INSIGHT ARTIFICIAL INTELLIGENCE
on social media, or interactions between a player and the customer service, and we are looking forward to investigating into those, too.
Machine learning can be very powerful in helping identify people at risk and flag them to operators. What is still missing is the next step. What can we do with this information?
Do you think that we will come to a point where machine learning can be used on its own as a way to prevent gambling related harm?
Currently, machine learning is used to flag players, but not much to engage with them so to help them not to lose control. Understanding what intervention practices are most effective is still the biggest unsolved issue in the gambling sector.
Tere is definitely room for machine learning to have a role in the intervention phase. For instance, AI chatbots could use the individual behavioural profiles for a first engagement with players flagged as at risk, and, through reinforcement learning, the quality of these automated interactions would continuously improve.
AI chatbots have been already used to deliver cognitive behavioural therapy (CBT) to people at risk of addictions in other fields, and it has been demonstrated that CBT can be effective at minimising gambling harm. But AI-delivered CBT for gambling has not been investigated yet in our industry, so there might be an opportunity here.
Whatever the role of machine learning in gambling harm prevention will be in the future, it is hard to imagine a scenario with no human supervision and intervention at all. Rather, machine learning can enable a far larger and more timely range of interactions, dramatically improving the level or players’ protection.
What developments can we expect to see in the machine learning space and responsible gambling?
What I would personally like to see – and expect – is more cooperation across the whole gambling industry. Tere are many machine learning initiatives and trials carried out by different operators, but often the findings are not shared with each other. Protecting the health and improving the well-being of each one of us should be a joined-up, industry-wide effort, and not a way to achieve a possible competitive advantage. Playtech is committed to publishing its learnings as we believe that by sharing our successes and especially our failures, we can learn collectively and help make the gambling industry sustainable in the long-term.
P100 WIRE / PULSE / INSIGHT / REPORTS
“There is definitely room for machine learning to have a role in the intervention phase.
For instance, AI chatbots could use the individual behavioural profiles for a first engagement with players flagged as at risk, and, through reinforcement learning, the quality of these automated interactions would continuously improve.” Francesco Rodano
“There are many machine learning initiatives and trials carried out by different operators, but often the findings are not shared with each other. Protecting the health and improving the well- being of each one of us should be a joined-up, industry-wide effort, and not a way to achieve a possible competitive advantage. Playtech is
committed to publishing its learnings as we believe that by sharing our successes and especially our failures, we can learn collectively and help make the gambling industry sustainable in the long-term.” Francesco Rodano
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