In an interim report, available here, the authors outline the progress of AI tools and techniques that are driving a “fourth industrial revolution”. They also discuss exactly how the research landscape may be impacted.
Tools and techniques of interest
- Image classification
- Object detection
- Automated data monitoring
- Automated experiment selection
- Simulation and prediction of physical systems
- Parallelisation
- Content generation
- Natural Language Processing
New tech is not simply impacting the way that research is being conducted but is influencing the ways that data is captured, shared and evaluated. Tech will continue to drive and support open access and data sharing. Processes such as peer review and funding may be increasingly automated.
What happens next?
The next stage of the project will seek to address key policy questions:
- What are the barriers to adoption in academia?
- What effect will tech developments have on research career paths?
- Will the greatest gains to academic productivity come from the automation of administrative tasks?
- What might be the impact of automating grant writing?
- Will academia be able to afford the computational power necessary to compete with technology companies on AI-enabled research?
- Should governments provide more shared access to computational power?
- How can AI-assisted peer review help maintain research standards
- Is the Research Excellence Framework (REF) in its current form suitable for AI-generated papers and research?
- What are the implications of using automated processes in research planning and management?
- How can we encourage greater collaboration between academia and technology companies?
- Can AI-assisted peer review reduce the lag time between research and publication?
- Is training young researchers in computing and coding the most effective way to prepare them for an automated future?
- How can we sufficiently invest in universities’ digital infrastructure to ensure they can undertake world-leading automated research
- Do we need stronger data protection rules for the storage or sharing of human research subjects’ data in the cloud?
- How can we ensure that those working in AI are aware of the ethical dilemmas and challenges they may face in their work?
You can read more about the research project here.