New project: Generative AI research practice – funded by Advance HE

A cross disciplinary groups of experts from Staffordshire University have been awarded a Collaborative Development Fund grant by Advance HE to develop and support postgraduate research students.

Project overview

Generative AI (GAI) presents a paradigm shift for research practice; Sabzalieva and Valentini (2023) identified a range of possible uses including during the writing, research design, data collection and data analysis stages and Nordling (2023) found that 33% of postdoctoral researchers use ChatGPT to support their research. However, those numbers may well be exception in disciplines where AI technologies are integral to the science, most researchers are currently novices in terms of understanding the opportunities and limitations of GAI in their own disciplinary and research contexts. This project will also consider postgraduates on taught and doctoral programmes as well as those supervising them, and those leading the governance of programmes and research practice.

As researchers increasingly deploy GAI, there is a need to ensure that they are
aware of its potential and limitations, know how to evaluate the reliability and validity of outputs and understand its wider societal, ethical and integrity implications.

This project will work with postgraduate students and doctoral supervisors to:
(i) Co-create, deliver and evaluate an experiential workshop programme of workshops
exploring the application of GAI technologies in five different areas of research practice:
a. Literature reviews and synthesising of existing research
b. Reviewing and re-purposing own research for different audiences
c. Translation and undertaking research in another language
d. Qualitative Research skills
e. Researcher career support
(ii) Integrate cross-disciplinary activities to enable participants to:
a. Review, compare and critically evaluate the usefulness, validity, and reliability of the
GAI outputs for different research processes, methodological and disciplinary
contexts.
b. Explicitly consider the societal, ethical and integrity implications of utilising GAI in
these contexts.
(iii) With participants, co-create a set of principles for GAI for consideration by senior leaders in HE.
(iv) Disseminate the outcomes as re-usable learning objects and case studies for use by those involved in supporting researcher development

Timeline

Jan 2024 to June 2024

Project team

Overall lead: Dr Jane Wellens – Head of the Graduate School e: jane.wellens@staffs.ac.uk

Prof Jon Fairburn – Business School e:jon.fairburn:@staffs.ac.uk

Craig Holdcroft, Lecturer in Digital Marketing, Business School e: craig.holdcroft@staffs.ac.uk

Gary McNally, Research Training Manager gary.mcnally@staffs.ac.uk

Dr Jim Pugh – Director of the Institute for Education j.pugh@staffs.ac.uk

Other partners

UK Council for Graduate Education

Other resources

For any staff or PGR student interested in AI issues – Jon Fairburn and Gary McNally have already established a pan University MS Team to discuss and co-ordinate activity in this area – feel free to join.

AI and research

You may also be interested in another of our projects Digital Stoke which is researching the size, characteristics and growth of the digital sector.

How YOUR Business Can Benefit From Machine Learning!

It is no secret that the landscape of marketing is changing, with a huge shift in activity from traditional methods to digital marketing methods. Machine Learning is at the absolute forefront of this change, and is tipped to be the key to successful business online.

What is Machine Learning?

Machine Learning (ML) is closely related to Artificial Intelligence (AI), a topic of discussion that is prevalent not only in marketing, but as a cultural issue. ML is the application of AI to systems, allowing them to learn from experience. This involves complex algorithm’s that allow a machine to use data to produce predicted outputs.

In marketing terms, this means that a program can gather relevant information, analyse it, and give a specific output, whether that is a prediction or action. This is an exciting prospect for businesses as it can lead to increased efficiency and decreased costs.

So, how can you, as an organisation, utilise machine learning?

Utilising Big Data – 

Digital is growing rapidly, and is fuelled by the amount of data available online, labelled as ‘Big Data’. IBM reported in 2013 that 90% of the world’s data had been produced in the last 2 years. Although this number may seem overwhelming, analysing it is HUGE business, with International Data Corporation predicting it to reach a value of $203 billion in 2020.

With this mass of data, analyst’s need the help of machines if they wish to be able to analyse it fully. Data Analytic programs allow this to an extent, but ML programs, such as Torch, have the ability to spot hidden correlations and patterns in this data, which can be used strategically.

Chat bots – 

Creating a dialogue with customers is crucial to businesses online, and one way to do this effectively is to use chat bots. Chat bots are becoming increasingly popular, and with good reason. Using a chat bot, a customer can open a dialogue to, for example, buy a coat. In this example, a customer would message the business through a messaging app such as Facebook Messenger, and the bot would then reply. The customer would then tell the bot what style/colour of coat it desires, and the bot would provide you with options matching your needs.

As a business, it allows you to communicate with huge numbers of customers on an individual basis, without the need for humans for each customer. This not only saves costs, but is a method that is increasingly preferred by customers, especially millennials. Although Chat bots are already beginning to revolutionise customer service, it is important to realise that the tool is still in its infancy, and so inevitably as technology advances, more and more opportunities concerning them will arise.

Image result for chat bot

Recruitment – 

Another way ML can improve your business activities involves recruitment. This is no more apparent than in ML tools used by companies like Zoho, such as Spark, which allows you to flip the equation in job searching – instead of candidates giving information and a list of vacancies being provided, Zoho uses information regarding the vacancy provided by the business, and supplies a list of candidates that best fit the role.

This can benefit your business because it ensures your prospective employees possess the traits you are seeking.

Oho landing page

Content Management –

With the swathe of content available to consumer’s, it is only natural that it becomes difficult for them to find the content they want to see. Businesses can address this problem through machine learning. By using a machine learning platform, businesses can use the data from previous content consumers have interacted with to predict other content that would be liked, and to ultimately produce content that resonates with their consumer’s. One such example of this is Pinterest. Pinterest use the previous images that their users have ‘pinned’ to suggest other images and content that users would like to see.

Image result for pinterest

This is Just the Start!

The benefits listed above should make it clear that ML has immense potential for business and marketing. It is now being used by giant companies, such as Google and Amazon, but there is no reason smaller companies could use it with just as much benefit. As the technology behind this area grows, organisations will be able to interact with and influence consumers like never before. Make sure you aren’t left behind.

Does your business use machine learning? How does it benefit you? What other benefits are available to businesses through this platform? Please share your opinion below.


by Rory Tarplee

LinkedIn

MSc Digital Marketing Student (Full Time)