Research Environment

Doctoral Research Education.

Graduate Research is our highest level of education, developing PhDs and advanced researchers for both society and the Academy. In most universities, the Doctoral cohort is the smallest by numbers, but often drives impact that far outweighs its size. The research education environment is changing in response to 4IR, but there is much work to be done to keep pace. 

Engagement with sociotechnical systems are an everyday part of higher education environments in the 2020’s.

PhD graduates moving into industry.

Today’s doctoral graduates looking to work outside of the Academy require technical and non-technical skills. In the World Economic Forum’s (WEF) Future of Jobs Report 2018 the top ten list of growing skills included ‘soft’ skills of: active learning and learning strategies, creativity and originality, leadership and social influence, and emotional intelligence. Declining skills included those that machines are outperforming humans at, such as: memory, reading and math, time management, technology maintenance, and technology use. That is not to say that reading and math are no longer desirable attributes in candidates, it is that according to the findings of the WEF these skills are ranked by employers as having less importance.

Source: World Economic Forum, The Future of Jobs Report 2018 Leopold, 2018. Declining skills does not mean they are no longer desirable in candidates, they are just ranked as having less importance than the skills listed under “growing”.

On-going academic jobs for doctoral graduates are becoming increasingly scarce, a situation exacerbated by the COVID-19 pandemic, and more students are looking for non-traditional academic careers. More doctoral graduates are moving into external workplaces and requiring more employable skills than just the development of a thesis may give them. Even where graduates do stay in the academy, many research positions require some collaboration with external industry stakeholders, the ability to communicate with the public, and an understanding of the systemic impacts of their research on society, economies, and the natural environment.

As graduates move out of traditional academic environments into industry arenas where the hypercompetitive adage ‘move fast and break things’ is giving way to corporate sustainability and ethical inclusivity, it would behove them to be equipped with a wide range of 4IR-ready qualities. Universities should help develop the employment skills and qualities doctoral students need for work and ethical leadership in 4IR. There is undeniably scope for a more university-wide, interdisciplinary approach to equipping PhD students with the skills of 4IR technology ethics.

In the early 2020’s a PhD Graduate is less frequently seen as the sum of their thesis and published papers and more often expected to show a roundedness of qualities and skills. Identifying what skills and qualities are needed in the fourth industrial revolution (4IR) is one part of the work of my project, understanding how to facilitate doctoral candidates to develop and demonstrate these skills is the natural next step. As many doctoral graduates go on to leadership roles in research-based jobs, an enhanced understanding of how their work intersects with 4IR technologies, such as AI, in an ethically responsible way has become critical for the development of equitable societies and a sustainable planet.

A disruptor and a shift.

This PhD project work is situated in the research education environment in the early 2020’s, a timeframe that necessarily now includes the impacts of the COVID-19 pandemic on doctoral student experiences. Within research education I have focussed on doctoral degrees to enable better comparisons between different international education systems.

The effects of the 4IR-shift and the COVID-19-disruptor on doctoral preparedness for work are important when considering increasingly mis-aligned numbers of academic positions to graduates. I conducted work into the impacts of the pandemic on research students in April 2020 resulting in a 100-page report to senior leaders in research education in Australia and a subsequent paper currently in review. In the first two months the pre-print was viewed 4,400 times and was reporte on in Nature, The Guardian, The Conversation, and by the Australian Academy of Science.

For the full impact of the early work click here: The Quiet Crisis of PhDs – not so quiet anymore!

To view the pre-print click here: The Quiet Crisis of PhDs and COVID-19: Reaching the financial tipping point.

This research project addresses the need for a better understanding amongst doctoral candidates of how their work either intersects with AI technologies during their project, or how the datasets and knowledge they create may be used by future researchers employing AI technologies. It is expected that by facilitating PhD students’ to better future-proof their work to be ethically sustainable if future technologies intersect with their research, graduates will develop some of the most highly sought 4IR employability skills.

At the recent Times Higher Education World Academic Summit, the senior vice president for Elsevier noted the huge increase in demand for ethics and AI university courses . At the same conference a leading UNSW professor of ethical AI, Toby Walsh, said that more important than technical AI skills was for people capable of designing “the policy, formal and informal, that allows us to trust decisions taken by machines”.

The point here is that ethical AI is not going to be solved by making sure everyone has great coding skills and regularly attending hackathons; that is counter to interdisciplinary inclusivity. A broader contextual understanding of the how AI technologies fit within the system, from a range of perspectives and biases, is essential if we are serious about making a lasting impact on this problem.

Why STS approaches for PhD students?

Generally, doctoral candidates don’t aim to be destructive when using 4IR technologies to enhance the impact of their research! It is usually the case that a lack of systems planning causes deleterious and unanticipated effects. Systems considerations in doctoral research might include factors such as how data framing, collection, tagging, or algorithmic analysis could cause negative systemic impacts not immediately obvious to the researcher. Improving systems thinking would likely help doctoral researchers better plan the impacts of their work, even beyond their own degree. Facilitating enhancement of ethical AI related systems thinking can help future-proof their research and provide a valuable employability skill.

The benefit of sociotechnical systems (STS) approaches to ethical intersections of AI to a candidate’s research is that the researcher does not need to be a computer science expert or even proficient in coding AI. An STS framework would help students consider their work in a broader techno and social context. Approaching the ethics of AI in this way opens the door for more social scientists and philosophers to contribute to the field, as well as political, governance, legal, communications, and other humanities researchers.

Image credits

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