An official website of the United States government
Begin with the end in mind!1 PhD students in artificial intelligence can start to prepare for their career after their PhD degree immediately when joining graduate school, and probably in many more ways than they think. To help them with that, I asked current PhD students and recent PhD computer-science graduates from the University of Southern California and my own PhD students to recount the important lessons they learned (perhaps too late) and added the advice of Nobel Prize and Turing Award winners and many other researchers (including my own reflections), to create this article.
more »
« less
Didn’t know, or didn’t show? Preschoolers consider epistemic state and degree of omission when evaluating teachers
- Award ID(s):
- 1640816
- PAR ID:
- 10041795
- Date Published:
- Journal Name:
- Proceedings of the Cognitive Science Society
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)To address the lack of comparative evaluation of Human-in-the-Loop Topic Modeling (HLTM) systems, we implement and evaluate three contrasting HLTM modeling approaches using simulation experiments. These approaches extend previously proposed frameworks, including constraints and informed prior-based methods. Users should have a sense of control in HLTM systems, so we propose a control metric to measure whether refinement operations’ results match users’ expectations. Informed prior-based methods provide better control than constraints, but constraints yield higher quality topics.more » « less
-
An extensive number of empirical research studies support the engagement of young children and youth in out-of-school science, technology, engineering, and/or mathematics learning experiences. In this case study, we add to this knowledge base through examining how rural middle school learners engage with science and math concepts and practices through an afterschool program that emphasized the development of STEM content, skills, and practices using the field of archaeology, as well as Indigenous knowledges, as mediums. Results highlighted how various syncretic approaches within the afterschool program afforded 61 middle school aged learners’ opportunities to engage with math and science concepts common to archaeologists and Indigenous peoples. We illustrate this through five “doings.” For example, learners engaged in similar science practices to Indigenous peoples through considering how local landscapes and the natural environment informed decisions regarding settlements. This study concludes with recommendations for professional archaeologists and educators to adapt and/or develop a similar afterschool program to support students’ participation as ARCH + STEM learners.more » « less
-
Many researchers and policymakers have expressed excitement about algorithmic explanations enabling more fair and responsible decision-making. However, recent experimental studies have found that explanations do not always improve human use of algorithmic advice. In this study, we shed light on how people interpret and respond to counterfactual explanations (CFEs)---explanations that show how a model's output would change with marginal changes to its input(s)---in the context of pretrial risk assessment instruments (PRAIs). We ran think-aloud trials with eight sitting U.S. state court judges, providing them with recommendations from a PRAI that includes CFEs. We found that the CFEs did not alter the judges' decisions. At first, judges misinterpreted the counterfactuals as real---rather than hypothetical---changes to defendants. Once judges understood what the counterfactuals meant, they ignored them, stating their role is only to make decisions regarding the actual defendant in question. The judges also expressed a mix of reasons for ignoring or following the advice of the PRAI without CFEs. These results add to the literature detailing the unexpected ways in which people respond to algorithms and explanations.They also highlight new challenges associated with improving human-algorithm collaborations through explanations.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
