligent data analytics layer with a standardized API bridge to external services like voice-pattern analysis or facial recognition.
The technical architecture for emotional AI will essentially be the same: Once 80% of the platform is in place – and players who already use plain AI will be able to utilize existing development –, companies will have a solid foundation for any new hyper-personalized services they wish to implement. The necessary delta programming will account for just 20% of the effort involved.
One Architecture, Many and Varied Use Cases
To take the security and health examples presented earlier: In both cases, the underlying software and hardware architecture, which accounts for around 80% of the overall solution, is virtually identical. The only thing that changes between the different use cases is the business logic (the remaining 20% or so of the solution), which initiates the appropriate workflows and responses.
In the anti-terror use case, biometric capture and interpretation of certain pre-defined behaviors would trigger one set of alerts specifically for security staff. In the health use case, a different set of behaviors would trigger alerts, with suggested courses of action, to the cabin crew.
Sidestepping Possible Pitfalls – by Acting Responsibly
As with any new tech, there are a number of potential issues that travel businesses looking to leverage emotional AI need to be aware of. The most obvious of these is data privacy and data security. In the wake of the recent Facebook data harvesting revelations, if operators are to gain the necessary consent, they will have to set out clear terms and conditions for processing passengers’ data using emotional AI. They will also have to ensure personal information is secure – particularly in light of requirements like the new EU Data Protection Directive.
While handling the data required for emotional AI use cases is a sensitive area, the good news is that passengers are already happy to use biometric technology to smooth their way through airport checks. According to a recent SITA report, more than a third of passengers using automated ID control or biometrics on their most recent flight. This suggests that customers are likely to be willing to consent to the use of emotional AI if it offers sufficiently attractive benefits and their data is protected accordingly.
Using emotional AI responsibly is key to earning customers’ trust. This means putting people center stage and safeguarding their data from possible misuse. Only then can companies hope to gain the consent needed to make emotional AI a viable business reality.
Attractive Opportunities for First Movers
Travel players who start actively investigating emotional AI now stand to gain a vital competitive advantage in a potentially highly lucrative segment. Investing in the necessary architecture and scalability today is likely to bring rich additional revenue opportunities tomorrow.
By adding hyper-personalized services to their portfolio, airlines and hospitality companies can set themselves apart from the crowd – boosting brand attractiveness and customer loyalty.