New Human-AI Research Teams could be the future of research, meeting future societal challenges
The University of Manchester is developing unique research teams to help cure humanity’s increasingly complex future health and societal problems by partnering researchers with Artificial Intelligence (AI).
Today, Professor Sami Kaski from The University of Manchester has been appointed among the first Turing Artificial Intelligence (AI) World-Leading Research Fellow. The fellowships, named after AI pioneer Alan Turing, are part of the UK’s commitment to further strengthen its position as a global leader in the field.
Through his fellowship, Professor Kaski aims to overcome a fundamental limitation of current AI systems, that they require a detailed specification of the goal before they can help. Machine learning, where solutions to problems are automatically learnt from data, is a form of AI with great promise for addressing a number of challenges. This includes healthcare, where AI can detect patterns associated with diseases and health conditions by studying healthcare records and other data.
As part of this new AI driven approach The University of Manchester has also today received a share of £4.4 million research funding from UKRI, in addition to contributions from the partners and the university totalling over £10 million. With these investments the university is further strengthening its fundamental research in AI.
For healthcare applications, the AI activity will build on the multi-million pound Christabel Pankhurst Institute for Health technology. The aim of the Institute is to capitalise on the University’s strengths in digital health, AI and advanced materials and develop innovative products and services for the health care sector. In turn this will drive business growth and employment as well as boost the long-term health benefits of the city region.
Artificial intelligence is still limited by the fact that human intervention is needed to set appropriate objectives and rewards to tell AI systems which outcomes are desired. This is difficult when we only partially know the goal, as is the case at the beginning of scientific research.
In drug design, for instance, the most advanced current tools are able to generate candidate molecules if we can specify a precise objective function for them. However, for us humans that is difficult to do – and if our specification is not perfect the intelligent system will very cleverly produce results we do not want. This is where the new approaches tools will help us.
This is where AI can help, but we need new kinds of AI assistants which can learn to work well with humans and complement their skills. That requires new fundamental AI research, and I am glad Manchester has recognized this opportunity and is considerably strengthening its AI research. Manchester is a top-notch place to build and apply new AI which matters and has impact.
The potential for AI in research and complex decision making is still relatively untapped. Now Professor Kaski, aims to develop new ways for machine learning systems to help humans in the process of designing experiments and interpreting what results mean, before deciding what to measure next, and to finally reach trustworthy solutions to problems. In lung cancer personalised medicine, for instance, to maximize effectiveness of radiotherapy for a new patient while minimising side effects, doctors need to combine their expertise and what can be learned from measurements from earlier patients.
Professor Kaski said: “This is where AI can help, but we need new kinds of AI assistants which can learn to work well with humans and complement their skills. That requires new fundamental AI research, and I am glad Manchester has recognized this opportunity and is considerably strengthening its AI research. Manchester is a top-notch place to build and apply new AI which matters and has impact.”
This new approach will be applied to three challenges: diagnosis and treatment decision-making in personalised medicine; the guidance of scientific experiments in synthetic biology and drug design; and the design and use of digital twins to design physical systems and processes.
Digital twins, a virtual representation of a complex objects or systems, can be built for patients for personalised medicine, but also for physical systems, such as complex buildings, a farm and even a city. With the twins it is possible to plan changes to roads, for instance, and anticipate effects on traffic and air quality.
An AI centre of excellence will be established at The University of Manchester, in collaboration with the Turing Institute and a number of partners from the industry and healthcare sector, and with strong connections to the networks of best national and international AI researchers.