BEGIN:VCALENDAR VERSION:2.0 PRODID:-//events.la.psu.edu//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:STANDARD DTSTART:20201101T020000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD BEGIN:DAYLIGHT DTSTART:20200308T020000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:17708-0229d95ddb9c662ff2b1a5b376124d30@events.la.psu.edu DTSTAMP:20260307T150120Z DTSTART;TZID=America/New_York:20251106T140000 DTEND;TZID=America/New_York:20251106T150000 SUMMARY:Consortium Workshop: Nick Byrd DESCRIPTION:\nHow Can We Improve Our Decisions? Results From Multiple Me thods And Experiments\n\nNick Byrd\, Ph.D.\n\nAssistant Professor of Cog nitive Science\n\nGeisinger College of Health Sciences\n\nDepartment of Bioethics and Decision Sciences\n\nNobel laureates like Daniel Kahneman popularized research about cognitive biases. To better understand and am eliorate these reasoning errors\, we have been developing more scalable methods to (a) trace reasoning processes and (b) improve faulty reasonin g. So far\, we have run at least a dozen experiments involving thousands of participants. Consider some examples:\n\nThinking aloud is a common critical thinking exercise in education\, computer science\, and other a nalytic decision-making contexts. Alas\, legacy methods of recording peo ple as they think out loud are time consuming. Also\, thinking aloud may use cognitive resources that could otherwise be spent on improving deci sions. To address these issues\, I partner with startups to develop web apps that remotely (and consensually) record and transcribe people’s rea soning process (e.g.\, from the microphone on the participants’ smartpho ne)\, which drastically expedited data collection and transcription — fr om months to hours. Behavioral results have improved our understanding o f what reflection tests measure and how people overcome faulty intuition s.\n\nDebate is supposed to enhance intelligence analysis\, policymaking \, and other forms of critical thinking. However\, facilitating debates require significant human resources. So\, we developed web apps to autom atically facilitate solitary and discussion-based reflection with varyin g financial incentives. This allows hundreds of debates to be recorded i n parallel from afar\, drastically accelerating data collection and tran scription. Our quantitative decision analyses find that conversation can be better than cash in terms of improving decisions.\n\nOur thinking-al oud\, writing\, and chatting protocols also yielded decision transcripts  that contain much more information than standard survey data. Research assistants\, crowd workers\, and language models can categorize and quan tify aspects of these step-by-step decision records. The resulting ratin gs allow us to quantitatively test the assumptions of cognitive tests an d isolate which reasoning patterns actually predict better decisions.\n\ nWe are also testing interventions such as information formatting (e.g.\ , argument mapping or data visualization)\, philosophical reflection (e. g.\, thought experiments)\, testing effects (e.g.\, having people comple te some reasoning test items before the primary test of reasoning)\, nud ges (e.g.\, text message reminders)\, and boosts (e.g.\, educational inf ographics).\n\nUltimately\, few interventions reliably improve decisions . And some popular interventions seem ineffective in improved research d esigns (e.g.\, with larger samples\, better data\, better measures\, or more controlled variables). This presentation will dive deeper into the methods and results.\n\nFor Zoom link email Daryl Cameron at cdc49@psu.e du.\n\nFor more details: https://events.la.psu.edu/event/consortium-work shop-nick-byrd/ X-ALT-DESC;FMTTYPE=text/html:

How Can We Improve Our Decisions? Results From Multiple Methods And Experiments

Nick Byrd, Ph.D.

Assistant Professor of Cognitive Science

Geisinger College of Health Sciences

Department of B ioethics and Decision Sciences

Nobel laureates like Daniel Kahnema n popularized research about cognitive biases. To better understand and ameliorate these reasoning errors, we have been developing more scalable methods to (a) trace reasoning processes and (b) improve faulty reasoni ng. So far, we have run at least a dozen experiments involving thousands of participants. Consider some examples:

Thinking aloud is a comm on critical thinking exercise in education, computer science, and other analytic decision-making contexts. Alas, legacy methods of recording peo ple as they think out loud are time consuming. Also, thinking aloud may use cognitive resources that could otherwise be spent on improving decis ions. To address these issues, I partner with startups to develop web ap ps that remotely (and consensually) record and transcribe people’s reaso ning process (e.g., from the microphone on the participants’ smartphone) , which drastically expedited data collection and transcription — from m onths to hours. Behavioral results have improved our understanding of wh at reflection tests measure and how people overcome faulty intuitions.

Debate is supposed to enhance intelligence analysis, policymaking, and other forms of critical thinking. However, facilitating debates requ ire significant human resources. So, we developed web apps to automatica lly facilitate solitary and discussion-based reflection with varying fin ancial incentives. This allows hundreds of debates to be recorded in par allel from afar, drastically accelerating data collection and transcript ion. Our quantitative decision analyses find that conversation can be be tter than cash in terms of improving decisions.

Our thinking-aloud , writing, and chatting protocols also yielded decision transcripts that contain much more information than standard survey data. Research assis tants, crowd workers, and language models can categorize and quantify as pects of these step-by-step decision records. The resulting ratings allo w us to quantitatively test the assumptions of cognitive tests and isola te which reasoning patterns actually predict better decisions.

We are also testing interventions such as information formatting (e.g., arg ument mapping or data visualization), philosophical reflection (e.g., th ought experiments), testing effects (e.g., having people complete some r easoning test items before the primary test of reasoning), nudges (e.g., text message reminders), and boosts (e.g., educational infographics).

Ultimately, few interventions reliably improve decisions. And some popular interventions seem ineffective in improved research designs (e.g ., with larger samples, better data, better measures, or more controlled variables). This presentation will dive deeper into the methods and res ults.

For Zoom link email Daryl Cameron at cdc49@psu.edu.

Fo r more details: https://events.la.psu.edu/event/consortium-workshop-nic k-byrd/

URL:https://moralconsortium.psu.edu LOCATION:413 Welch Building END:VEVENT END:VCALENDAR