BEGIN:VCALENDAR PRODID:-//Microsoft Corporation//Outlook 16.0 MIMEDIR//EN VERSION:2.0 METHOD:PUBLISH X-MS-OLK-FORCEINSPECTOROPEN:TRUE BEGIN:VTIMEZONE TZID:Central Standard Time BEGIN:STANDARD DTSTART:16011104T020000 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZOFFSETFROM:-0500 TZOFFSETTO:-0600 END:STANDARD BEGIN:DAYLIGHT DTSTART:16010311T020000 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZOFFSETFROM:-0600 TZOFFSETTO:-0500 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT CLASS:PUBLIC CREATED:20260924T185241Z DESCRIPTION:Speaker:\nKristina Lerman\, Professor of Informatics\, Luddy Sc hool of Informatics\, Computing and Engineering\, Indiana University\n\n\n Title:\nSocial Dynamics of Human-Algorithm Interactions Amplify Social Dys function\n\n\nAbstract: \nSocial media platforms have achieved remarkable success by predicting what users will click\, watch\, share\, and engage w ith. Yet algorithmic feeds have also been implicated in rising polarizatio n\, growing psychological distress\, and the erosion of social trust. How can systems so effective at predicting human behavior produce outcomes poo rly aligned with human welfare? I introduce algorithmic misalignment as a framework for understanding this puzzle. Recommendation algorithms are opt imized to predict observable behavior\, but behavioral signals are imperfe ct proxies for what people actually want or value. Moreover\, optimization favors behaviors that are easiest to predict—often fast\, reactive\, an d emotionally driven responses. Feedback loops reinforce these tendencies as algorithmic recommendations shape behavior that subsequently becomes al gorithmic training data\, allowing subtle human biases to scale into colle ctive outcomes. I illustrate this framework through two case studies. In p olitical discourse\, algorithms amplify anger\, outrage\, and out-group ho stility\, contributing to affective polarization. Interactions between gro ups then transform animosity into durable partisan disagreements. In menta l health\, algorithmic feeds amplify social comparison\, envy\, and status anxiety\, with consequences for body image and eating disorders. Although typically studied separately\, these outcomes may share a common structur al origin in the interaction between human psychology and algorithmic opti mization\, suggesting new directions for designing healthier human–algor ithm ecosystems.\n\n\nSpeaker Bio:\nKristina Lerman is a Professor of Informatics at Indiana Uni versity’s Luddy School of Informatics\, Computing and Engineering. Trai ned as a physicist\, she uses AI\, machine learning and network science to answer questions in computational social science\, including how algorith ms and online platforms shape social behavior and human psychology\, acces s to information\, attention\, and social-emotional support. Her work has been covered by the Washington Post\, Wall Street Journal\, and The Atlant ic. She is a fellow of AAAI.\n\nLocation:\nIn person: Chambers Hall\, 600 Foster Street\, Lower Level\nRemote option: https://northwestern.zoom.us/ j/93389536671 \nPasscode: NICO26\n\n\nAbout the Speaker Series:\nW ednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems\, networks\, and artificial intelligence. It bri ngs together attendees ranging from graduate students to senior faculty wh o span all of the schools across Northwestern\, from applied math to socio logy to biology and every discipline in-between. Please visit: https://bit .ly/WedatNICO for information on future speakers.\n \n DTEND;TZID="Central Standard Time":20261007T130000 DTSTAMP:20260924T185241Z DTSTART;TZID="Central Standard Time":20261007T120000 LAST-MODIFIED:20260924T185241Z LOCATION:Chambers Hall (600 Foster St\, Evanston\, IL 60201) PRIORITY:5 RECURRENCE-ID;TZID="Central Standard Time":20261007T120000 SEQUENCE:0 SUMMARY;LANGUAGE=en-us:Wed@NICO: Kristina Lerman\, Indiana University TRANSP:OPAQUE UID:040000008200E00074C5B7101A82E00800000000A06CD56D854BDD01000000000000000 010000000FD502B7634EB0B4F84204E9F72ECF6B8 X-ALT-DESC;FMTTYPE=text/html:
< p class=MsoNormal>Speaker:

Kristin a Lerman\, Professor of Informatics\, Luddy School of Informatics\, Comput ing and Engineering\, Indiana University

Title:

Social Dynamics of Human-Algorithm I nteractions Amplify Social Dysfunction

Abstract : \;

Social media platforms have achieved remarkable success by predicting what users will click\, watch\, share\, and engage with. Yet algorithmic feeds have also been implicated i n rising polarization\, growing psychological distress\, and the erosion o f social trust. How can systems so effective at predicting human behavior produce outcomes poorly aligned with human welfare? I introduce algorithmi c misalignment as a framework for understanding this puzzle. Recommendatio n algorithms are optimized to predict observable behavior\, but behavioral signals are imperfect proxies for what people actually want or value. Moreover\, optimization favors behaviors that are ea siest to predict—\;often fast\, reactive\, and emotionally driven res ponses. Feedback loops reinforce these tendencies as algorithmic recommend ations shape behavior that subsequently becomes algorithmic training data\ , allowing subtle human biases to scale into collective outcomes. I illust rate this framework through two case studies. In political discourse\, alg orithms amplify anger\, outrage\, and out-group hostility\, contributing t o affective polarization. Interactions between groups then transform animo sity into durable partisan disagreements. In mental health\, algorithmic f eeds amplify social comparison\, envy\, and status anxiety\, with conseque nces for body image and eating disorders. Although typically studied separ ately\, these outcomes may share a common structural origin in the interac tion between human psychology and algorithmic optimization\, suggesting ne w directions for designing healthier human–\;algorithm ecosystems.

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Speaker Bio:

Kristina Lerma n is a Professor of Informatics at Indiana University’\;s Luddy S chool of Informatics\, Computing and Engineering.  \;Trained as a phys icist\, she uses AI\, machine learning and networ k science to answer questions in computational social science\, including how algorithms and online platforms shape social behavior and human psycho logy\, access to information\, attention\, and social-emotional support. H er work has been covered by the Washington Post\, Wall Street Journal\, an d The Atlantic. She is a fellow of AAAI.


Location:

In person: Chambers Hall\, 600 Foster Street\, Lower Level
Remote option: \; https://northwestern.zoom.us/j /93389536671
Passcode: NICO26

About the Speaker Series:

We dnesdays@NICO is a vibrant weekly seminar series focusing broadly o n the topics of complex systems\, networks\, and artificial intelligence. It brings together attendees ranging from graduate students to senior facu lty who span all of the schools across Northweste rn\, from applied math to sociology to biology and every discipline in-bet ween. Please visit: https://bit.ly/Weda tNICO for information on future speakers.

 \;

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