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The Turing Test

March 17, 2020

Whether it’s inflight internet access or the ability to check-in from your mobile phone, technology is changing the shape of travel - and aviation is at the center of much of the innovation.

A recent study by SITA, the leading airline IT provider, found that passengers are demanding technological innovation as they strive for “self-service to manage their own journey” and, at the same time, looking for a seamless experience across airlines, airports, border agencies and other stakeholders involved in their trips.

The rising expectations of “post-digital passengers” coincide with the rapid roll-out of various technologies across the travel ecosystem, one of which is Artificial Intelligence (AI).

In the travel and aviation context, most of AI has been very observational in that it looks at patterns and either tries to see those patterns in data it hasn’t seen before or tries to extrapolate from what it has seen in data in the past. However, this is changing rapidly with the growing sophistication of AI applications in travel, where ensembles of technologies are being used to create human-like automation of tasks.

A wide range of AI techniques and technologies are being leveraged to enhance or automate traditionally human-executed tasks, to the point that we are unaware of whether it is a human or computer conducting it. Travel AI is starting to pass the Turing test.

Coupled with the growing power, increasing speed and decreasing cost of computing, the amount of data available is also growing exponentially, leading to the wider application of AI to create a better experience for travelers.

Robotic process automation and machine learning are being used to streamline the booking process. For instance, where a traveler visits a few locations regularly and generally flies the same route, the same airline and the same day and time, it’s possible to automate the process fairly easily. A simple “fly to London” request on the booking tool can be automatically turned into a booking with a few key strokes.

AI-enabled messaging – commonly known as chatbots – which have played a crucial role in helping other industries such as banking and retail provide quicker support to customers, are also making their way into travel and aviation. By managing simple tasks, such as responding to requests for itineraries, chatbots free up employees’ time so they can focus on more complex activities and be more productive, delivering a better traveler experience.

Facial recognition is increasingly being used to speed up airport check-ins. Several airlines and airports around the world are testing and implementing facial recognition software that can verify travelers with a “quick photo capture”, allowing passengers to board using a biometric self-boarding gate. Airports like Jackson Atlanta International Airport have ‘fully biometric’ gates and terminals where travelers’ faces are their tickets. It is predicted that by 2021, the majority of airlines will be using self-boarding gates with biometrics. This is expected to improve safety and security, while creating a faster and more efficient check-in and boarding process.

Then we come to AI-powered robots – some of these are being deployed at airports, especially in Asia. Seoul’s Incheon Airport has a number of robots performing concierge roles, while airports in India and Japan are applying similar solutions. Similar to AI-enabled messaging, the idea is that it will reduce the need for guests to wait in line to ask a question, while freeing up employees’ time to focus on other tasks.

With AI, we can also get better at predicting trip disruptions. Various solutions that use predictive analytics to identify delay patterns across flights to forecast disruptions are being developed. They factor in things like the historical on-time performance of an airline, seasonality, flight timings, flight paths and air traffic, congestion at various airports, and weather forecasts. With this information, they can predict the probability of a delay occurring, as well as the length of the delay.

Challenges and limitations

While AI can deliver cost savings, a streamlined booking process, and many other benefits, it has its limitations. For instance, we still cannot rely on it for the full automation of complex or unusual bookings, as the consequences of “getting it wrong” can be quite severe. If an automated stationery buying tool ordered virgin paper instead of recycled, you could just send it back. But if a business traveler gets to the airport and finds he’s been booked to Shanghai instead of Beijing, that could cost his company a contract – not to mention the frustration for the individual. Travelers require zero errors in their bookings, which is a high standard for AI to stand up to and so limits it to use cases in booking and trip management where near 100% accuracy is routinely achievable.

Another complication is that to a large extent, industry players have worked in isolation, developing a myriad of different apps and other technologies aimed at enhancing the travel experience. All of the disparate development means end-users have to rely on fragmented solutions, with each individual technology only addressing part of the experience. And it’s hard to see how the diverse solutions can be integrated because of the competing business models and financial interests in the travel value chain. To date, all the major players have, understandably, focused on meeting their own needs – and these do not always align with those of their supply chain partners. This does, however, present enormous opportunities for third-party integrators.

There are also legal issues that hinder the indiscriminate adoption of many technologies. Most of these are centered on privacy and data protection concerns of data processing and ownership of data required to enable a complete range of digitally-enhanced traveler services. The recent European General Data Protection Regulations (GDPR) provisions regulate the sharing of personal data and we expect further similar data regulations from other jurisdictions in the future.

Technology has largely evolved much faster than the key players’ capabilities to manage it, and while the traveler appetite for tech solutions grows, the gap will continue to widen. This, however, should not sound alarm bells. If anything, experience shows that such an environment is the breeding ground for disruption, and we could well see the emergence of new players able to assemble all the functionality onto a single screen – and profit from the process.

This article was first published on APAC CIO Outlook, titled, “How AI Is Improving The Air Travel Experience”. It is republished with permission.


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