text: **Risks and harm**
  
  **Privacy and copyright**
  
  Machine learning algorithms require large amounts of data. The techniques used to acquire this data have 
  raised concerns about privacy, surveillance and copyright. 
  
  AI-powered devices and services, such as virtual assistants and IoT products, continuously collect 
  personal information, raising concerns about intrusive data gathering and unauthorized access by third 
  parties. The loss of privacy is further exacerbated by AI's ability to process and combine vast amounts of 
  data, potentially leading to a surveillance society where individual activities are constantly monitored and 
  analyzed without adequate safeguards or transparency. 
  
  Sensitive user data collected may include online activity records, geolocation data, video or audio.[187] 
  For example, in order to build speech recognition algorithms, Amazon has recorded millions of private 
  conversations and allowed temporary workers to listen to and transcribe some of them.[188] Opinions 
  about this widespread surveillance range from those who see it as a necessary evil to those for whom it is 
  clearly unethical and a violation of the right to privacy.[189] 
  
  AI developers argue that this is the only way to deliver valuable applications. and have developed several 
  techniques that attempt to preserve privacy while still obtaining the data, such as data aggregation, de- 
  identification and differential privacy.[190] Since 2016, some privacy experts, such as Cynthia Dwork, 
  have begun to view privacy in terms of fairness. Brian Christian wrote that experts have pivoted "from 
  the question of 'what they know' to the question of 'what they're doing with it'."[191] 