  It is becoming cheaper to launch disinformation operations at scale using
AI-generated content, in particular 'deepfake' technology. We have observed
instances of deepfakes in political campaigns, where generated content is
employed to both bolster the credibility of certain narratives (reinforcing
outcomes) and manipulate public perception to the detriment of targeted
candidates or causes (adversarial outcomes). We discuss the threats from
deepfakes in politics, highlight model specifications underlying different
types of deepfake generation methods, and contribute an accessible evaluation
of the efficacy of existing detection methods. We provide this as a summary for
lawmakers and civil society actors to understand how the technology may be
applied in light of existing policies regulating its use. We highlight the
limitations of existing detection mechanisms and discuss the areas where
policies and regulations are required to address the challenges of deepfakes.
