Robot Pool: Who Wins When AI Takes the Shot?

You’re playing pool, snooker, or billiards if you are of a certain age.

The rules are the same as usual, and you are playing against a good friend who is highly competitive. Much as you like your friend, they really like winning and will seldom let you forget if you lose.

Winning is, therefore, a big thing for both of you.

So, to help you win, both of you agreed to have an AI robot helper. This robot AI can make shots on the table with its clever robot arm, play pool as well as you, learn every time it takes a shot to get better and watch you and your friend take their shots. The only restriction is that you can use the AI every other shot and not all the time.

Both you and your friend alternate turns to take shots, first you, then them, then your robot AI, then their robot AI, before returning to you. After a while, you realise that your robot AI is particularly good at getting out of tricky situations and can play shots you usually miss when stuck behind another ball.

Now, towards the end of the game, it is very close. Your robot AI player has got you out of several tricky situations, and you’ve been able to pot most of your target balls. Your friend has your cue ball stuck in a corner, but if you can make the shot, you will win the game. But if you miss it, your friend will very likely clean up the table.

Already, they are looking unbelievably smug at how they have snookered you. Surely you cannot let them win and face further smugness?

It’s your robot AI’s turn to take the shot and possibly win the game. Do you let the robot take the shot?

Of course, many of us will read this story and believe, quite honestly, that they would stride forward, push the robot to one side, play the shot of their lifetime and win the game. Hurrah! We like to see ourselves as winners, but letting a robot win on our behalf doesn’t really feel like winning.

Yet, facing your friend’s smug face, many of us would let the robot AI take the shot. We would tell ourselves that it’s the robot’s turn and that we’ve played as a team the whole game. If it were the other way around, of course, we would take the shot, but just this once, it looks like the robot AI will win, and that’s precisely within the rules of the game.

We would hand over to the robot AI exactly how game theory would suggest we behave.

The Game Situation

Now, let’s change the narrative slightly. In this game, your friend has let their AI play every shot. They are so smug and confident that they believe their AI can beat you without your friend taking a single turn. So far, you have stayed in the game and now find yourself in the same situation. You are in a tricky position; you must make the shot to win the game, and it’s your robot AI’s turn to play the shot.

Your friend and even their robot AI are now looking at you smugly.

Would you still stride forward and take the shot, or let your robot AI, with a slightly higher probability of success, take the shot for you?

In this scenario, when playing against a robot AI on behalf of your friend, most people will let your robot AI take the shot and cheer loudly as the ball rolls into the pocket, and you win the game. You would feel no shame in letting your robot AI take its turn as, after all, your friend’s robot AI has taken every turn for them. Take that, smug friend and their even smugger robot AI!

These situations are precisely where we find ourselves in the adoption and deployment of AI. For the last decade, there have been well-intentioned and deeply considered reports, studies, conferences, and agreements on AI’s ethical and safe adoption. Agreements, statements, and manifestos have been written warning of the dangers of using AI for military, police, and health scenarios. Studies on the future of work, or lack of it, abound as we face an employment market driven by AI.

We would all agree that any AI that harms, damages, restricts or prevents human ingenuity or freedom would be a step in the wrong direction. We are all on the side of ethicists who say that death at the hands of a killer robot should be banned. We would all want to ensure that future generations can work with dignity and respect for at least a liveable wage.

We would agree until competition enters our lives.

Facing the AI Dilemma

Our brave adoption of ethical AI principles may face a more substantial test of winning or losing. At that point, would we remain ethical if losing looks likely? Would our ethical principles remain if faced with defeat by an enemy using AI to win? Applying game theory to these scenarios indicates a bleak future.

We all know that collaboration and working together is often better for us all. It is the basis of modern civilisation. We may also know that tit-for-tat with occasional forgiveness may be a better-winning strategy than cooperation, but only if we can trust the other person to vary their pattern. Suppose the other player always goes for the negative but advantageous choice. In that case, any competitor will likely follow the same harmful path.

We can see where this approach is heading if the favourable option is partial AI adoption and the negative is complete AI replacement of a service or function with AI. For instance, an organisation or company that fully adopts AI in their call centres will seize a competitive advantage over others who retain human operators. Their competitors may argue that retaining employees is the right thing to do, that customers prefer real human interaction even if they struggle to tell the actual difference, or that there is a brand advantage to retaining humans in their service.

Ultimately, though, the AI service will prove significantly cheaper and, based on current deployments, will provide at least as good a service as human call centres for most scenarios. Customers of recent AI call centre deployments show that they cannot tell the difference between humans and AI. Faced with such a choice, will a competitor keep the equivalent of playing their own pool shots or hand over part of their service to a robot AI?

The immediate impact is faster service as the wait time for an operator disappears and a significant reduction in operating costs. The business may use these savings to create better services and products, invest in reskilling call centre staff, or use them as profit and reward.

In the longer term, the impact of this simple game decision, scaling across call centre companies, would be much bleaker.

When 4% of the UK workforce, around 1.3m people, work in call centres, we can begin to feel the impact of such a decision. In the region of Newcastle, North East England, there are 178,000 call centre employees, primarily female. These workers are often the only income earners for their families after the manufacturing sector in the area collapsed due to cheaper foreign alternatives and manufacturing automation.

A few companies may avoid this movement and value their human employees more than their profits, revenue, or shareholder return. They may ensure alternative employment is found for their workers or provide reskilling initiatives. The reality is that most will be unemployed, with few transferable skills, and in a region with the highest unemployment rate in the UK.

The AI Adoption Conundrum

When faced with a snooker game where one company adopts AI, the competitors will quickly follow suit. Unlike previous automation waves, like in car manufacturing, which took place over several years, this wave will be quick. Service sector work, especially work centred on information and data, can be quickly automated in months rather than years.

That timescale does not allow the creation of alternative jobs, new skills to be learned, or employment opportunities. It is at a pace that most people would struggle to comprehend or manage, let alone emerge from with better prospects.

The impact rapidly expands beyond the individuals struggling to find employment. The first impact would be a surge in benefit claims, increasing government expenditures. At the same time, employees’ income tax payments would vanish, and their employer’s national insurance payments would cease. Costs would rise, and tax income would decrease. Local expenditures would diminish, impacting other businesses and employment.

This pattern is seen in the Northeast and similar cities like Detroit, US. In the 1980s, heavy industry and manufacturing collapsed. In 1986, as an example, Newcastle was reeling after the Royal Ordnance factory closed (400 jobs), two coal mines closed (2000 jobs), shipyard closures (3000 jobs), British Steel mills (800 jobs), NEI Parsons (700) and Churchills (400). Over 7000 unemployed in 12 months, and these were just the large employers. Countless small businesses also closed at the same time.

The consequences of these closures in the Northeast were decades of stagnation until service industries, like call centres, eventually moved into the region, and employment picked up once more.

Now, we stand at a similar crossroads. Still, this time, the threat of AI-induced job displacement looms over the very service sectors that once revitalised communities. The allure of efficiency and cost-cutting is undeniable. Still, the human cost could be far steeper than any short-term gain. Just as in the pool game, where we were tempted to hand control over to a robot AI, in the real world, businesses and individuals may find themselves willing to let AI take over vital tasks for the sake of winning in a competitive market.

However, unlike in the game, the stakes here are much higher. While letting the AI play might win you a single match, relying too heavily on AI in society could unravel the social fabric of entire regions. The ripple effects of AI replacing human workers are not confined to immediate job losses; they extend to the erosion of livelihoods, communities, and human dignity.

The lesson from our robot AI pool game is clear: the allure of short-term victory should not close our eyes to the long-term consequences. Winning at any cost, whether in a friendly match or business, often leads to outcomes that benefit only a few while leaving many behind. We must approach AI adoption not merely through the lens of efficiency but with a deep sense of responsibility toward our workforce and broader society. In the game of life, true victory lies not in replacing humans with AI but in finding a balance that empowers both to thrive.

Can we do that?

Next week's article will explore what happens when we apply this game theory approach to the battlefield with a real-world example