Track Record
Looking to the future with the Centre for Decision Sciences and AI at AMBS.
Artificial Intelligence has only recently entered everyday language, but AMBS has a long history of research in applied AI, says Nadia Papamichail.
Artificial Intelligence (AI) is shaping a new era, transforming the way we work, our industries, and the world around us. Yet even though AI has very quickly become an integral part of our vocabulary over the past year, it is not a new concept. In fact, AMBS has a long history of research in applied AI for facilitating decision making processes.
Large datasets
AI can help decision makers by analysing large datasets, detecting patterns, and making recommendations of optimal solutions. As such it is little surprise that as data grows and digital technologies evolve, so organisations are increasingly turning to AI powered decision tools to gather intelligence and drive decisions.
Established in 2010, the Centre for Decision Sciences and AI at AMBS has a track record of delivering successful collaborative projects with industrial partners by developing optimisation models, explainable decision algorithms and AI powered decision tools.
We have a longstanding history in the application and deployment of Multiple Criteria Decision Analysis (MCDA) for tackling complex decision problems in the face of conflicting objectives, multiple stakeholders and uncertainty.
Name change
Until recently the Centre was known as the Decision and Cognitive Science Research Centre and it has thrived under the leadership of Professor Jian-Bo Yang for many years, with a rich portfolio of research activities and projects.
Our new name reflects our roots in decision sciences. But it also embraces the world of opportunities that arise from our AI capabilities given that we are a well-established centre of research and innovation that seeks to harness the power of decision sciences and AI to help individuals, groups and organisations make faster and better decisions — while also making a positive impact on society and the world around us.
The Centre draws on our academic expertise and we help businesses augment business performance and facilitate well-informed decisions. Specifically, our members conduct research in the critical areas of decision sciences and AI including decision analysis, optimisation, machine learning, evolutionary computation, data analytics, simulation, probabilistic modelling, risk analysis, explainable AI, AI ethics, responsible AI, decision support systems and behavioural data science and behavioural decision-making.
The Centre for Decision Sciences and AI has a track record of delivering successful collaborative projects with industrial partners by developing explainable decision algorithms and AI powered decision tools.
AI ecosystem
The University of Manchester is committed to AI research and our Centre will continue to be an integral part of the University's wider AI ecosystem. For instance, our members have been contributing to a number of programmes ranging from executive education courses to the MSc Business Analytics programme, ranked 17th in the world and third nationally (QS Business Master's Rankings in Business Analytics 2024).
Together with Centre Co-Director Prof Yu-wang Chen, our commitment to innovative research will continue. For instance, we are strong in delivering projects that help organisations gain strategic advantage through the use of decision sciences and AI, and our members have been involved in projects that optimise processes such as claim management and product development by generating insights from data and customising customer journeys.
We also have an established track record in areas such as legaltech and fintech where we have run a series of successful Knowledge Transfer Projects.
Data and AI for Leaders
Build confidence in your understanding of data and AI and use emerging technologies to your advantage.
Personal experiences
Looking ahead, we expect demand for conversational interfaces and chatbots with personalised recommendations and experiences to continue to rise. As such we will continue to work on human-in-the-loop solutions by combining machines and humans to yield better results.
We are also committed to developing ethical and sustainable decision aiding tools because we recognise that those using our digital solutions will be preoccupied with accountability and transparency concerns alongside decision-making accuracy and speed considerations.
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