I recently led a session at the eResearch Australasia conference on the ethics of AI in higher education. It is a big topic to handle, and I’m pretty new to this stuff, but the conversation went pretty well, and the awareness of both AI and ethics is high in this community. The ethical challenges posed by AI are significant, but the benefits are also great, and it is vital for educators and citizens to be aware of both. Here are some of the key points made by the audience (and I am pursuing the topic, so will post some more later on).
After many false dawns, AI may be gaining traction. Chatbots, Natural Language Processing, robots, autonomous vehicles, and the combination of big data and AI are all findings applications in a myriad of commercial, educational and other contexts. AI was once about explicit commands; what you put in is what you got out, but now it is largely about machine learning and big data, about machines that not only learn, but also make decisions. This is behind a number of new and emergent applications in medicine, transport and education that hold great promise but also ethical challenges.
In particular, it is an ability to ‘make decisions’ that poses numerous ethical dilemmas; can an autonomous Volvo car chose to collide with either a pedestrian or a dog ‘ethically’; can a Google chatbot impersonate a human for nefarious purposes, and can an autonomous military drone decipher images of illicit activity and then take autonomous action? These are not dystopian projections of a sci-fi future, rather these ethical issues that exist now well within the province of AI and its applications.
Whilst ethicists have provided critique, debate, and numerous ethical frameworks for an AI future, (indeed the Australian Government has just proposed a “technology roadmap, a standards framework and a national AI Ethics Framework”, and regulation in the space), higher education has been relatively quiet in terms of debating the impacts of AI on teaching and research and the broader HE education system. Indeed, while AI applications are not yet fully realised in research, this could opportune time to think about them, before they are (and this change could occur quite rapidly as did the use of data in research across both the humanities and the sciences).
Some of the ethical issues posed include the stalwart of IT ethics, being privacy, but also new issues arise, particularly around transparency and the interpretation of data using machine learning and how these interpretations may influence later research findings, be credited as research work, and indeed impact upon broader society. This is a particularly difficult issue as AI does afford many benefits in terms of the researcher’s ability to deal with the scale and complexity of big data, but there are things that machines are good at and things that people do better, and this intersection of machine and people intelligence, including ethical decision making, needs to be considered from the very emergence of AI in research.
Pollit, Edward. “Budget 2018: National AI ethics framework on the way, Increased regulation signalled as part of $30m investment” Australian Computer Society, https://ia.acs.org.au/article/2018/budget-2018–ai-boost-with-an-ethical-focus.html (Accessed 13 June 2018).
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