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This legal article/report forms part of my ongoing legal commentary on the use of artificial intelligence within the justice system. It supports my work in teaching, lecturing, and writing about AI and the law and is published to promote my practice. Not legal advice. Not Direct/Public Access. All instructions via clerks at Doughty Street Chambers. This legal article concerns AI Law.
As I continue to build this blog and have discussions with academics, lawyers, and technical leads, I am always analysing how this might impact on my specific areas of practice. My Chambers will shortly be hosting a conference on rogue landlords and below is a summary of my thoughts on potential risks associated with AI and landlords who may not adopt it responsibly.
Excessive Monitoring
Rogue landlords already use various forms of surveillance, but AI dramatically escalates this threat. AI enables landlords to not only record tenants’ activities but to automatically analyse, categorise, and interpret them. Using sophisticated facial recognition or pattern-detection algorithms, landlords can track who visits, when tenants come and go, and even identify emotional or behavioural patterns. For example, an AI-driven camera system installed in communal entrances or hallways could instantly alert landlords when a tenant consistently returns late, when guests frequently stay overnight, or even predict tenant vulnerability by observing emotional states, facilitating targeted harassment or intrusive questioning.
Tenants can resist this in numerous ways. Clearly asserting their privacy rights under GDPR, Article 8 of the Human Rights Act or the Equality Act 2010 are just some. Ensuring that surveillance measures are explicitly stated in tenancy agreements and strictly limited will be beneficial. Any excessive surveillance, especially AI-based monitoring beyond what’s necessary for security, can be challenged legally via local councils or directly with the ICO. It may also amount to harassment under the Protection From Harassment Act 1997.
As surveillance technology becomes cheaper and more accessible, this issue will likely intensify, requiring clearer legislation around AI surveillance in residential properties. Tenants will increasingly need legal frameworks explicitly regulating and limiting AI-powered surveillance in private rental accommodation.
Automated Complaint Denial
Landlords frequently ignore tenant complaints, but AI transforms this into a systematic issue. Rogue landlords could implement AI chatbots or automated complaint systems trained to automatically dismiss or trivialise tenant issues. These chatbots use Large Language Models (LLMs) to convincingly deflect genuine maintenance concerns by falsely labelling them minor or tenant-caused. For instance, a tenant reporting mould growth via a landlord’s online portal might receive an immediate AI-generated reply dismissing the issue as poor ventilation, shifting blame and reducing landlord responsibility.
Tenants should mitigate this by demanding human verification and clearly documenting all maintenance requests in writing themselves. There are obvious issues with this if there are vulnerabilities or disabilities which may preclude detailed notice recording, nonetheless, some form of record keeping, however imperfect, should be adopted and speaking to friends or support services is essential. If an automated system repeatedly dismisses legitimate concerns, tenants can escalate complaints to local housing authorities or seek legal advice. Ensuring there’s a paper trail and human oversight will be essential.
Over time, without clear regulation, landlords might rely heavily on such AI systems, creating a consistent barrier to tenant rights. Tenants and regulators will need to closely monitor landlord practices and require transparent human-led complaint mechanisms.
Personalised Harassment
Harassment by landlords is sadly not new. I would refer the reader to the following examples of harassment on Chambers website including race based harassment [link] and [link]
But AI drastically amplifies the personalisation and scale. Using LLMs, landlords could automatically generate targeted and persistent harassment messages, tailored specifically to tenants’ personal situations. AI can analyse a tenant’s financial, social, or emotional vulnerabilities to craft messages that increase psychological pressure. For instance, a landlord might deploy a chatbot to continuously remind a financially struggling tenant about late rent payments, even subtly threatening eviction through automatically generated, personalised messages based on collected personal data. AI obfuscation may also be a relevant.
Again, tenants can counter this by documenting all instances of harassment and understanding that any harassment, automated or otherwise, breaches the Protection from Harassment Act 1997. Persistent automated messages designed to distress or intimidate are unlawful and should be reported immediately.
As LLM technology improves, these forms of harassment may become harder to distinguish from genuine interactions. This will necessitate stronger legal protections explicitly covering AI-driven harassment.
Predictive Neglect
While landlords neglecting repairs and maintenance is more common than it should be, AI introduces predictive analytics that allow neglect to become strategic and targeted. Landlords might use AI to predict exactly how long tenants will tolerate unresolved issues, calculating precisely when a tenant is likely to move out rather than pursue further action. For example, an AI might predict that a tenant is unlikely to leave within six months, even if repairs like heating or plumbing remain unfixed, thus incentivising strategic delays by the landlord.
Again, tenants must document unresolved issues and promptly seek intervention from local housing authorities, environmental health departments and take legal advice when delays appear intentional. Understanding rights under the Housing Act 2004 empowers tenants to demand timely resolutions to problems.
As predictive analytics become commonplace, tenants may see increasing strategic neglect from rogue landlords. Regulation must evolve to account for this systematic misuse of predictive tools.
AI-driven Rents and Charges
Dynamic rent-setting already happens, but AI enables rogue landlords to tailor pricing precisely and unfairly towards individual tenant vulnerability. AI-powered software can analyse tenant data, employment, family status, or financial vulnerability, to set rents based on personal circumstances rather than market conditions. For example, a landlord might use AI to increase rents specifically when a tenant’s employment status changes positively, such as after a promotion, exploiting the tenant’s improved financial situation.
Tenants can challenge this by questioning unjustified rent increases, seeking legal advice, and appealing to rent tribunals where appropriate. Transparent explanations for rent adjustments must be demanded to counteract personalised exploitation.
Future trends may see rogue landlords increasingly adopting sophisticated AI-driven pricing models. Therefore, stricter transparency and fairness regulations for automated pricing are likely necessary.
Credit and Background Profiling
I am currently working on two blogs about this specific issue which has already found its way into American and Australian courts.
In brief, Landlords already profile tenants, but AI expands profiling capabilities dramatically. AI-driven software can rapidly compile comprehensive profiles, including credit histories, employment records, and even social media content, to discriminate, directly or indirectly, against tenants they deem less desirable.
For instance, landlords might use AI-generated reports flagging tenants with irregular income or non-traditional employment patterns, unfairly excluding them from housing opportunities. The problem that came to be known as ‘no DSS benefit discrimination” will likely be exacerbated.
Both tenants and prospective must carefully consider these issues. It can be mitigated by regularly exercising their GDPR rights, requesting transparency regarding data collected and challenging any discriminatory decisions legally through tribunals or ombudsmen.
In future, as AI profiling becomes ubiquitous, ensuring fairness and transparency in data-driven tenant screening will become critical. Regulatory intervention will likely become essential to prevent systematic discrimination.
Automated Eviction Notices
While eviction threats already exist, AI automates and intensifies these intimidations. Rogue landlords could employ AI to generate eviction notices instantly, deploying automated threats to tenants perceived as problematic based on AI analysis of their tenancy data. For example, an automated system could immediately issue eviction warnings whenever a tenant submits repeated maintenance requests, attempting to intimidate the tenant into silence.
We already know from Worthington & Anor v Metropolitan Housing Trust Ltd (2018) EWCA Civ 1125 that heavy handed, inaccurate threats of legal action can amount to harassment and we may see AI exacerbating the position. If this happens, tenants should immediately seek legal advice on receiving such automated eviction notices.
Unfortunately, automated eviction threats may increase as AI-driven intimidation becomes cost-effective and easy to implement, making clear and swift legal challenges increasingly vital.
Social Media and Online Tracking
Social media tracking already occurs, but AI allows rogue landlords to comprehensively and covertly monitor tenants’ online activities. Landlords might employ LLM-driven analytics to automatically summarise a tenant’s online presence, making unfair assumptions about lifestyle choices, finances, or relationships. For example, an AI summarising social media posts might inaccurately identify a tenant’s social activities as disruptive or undesirable, influencing decisions to refuse tenancy renewal.
Tenants can proactively protect themselves by maintaining strong privacy settings on social media and being cautious about publicly sharing personal details that could be misinterpreted.
As AI’s ability to interpret and summarise vast amounts of personal online data grows, legislation will likely need to clarify the illegality of such invasive profiling explicitly.
Automated Legal Threats
Similar to automated notices of eviction, AI significantly lowers barriers for rogue landlords issuing intimidating legal threats. Using LLM-generated letters, landlords could cheaply produce credible-looking legal notices, intentionally confusing tenants unfamiliar with legal processes. For example, automated, AI-generated letters threatening court action for minor infractions like late payment could easily frighten vulnerable tenants into compliance.
Tenants should respond by verifying legal threats through independent legal advice immediately. Documentation of any intimidation attempts is crucial for potential harassment claims.
The accessibility of LLM-generated legal notices will likely encourage misuse, demanding greater legal clarity around automated legal communications.
Tenant Data Monetisation
AI makes it easier for rogue landlords to exploit tenant data for profit. Using AI tools, landlords could quickly aggregate and anonymise personal tenant information, collected through tenant portals or smart-home devices, and sell it to advertisers without tenant knowledge. For instance, landlords could sell tenants’ behavioural data to marketing companies, profiting from tenants’ private lives without consent.
Tenants should regularly request transparency under GDPR, specifically regarding how their data is collected and shared. Any misuse can be challenged through ICO complaints.
Future developments will likely necessitate stronger enforcement and oversight to prevent widespread data monetisation abuses.
Conclusion
This is a growing and pressing concern, particularly because AI technologies seem to be advancing at a much faster rate than the laws and regulations intended to protect us. Without swift and decisive action, there is a genuine risk that these abuses will escalate, leading to serious and lasting harm for tenants. I sincerely hope my fears prove unfounded, yet I anticipate returning regularly to this topic, providing updates, and highlighting real world examples where AI misuse has already occurred. Until robust legal protections are in place, vigilance and proactive awareness will remain essential.
