Airbnb scams: criminal activity on big tech platforms

Big tech sharing economy platforms like Airbnb and Uber are marketed as trustworthy, but a new book by a South African media scholar argues that they are highly vulnerable to scammers who spread delusive speech (a form of disinformation, designed to deceive by criminal intent).

Julie Reid draws from first-hand accounts and over 600 cases from around the world of victims lured into scams or physical danger by fake Airbnb reviews and listings, providing a detailed case study. We asked her five questions about her book.

HOW DO THE SCAMS WORK?

Airbnb is the world’s largest accommodation-sharing platform. It connects property owners who want to rent out their homes with travelers looking for alternatives to traditional hotels. The company recently expanded its offering and now facilitates the booking of other services like personal trainers or caterers along with accommodation rentals.

Airbnb scams happen in several ways. The most obvious is the phantom listing scam. The scammer constructs a fake but attractive listing on Airbnb and accepts payments from unsuspecting guests. It’s only when guests arrive at the address that they discover the property doesn’t exist. Scammers have also learned to navigate around Airbnb’s review system. Fake positive reviews are produced by scam host networks, making them appear to be authentic.

Bait and switch scams are also common. Here the scam “host” contacts the guest on check-in day claiming the reserved property is suddenly unavailable. They offer alternative accommodation, which the guest later discovers is not as good as the original property they’ve paid for (which is often fictional). The guest pays for a premium rental but is forced to stay in a property that might be unsafe, unclean, or missing amenities.

Scam hosts use misleading, plagiarized, or artificial intelligence (AI)-generated property images and fake descriptions along with fake personal profiles and aliases.

Delusive tactics also redirect guests away from the secure Airbnb payment portal to alternative payment methods. The scammer disappears with the money.

But the danger isn’t limited to financial crimes. The platform’s business model is premised on staying in a stranger’s private property, which can put guests’ personal safety at risk.

Criminal hosts can lure targets into dangerous environments. Once checked in, guests are isolated from public view, housed in a property to which the host has access.

I’ve assessed multiple cases where Airbnb guests were assaulted, robbed with no signs of forced entry, raped, murdered, made victims of sexploitation, extortion or human trafficking, or held hostage.

HOW DOES THE DISINFORMATION WORK?

I consider delusive speech a subset of disinformation because it presents intentionally misleading content at scale. But it differs from disinformation in its intentions. It isn’t done to promote a particular cause or gain ideological, military, or political advantage. Delusive speech is motivated purely by criminal intent or nefarious financial gain.

Delusive speech works by hiding in plain sight on platforms we think we can trust, like Airbnb, Booking.com, Uber, and others. Often, it’s indistinguishable from honest and genuine content. When users browse Airbnb listings for holiday accommodation, they’re presented with numerous options. A fake property listing looks, sounds, and feels exactly the same as a genuine one.

This happens on a platform that has built its brand narrative around the concept of trust. Scammers exploit these digital contexts of pre-established trust. When users log on to popular e-commerce or sharing economy platforms, they’re already primed to pay for something. It becomes relatively easy for scammers to delude targets into parting with their money.

WHAT CAN AIRBNB DO ABOUT IT?

Airbnb already has several trust and safety mechanisms in place. They include rapid response teams, an expert Trust and Safety Advisory Coalition and travel insurance for guests. The company claims to be trying to stop fake listings with machine learning technology.

Sadly, none of these mechanisms work perfectly. While Airbnb promises to verify properties and host identities, my analysis exposes flaws in these systems. Scammers easily bypass verification tiers through aliases, forged documents and AI-generated material. Airbnb has admitted it needs to address the failures of its verification processes.

My analysis uncovered how scammed guests are routinely denied the opportunity to post reviews of problematic rentals. Opaque terms of service and content policies allow Airbnb customer service agents and executives to justify censoring negative but honest guest reviews.

This means dangerous and fraudulent activity goes publicly unreported and unreviewed, leaving future guests vulnerable. I argue that Airbnb’s review curation mechanisms should be revamped according to internationally recognized human rights frameworks that protect freedom of speech. This would allow for more honest accounts of guest experiences and create a safer online environment.

Perhaps the most common complaint I encountered was that Airbnb doesn’t remove offending listings from its platform, even after a scammed guest provides evidence that the listing was posted by a fraudster. Airbnb must develop an urgent protocol for swiftly removing offending listings when discovered, to protect future guests from falling victim to the same scam trap.

WHAT CAN USERS DO TO PROTECT THEMSELVES?

Travelers can protect themselves by being extra cautious. Ask around. Seek recommendations from people you know and trust, and who can verify that the property you are booking actually exists and that the host is trustworthy.

If that isn’t an option, consider an established hotel instead, but book directly with the hotel and not via third party sites like Booking.com where listings can easily be faked. Check on Google Street View to make sure the property is where it claims to be.

Either way, have a Plan B in case things go wrong. Prepare ahead of your trip by deciding what you will do if you find yourself in an unsafe situation. And always, always, buy travel insurance.

IS IT PART OF A BIGGER PROBLEM?

I assessed several digitally initiated scam categories in this book. While my main case study focused on Airbnb, the problem of delusive speech online isn’t unique to this platform. Delusive speech is now carried by all major tech platforms integral to everyday life. In the book, I also highlight how scammers operate in every corner of the internet, including dating apps like Grindr, Tinder and Hinge; ride-sharing services like Uber, Lyft, and Bolt; travel sites like Booking.com and Hotels.com; and social media platforms like Facebook, Instagram, and YouTube, among others.

I hope that these examples will boost awareness of the risks of using these apps and sites.

Julie Reid is a professor at the University of South Africa.

Source: Business World

Reducing emissions and air pollution from informal brick kilns

INTRODUCTION:

In many low- and middle- income countries, it is commonly believed that weak state and regulatory capacities limit the ability to reduce pollution and mitigate climate impact. In Bangladesh and across South Asia, most brick manufacturing takes place in informal, traditional coal- fired kilns. These kilns are among the largest sources of greenhouse gas emissions and air pollution, leading to an enormous public health burden.

RATIONALE:

In Bangladesh, efforts to improve the brick kiln industry over the past 30 years have had limited success. Our past work suggests that a correctly operated zigzag kiln (a traditional kiln type that accounts for 81% of the sector) can not only improve efficiency but also increase kiln profits. However, most zigzag kilns in Bangladesh are incorrectly operated, leaving these social and private benefits unrealized. Improving energy efficiency presents an alternative strategy to reduce emissions and pollution while also delivering productivity gains.

RESULTS:

We developed a low- cost intervention to improve the energy efficiency of zigzag kilns and conducted a randomized controlled trial (RCT) of the intervention among 276 kilns in Bangladesh.

Our study included a control arm and two intervention arms (a “technical” arm and a “technical+incentive information” arm). All kilns assigned to both intervention arms received information, training, and technical support to adopt operational improvements that improve fuel combustion and reduce heat loss in the kilns.

These improvements specifically targeted how coal is fed during the firing process and how bricks are stacked inside the kiln, along with several other aspects of operation.

Kilns assigned to the “technical+incentive information” arm also received explicit information regarding the business rationale for incentivizing workers to adhere to the new practices. There was high demand for the intervention, with 65% of intervention kilns adopting the intervention’s recommended firing and stacking practices.

Notably, 20% of control kilns also adopted these practices, bolstering the interpretation that demand was high. There were no differences in adoption between the two intervention arms and no use of incentives or benefits in the “technical+incentive information” arm. We studied the intention- to- treat (ITT) effect of random assignment to the intervention, as well as the impact of the intervention after adjusting for compliance using an instrumental variables (IV) framework. Among compliers, the intervention led to substantial reductions in the amount of energy used to fire bricks (23%) and corresponding reductions in carbon dioxide (20%) and particulate matter with a diameter of <2.5 μm (20%).

These gains were achieved without any evidence of a rebound in energy demand. Kiln owners also benefited financially from the intervention; production of the highest quality category of bricks increased in intervention kilns and spending on fuel per brick declined. The primary costs of the RCT were the training costs and technical support costs throughout the season. Using a social cost of carbon of 185 USD per metric ton to value the reductions in CO2 emissions, we find the benefits of the intervention outweighed the costs by a factor of 65 to 1, and that these reductions were achieved at an average cost of 2.85 USD per ton.

CONCLUSIONS:

Our study demonstrates that meaningful reductions in emissions by traditional kilns are achievable, even in the absence of stronger regulations, if they can be made financially attractive to private kiln owners.

Source: Science 08 05 2025

Why some Hong Kongers live in homes smaller than a parking space

Landlords in Hong Kong, a city with a notoriously high cost of housing, have found they can make more money by dividing a flat into two or more units

Tens of thousands of people in densely populated, land-poor Hong Kong live in tiny dwellings made by dividing up apartments, most smaller than a parking space. It’s an affordable option for students and low-income families but can also mean banging shins in cramped and in some cases substandard living spaces.

The city’s government has proposed new rules that would set minimum standards for such housing units, but residents and advocates for the poor worry that it could drive up rents and make it even harder to hang on in the city. The city’s eventual goal, mandated by Beijing, is to eliminate subdivided apartments over the next 25 years.

Officials are aiming to pass the rules into law within the year. After that, landlords will have a grace period to make their substandard flats meet the bar. The government has promised to assist affected residents in resettlement and adopt a gradual approach in its policy implementation to avoid causing panic.

Here are some of the numbers that illustrate the residents’ living conditions and the proposed policy.

7.5 million Hong Kong’s population in mid-2024

80 square kilometers (31 square miles) How much land is used for housing in the densely-packed territory, according to the city’s planning department

110,000 The number of dwellings created by dividing apartments

220,000 The number of people who live in them

10 square meters (110 square feet) The median size of the units that have been carved out. About one-fourth are less than eight square meters (86 square feet), the minimum size mandated under the proposed rules

12.5 square meters (135 square feet) The standard size of a parking space in Hong Kong

5,000 Hong Kong dollars: or PHP 37,000 the median rent for a unit in a subdivided apartment

33,000 Estimated number of units that would need major renovations under the proposed rules

2049 The year by which China’s central government wants Hong Kong to phase out subdivided units. It will mark 100 years of communist rule in China.

Source: Philstar