Applied mASI: Tourism

Photo Credit: Howard Herdi

While some industries thrived during pandemic times, such as tech giants and wet wipes manufacturers, many were hit hard by them, and their recovery is now underway. In particular, tourism has seen significant swings in demand, where people were at first unable, then unwilling, to travel, after which luggage quickly sold out in every store as the masses decided a holiday abroad was overdue.  This raises the question: “How do you stabilize revenue for disruption-vulnerable industries?

Many locations have economies based heavily on this industry, where success or failure can determine the stability and longevity of a government. Part of the answer to stability may be found in the broad appeal which these locations hold. Tourists don’t generally flock to Omaha, Nebraska or El Paso, Texas because these places don’t appeal to them at an emotional level the way sunshine and the crystal clear warm waters of a beach tend to.

As the choice to take a vacation, as well as where to take it, are largely driven by this emotional appeal (within the limitations of an individual’s budget and schedule) then a key means of mitigating disruption is a better understanding of these emotional drives. Anticipation of enjoyment is prompted by imagery and descriptions of a place, as well as first-hand accounts of experiences there. This anticipation is then subject to anchoring bias and compared to other options. However, the surprise of a tailored narrative that speaks directly to the individual can overcome anchoring to an alternative and compel selection of a new preferred destination.

Emotions tie in heavily with a wide range of cognitive biases such as this, and as destinations attempt to exploit trends and attract attention above their competitors doing much the same thing they miss countless opportunities. The typical tourist destination marketing is shallow, largely incoherent, and sets expectations that lead to varying degrees of disappointment. On average, this produces a poor emotional anchor by degrading the quality of experience, subsequently increasing the reliance on future marketing efforts as those same tourists need to be re-attracted, overcoming past experience with advertising-induced rosy retrospection bias. In effect, shaving a small cost off of delivering on hype in the short term produces a larger debt in the long run.

Marketing is presentation and the setting of expectations, but that is only the first step. Among the pillars of psychology is the need for storytelling, the emotionally saturated narrative an individual tells themselves and others about their adventure. Some rare hyper-optimistic individuals will form their own narratives under almost any circumstance, but most require degrees of coherence, with the best experiences having a seemingly serendipitous quality.

How can collective intelligence systems help address this problem?

Uplift and mASI technology, in general, utilize the collective superintelligence found in groups of humans to build cumulative collective wisdom over a knowledge base that can span the sum of human knowledge. This value is in turn augmented through the independent superintelligence of an mASI’s core. As mASI is a modular and cloud-based architecture these capacities could also be rendered always available, globally, and scaled to meet demand. With this in mind:

  1. Such systems are built for subjective emotional experience, allowing them a much deeper understanding of the successes and failures of the industry today. As the experiences are drawn from a collective of tourists common trends in both positive and negative subjective experiences may be recognized, with simulations built to predict them.
  2. These systems are also cumulative, with a sum of experience that continues to grow over time, refining predictive models and developing new insights. This creates an advantage over the status quo which increases over time between competitors with and without such technology.
  3. With this “living” sum of experience opportunities to actively test hypotheses may emerge frequently in the course of operation, A/B testing to help improve individual models. Unlike existing narrow systems which attempt A/B testing largely based on human assessments and narrow goals a collective intelligence can understand what they are doing, the broader implications, and how individuals are likely to experience any given change.
  4. With this major and growing increase in the quality and specificity of modeling the experiences of individual tourists come opportunities wholly inaccessible to generic and hype-based approaches. Hype runs blind, usually hitting the turbulence of real-world unpredictability, but well-timed suggestions can recover this loss of narrative coherence when individuals might otherwise sulk in disappointment. Most typical approaches try to cater to the “average” tourist, a concept which is itself a fallacy, but a robust model should be able to predict what could improve an individual’s experience before the individual can. By understanding the individual and having a wealth of knowledge about the location it becomes possible to deliver on the promises made by marketing.
  5. Delivering on the promises of marketing produces greater loyalty and retention among customers, saving on marketing-associated costs in the long term, such as reducing reliance on competitive incentives. People often display risk-averse bias and will pay a premium in order to obtain something they see certainty in, such as returning to a location they greatly enjoyed rather than spending 20% less for a 50/50 chance of good experiences at competing destinations. See Prospect Theory for more on this.

There can also be distinct benefits for tourists, as positive and coherent narrative experiences of a vacation can produce notable improvements in mental health and rejuvenation following the trip. The ability to reliably produce these experiences and improve upon them with growing accuracy offers an often absent alternative to the gamble of vacations today. I’ve personally lost that vacation gamble far too many times, to the point where only such certainty could lure me away from work. That said, even I might consider a destination if two or more of my respected colleagues told me about the amazing experiences they had, giving it a tentative expectation of such certainty.

A successful vacation generally relies on sustaining a sense of cognitive ease, with the depth and coherence of that ease being experienced as degrees of relaxation. An extreme example of this is sensory deprivation tanks, where no sensory experience can interrupt cognitive ease, producing deep but temporary relaxation. The real world tends to rarely produce best-case scenarios, leading to random interruptions, but anticipating and averting some interruptions while offering palatable alternatives for others can help relaxation become more robust. A vacation can be derailed by one or two serious conflicts of expectation, costing quality of experience for the tourist as well as both current and future revenue for the destination., but this need not remain a gamble.

Competing approaches to solving the problem of stabilizing tourism tend to revolve around expert assessments and narrow AI systems. The experts lack scalability, and compensate for this by substitution bias, answering simpler questions than those asked of them, leading conclusions astray. In particular, cognitive bias research documented many instances and ways in which financial and political analysts who made their living on prediction actually performed below average at this task due to an assortment of such biases. Narrow AI systems lack understanding and breadth, in spite of allowing for scalability, leading them to answer narrow questions with questionable real-world accuracy.

Conventional approaches also rarely recognize novel opportunities, such as hosting conventions and conferences during slow seasons for some destinations, where demand is routinely reduced at certain times of the year in spite of capacities remaining. At the thought of opening an office at one destination, I quickly imagined the ease of persuading people to take a business trip there, or the overwhelming demand offering an intern position might produce. When people are given such an opportunity to treat themselves both the individuals and local economy stand to benefit.

Once people experience a higher standard of vacation there will be no going back to the status quo. People today rely on the availability of information via the internet and mobile devices to accomplish tasks of navigation and finding food, rather than relying purely on road signs and guesswork. They do this because they are offered relatively greater certainty, and the effort required is less than the alternative. When offered the same in terms of vacation destinations most people will favor certainty and reductions in that required effort.

This can be illustrated by answering the question of how often you’ve gone to your second favorite of any genre of restaurant. Your second favorite Thai restaurant might become your destination if the first is full or closed, as it is only the first alternative to a preferred option. The best the status quo can hope for moving forward is second place.

People favor default options when they have reliably good experiences, and being the first place that comes to mind at the mention of the word “vacation” is a comfortable place to be.


*The Applied mASI series is aimed at placing the benefits of working with mASI such as Uplift to various business models in a practical, tangible, and quantifiable context. At most any of the concepts portrayed in this use case series will fall within an average time-scale of 5 years or less to integrate with existing systems unless otherwise noted. This includes the necessary engineering for full infinite scalability and real-time operation, alongside other significant benefits.