Artificial Intelligence, or AI as it is known, has been around for a long time, though its progress up until now has been relatively slow. While we have robots that can carry out menial tasks and algorithms that can solve highly technical problems, some as life-changing as detecting new forms of cancer, doubts still remain over how a machine will ever reach so-called artificial general intelligence. That is the ability to combine vastly different types of problem-solving capabilities and learn to advance itself along the way – the hallmark of human intelligence.
The landmark in the latest robotic achievement – winning at poker – is that poker is a game played with imperfect information. Unlike with other games such as chess, poker players don’t get to see each other’s hands and are required to bluff and correctly interpret misleading information in order to win. Tuomas Sandhol, a professor of computer science at Carnegie Mellon University and creator of the poker-winning machine known as Libratus, described the challenge as one that is so huge and complicated that it has been elusive to AI researchers until now. Even going into the tournament, international betting sites put Libratus as the underdog at 4-1 and expected the humans to win.
Unlike with other such computer robots, Libratus wasn’t told how to play poker, instead it was given the rules and told to learn on its own. According to Sandhol, the bot, as he calls it, started playing randomly and over the course of playing trillions of hands was able to refine its approach and arrive at a winning strategy.
The algorithms that power Libratus aren’t specific to poker, meaning the system could have a variety of applications outside of recreational games, from negotiating business deals to setting military or cybersecurity strategy and planning medical treatment – anywhere where humans are required to carry out strategic reasoning with imperfect information.
The key thing to take away from this experience is that artificial intelligence is not something to be ignored. Now is the time for companies to embrace the phenomenon and learn how humans and computers can play off each other’s strengths to create competitive advantage.
While some tasks will, without doubt, be easily conducted by machines, other more highly-cognitive tasks will require partnerships between machines and individuals. As such, instead of scaremongering about how machines are going to take away our jobs – a recent report from Oxford University estimated that 47 per cent of US jobs could be automated within the next two decades, we need to take the opportunity to adapt our skills to take advantage of what machines are capable of and to work in tandem with them to develop complimentary roles and responsibilities.
In reality we are entering an era of cognitive collaboration in which machines can be used to help us make better decisions and it is time we learnt to use them to our advantage.
Earlier this year, Citigroup released a report entitled digital disruption, in which it said there was a huge cost take-out opportunity for financial institutions from the fast-growing area of regulatory technology. With a staggering $40.6 billion predicted spend on AI by 2024, it is vital we make it work for us. In the future, AI will form a critical part of every business’ infrastructure, making it vital for company decision-makers to understand how this technology can, and will, disrupt traditional models.
As financial firms already accustomed to using technology to help reach our goals, it is time to take things one step further and see how we can improve our customer and user experience. In short, how can financial institutions leverage digital transformation to advance their competitive position, strengthen customer engagement and improve performance?
In the past the focus was on increasing accessibility by facilitating the use of mobile devices. More recently it has been on information insight – providing consumers with products and services that meet their needs when and where they need them. Going forward, the key will be how you handle your data. Done correctly, financial institutions should be able to use this to make informed business decisions, providing their customers with the best possible user experience.
One of the main challenges facing these institutions is data complexity. With the amount of data in the world almost doubling each year, it is a challenge that shows no sign of abating. As a result, learning how best to extract meaningful and actionable intelligence from the raw data is essential if you are to stay ahead of the competition. This is where AI can help, as such tools are able to read, review and analyse vast quantities of disparate data quickly and efficiently. Still, while progress is being made in this area, there is one thing that AI cannot cater for in the short term and that is the fostering and maintenance of client relationships, product creation and innovation, as well as the insights for the future.
So, whatever your plans for the future, it seems embracing AI is a step in the right direction. The fact that no one is yet certain of the full potential of this technological development only enhances the opportunities and, providing you make your move soon, levels the playing field for all participants.