Skip to main content

Challenges in Machine Generation of Analytic Products from Multi-Source Data Proceedings of a Workshop (2017) / Chapter Skim
Currently Skimming:

9 Session 8: Use of Machine Learning for Privacy Ethics
Pages 31-33

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 31...
... ) Because it is impossible to use hard-coded restraints for ethics, Riedl proposed an alternative way to address value alignment for artificial intelligence -- reinforcement learning involves trial and error in a simulated or real environment and rewards an agent's appropriate behavior accordingly.
Read the entire page →
From page 32...
... Procedural commonsense knowledge includes sociocultural conventions that reduce human–human conflict. Riedl pointed out that databases are being created to collect commonsense knowledge; however, declarative knowledge databases are missing information and, of course, contain no procedural information.
Read the entire page →
From page 33...
... Riedl noted that systems that are aware of sociocultural conventions or curated data sets do not currently exist, and researchers still do not know how to solve these problems using deep neural networks. Three to 5 years from now, Riedl expects agents to start using commonsense knowledge and world knowledge to address human needs; to engage in longer conversations; to rely on computational imagination; and to differentiate behavior based on cultural context.
Read the entire page →

Key Terms

  • reinforcement learning
  • value alignment
  • commonsense knowledge
  • sociocultural conventions
  • ethical artificial

  • machine enculturation
  • riedl explained
  • address human
  • deploying reinforcement
  • intelligence safety

  • address value
  • learning involves
  • riedl expects
  • human behavior
  • declarative knowledge

  • procedural commonsense
  • includes sociocultural
  • appropriate behavior
  • riedl proposed
  • using deep

  • understanding artificial
  • start using
  • learning agents
  • world knowledge
  • address broader

  • using reinforcement
  • differentiate behavior
  • using commonsense
  • intelligence understanding
  • curated data


    • This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
    More information on Chapter Skim is available.