Eliot Michaelson

Philosophers have been thinking about lying for several thousand years, yet this topic has only recently become a central area of academic interest for philosophers of language, epistemologists, ethicists, and political philosophers. Lying: Language, Knowledge, Ethics, Politics provides the first dedicated collection of philosophical essays on the emerging topic of lying. Adopting an inter-subdisciplinary approach, this volume breaks new methodological ground in exploring the ways that a better understanding of language can inform the study of knowledge, ethics, or politics - and vice-versa. How can we lie when it is unclear what exactly we believe, or when we have contradictory beliefs? Can corporations lie, and if so how? Is lying always wrong, or always at least prima facie wrong? What can one learn from a liar? Can we lie to mindless machines? These engaging questions and many more are explored at length in this accessible reference text.

The aim of this chapter is to explore various ways of thinking about the concept of manipulation in order to capture both current and potentially future instances of machine manipulation, manipulation on the part of everything from the Facebook advertising algorithm to super-intelligent AGI. Three views are considered: a conservative one, which slightly tweaks extant influence-based theories of manipulation; a dismissive view according to which it doesn't matter much if machines are literally manipulative, provided we can classify them as so doing to make sense of our interactions with them; and an ameliorative analysis, according to which we should change our concept of manipulation better to make sense of machine manipulation. We tentatively favor the latter.

In addition to ordinary conversations among relatively small numbers of individuals, human societies have public conversations. These are diffuse, ongoing discussions about various topics, which are largely sustained by journalistic activities. They are conversations about news – what is happening now – that members of various groups (such as the residents of a certain country, a certain town, or practitioners of a certain profession) need to know about in their capacity as members of those groups, and about how to react to the news. Our topic in this chapter is a type of resistance to evidence that can arise at the level of these public conversations, rather than at the level of individual agents. We call it “relevance-based resistance to evidence”. A public conversation exhibits this kind of evidence resistance when it becomes overly focused on topics that members of the group that the conversation concerns do not in fact need to know about qua members of the group – topics which are, in a word, irrelevant. We argue that the risks of such relevance-based knowledge resistance are significantly amplified by certain structural features of online discourse.