We’re at the cutting edge of lots of different industries and technical approaches. Here we talk about some of the hot topics that are widely discussed.
- Data – the issues of availability of data, its quality and connectivity cannot be underestimated. We find the problem of data impacts almost every project.
- Open source – there have emerged many great programmes, libraries. This is fantastic because it is free, it is often higher quality and it stays fresh because it continues to be developed.
- Multi-disciplinary teams of experts with each member bringing different skills, experience and outlook to a problem that otherwise could not be solved by traditional methods.
- Making tools accessible and really designed around the user and the decision they make. This brings together the model developers, interface designers, human factor experts and most importantly the users.
- Sustainability – this is no longer a fad. Almost all the companies we work with have this point high on their agendas and are actually doing something about it. Our work is increasingly supporting this: reducing leaks in the water network, factoring environmental priorities in infrastructure maintenance, minimising energy use.
- Handling uncertainties when making optimal decisions now that are flexible enough to deal with whatever happens in the future. It’s not enough to plan for the expected outcome: planning and the decision support needed has to take into account the probabilities of what could happen.
- Deep reinforcement learning where machine learning and simulation come together to provide the latest advances in AI.
- Explainability in modelling – it is now often a requirement not just to deliver a model, but also have it so the model explains the results. It’s a really important matter when we talk about making some of the technologies that support critical decisions, particularly for problems that could impact lives.
- Bias – resolving the problem of bias in models, and particularly artificial intelligence, is increasingly important. This is something that needs to be addressed now.
- Trust and ethics. How can we create trust in the tech systems? How can we ensure models, and particularly AI, follow ethical practices? Building trust in interaction between the humans and machines and ethical AI are hot subjects.
