Knowing What You Neeed to Know

Knowing What to Believe (when you already know something)

Although much work in NLP has focused on simply determining what a document means, we also must know whether or not to believe it. Fact-finding algorithms attempt to identify the “truth” among competing claims in a corpus, but fail to take advantage of the user’s prior knowledge and presume that truth itself is universal and objective rather than subjective. We introduce a framework for incorpo...

The benefits of knowing what you know (and what you don’t): How calibration affects credibility

People tend to believe, and take advice from, informants who are highly confident. However, people use more than a mere ‘‘confidence heuristic.” We believe that confidence is influential because—in the absence of other information—people assume it is a valid cue to an informant’s likelihood of being correct. However, when people get evidence about an informant’s calibration (i.e., her confidenc...

Do you know what you don't know?

Stick To What You Know

Iwill be arguing that a subject’s belief thatp is justified if andonly if heknows that p: justification is knowledge. I will start by describing two broad classes of allegedly justified beliefs that do not constitute knowledge and which, hence, cannot be what they are often taken to be if my view is correct. It is far from clear what my view is until I say a lot more about the relevant concept ...

Knowing What to Imitate and Knowing When You Succeed

If we are to build robots that can imitate the actions of a human instructor, the robotics community must address a variety of issues. In this paper, we examine two of these issues. First, how does the robot know which things it should imitate? Second, how does the robot know when its actions are an adequate imitation of the original? We further describe an on-going research effort to implement...