- Machine Ethics
In Machine Ethics, researchers examine how computer science can be reconciled with human ethics. This encompasses two major areas. Firstly, it is the understanding that computer programs and systems can be unethical, and that this possibility needs to be allowed for and mitigated in the design process. For example, in data science algorithms have been shown to compound structural inequalities, such as racism or sexism. Research in this area aims to understand how these biases are embedded in our technology and how we can measure their effects with a view to minimising them. Other technology might be impartial in itself, but its use might impinge on people’s human or civil rights, such as privacy.
The second area of Machine Ethics explores if machines can be programmed to be ethical. This requires collaboration with other disciplines to understand what ethics are, and how they develop. The major question is if a machine can be programmed to make ethical choices and adapt to evolving situations, or if it can only be programmed to follow specific rules. Increasingly computers are taking on roles where they might have to prioritise actions based on ethical judgements, for example care robots. Machine Ethics explores if human intervention will always be required in order to ensure the machine’s ethical behaviour, or if an ethical framework can be designed and implemented in a way that is socially acceptable.
In Computational Sustainability, research focuses on using computers to address issues which contribute to climate change. This includes using computers and innovative algorithms to reduce waste and increase efficiencies. For example, solutions offered in smart energy grids will help to reduce electricity consumption and consequently c02 emissions. In intelligent transport systems where the traffic flow is managed more effectively the pollution will be decreased and a more inclusive and sustainable solution will be offered to citizens. Computer Scientists might also support climate scientists in data collection and analysis, or in modelling for resource efficiency or repopulation efforts in damaged ecosystems.
Computational Sustainability also refers to ensuring that the ecological impact of computers is minimised. As the world relies more and more on computers, the proportion of the world’s carbon footprint which is generated by computers increases. Designing systems which maximise energy efficiency is a growing area of CS research.