There is currently no agreed upon typology of ML algorithms (Benbya et al. 2021). In our sample of n=62 adversarial attacks on ML systems, we found that practitioners referred to four types of algorithms:
• Object or image classification algorithm (16%): Takes images as inputs and classifies them (e.g., Google Cloud Vision) or uses sensors to classify objects in the environment (e.g., self-driving car).
• Recommendation algorithm (2%): Analyze user behavior to make recommendations. For instance, Facebook’s friend recommendation algorithm analyzes users’ followers, followings, common friends between followers, and recommend who they can follow.
• Facial or speech recognition algorithm (30%): Takes audio or an image of a face as input and grants access to the user based on the features detected (e.g., Apple iPhone face ID or Alexa voice- activated assistant). Other facial or speech recognition algorithms recognize faces in an image or voices in an audio input.
• Detection algorithm (31%): Detects anomalous or suspicious activity like malware in an email, fraud in a transaction, or deep fakes.
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