  Automated text generation has been applied broadly in many domains such as
marketing and robotics, and used to create chatbots, product reviews and write
poetry. The ability to synthesize text, however, presents many potential risks,
while access to the technology required to build generative models is becoming
increasingly easy. This work is aligned with the efforts of the United Nations
and other civil society organisations to highlight potential political and
societal risks arising through the malicious use of text generation software,
and their potential impact on human rights. As a case study, we present the
findings of an experiment to generate remarks in the style of political leaders
by fine-tuning a pretrained AWD- LSTM model on a dataset of speeches made at
the UN General Assembly. This work highlights the ease with which this can be
accomplished, as well as the threats of combining these techniques with other
technologies.
