UNCHARTED ETHICAL TERRITORY
The global gambling industry is increasingly interwoven with artificial intelligence. From the personalised user experiences on online platforms to sophisticated fraud detection systems and even responsible gambling tools, AI is rapidly becoming central to day-to-day operations.
This growing reliance on data-driven insights allows companies to fine-tune offerings, identify player behaviours and streamline processes, but a new academic review – Identifying Risks and Ethical Considerations of AI in Gambling: A Scoping Review – sounds a clear warning: the ethical implications of AI in this sector are being alarmingly overlooked.
Despite gambling being a heavily regulated industry worldwide, there is a striking absence of specific oversight or guidance for AI’s deployment.
This regulatory gap is a significant concern, especially given the rising public apprehension about AI’s potential misuse across various fields. The newly published scoping review, a broad examination of existing literature, identifies a critical need for the industry to proactively address these ethical blind spots.
The comprehensive study pinpointed six converging themes of risk and ethical concern surrounding AI in gambling, highlighting areas where current practices may fall short.
Firstly, explainability is paramount. It is crucial to understand how AI reaches its conclusions, particularly when algorithms flag a player as being at risk of harm.
Without transparent AI models, often referred to as “black boxes”, it becomes difficult for operators, regulators and even players to trust the system or audit its decisions, potentially hindering the adoption of beneficial tools.
Adding to these concerns is the potential for exploitation.
AI, with its capacity to analyse vast amounts of player data, could inadvertently or even intentionally manipulate individuals. This risk is amplified by the addictive nature of gambling itself. Algorithms designed to maximise engagement might unintentionally reinforce harmful behaviours in vulnerable players, guiding them towards more “addictive” games or persuasive marketing tactics.
Disturbingly, research suggests many online gamblers remain largely unaware of these sophisticated, AI-driven influencing techniques.
Furthermore, algorithmic flaws present a substantial ethical challenge.
AI systems are inherently reliant on the data they are trained on, and any biases or gaps in this data can lead to unfair or inaccurate outcomes.
For example, if a dataset contains too few examples of genuinely at-risk gamblers, an AI designed to spot them might be unreliable. Missing crucial personal context – such as a player’s mental state, financial stability or underlying vulnerabilities – could also lead to algorithms inadvertently preying on individuals in distress, especially given the known links between mental health and compulsive behaviours. The very design choices, such as using self-exclusion as a sole indicator for problem gambling, have been questioned for leading to flawed risk detection.
This then naturally leads to concerns over consumer rights.
While regulations like Europe’s General Data Protection Regulation (GDPR) exist to protect data privacy and consent, their application to AI use in gambling is not always clear-cut. Questions arise when player data is leveraged for purported “wellbeing” initiatives without explicit consent, potentially overriding individual autonomy. Players need to be fully informed about how their data is used and why certain AI-driven decisions are made to ensure genuine freedom of choice.
Such transparency is closely linked to accountability.
It asks to what extent operators are open about their AI practices and how stakeholders, from players to regulators, can hold them responsible. While fostering trust, achieving true accountability can be difficult when AI models are proprietary “trade secrets”. This competitive advantage could lead to reluctance in sharing details, potentially necessitating regulation to ensure independent audits and compliance.
Finally, the principle of human-in-the-loop underscores the need for continued human oversight throughout the AI development and deployment lifecycle.
Even the most advanced AI systems in gambling, particularly those touching on player welfare, should involve human intervention and supervision to ensure ethical outcomes and prevent unintended harm.
The study highlights a crucial imbalance: most existing research on AI in gambling has concentrated on its application for harm reduction, rather than scrutinising its commercial uses, such as marketing and game design.
The authors urge for more attention to be paid to these profit-driven applications, emphasising that they too carry significant ethical weight that must align with gambling licensing objectives.
In conclusion, this research provides a timely impetus for the gambling sector. It urges regulators and operators to move beyond general AI principles and develop specific, tailored governance frameworks for this unique industry. Success in harnessing AI responsibly will depend not just on philosophical ideals but also on understanding and integrating the rich tapestry of global ethical traditions, ensuring a sustainable and trustworthy future for online gambling.
