Who Predicts Better and Why? Humans, AI, and the Anatomy of a Forecast
Summary
AI models process vast signals; humans bring judgment and context. But who calls real-world outcomes better, and when? This session compares human and model forecasts on headline events, drawing on newsroom practice, product experience, and reasoning-centric AI research. We’ll map where models’ pattern breadth wins, where human context does, and why hybrids often work best. Instead of scoreboards alone, we’ll discuss how journalists and analysts should use uncertainty ranges, disclose methods and sources, and avoid feedback loops that can steer the story itself.
- Format: Panel
- Category: Panel
- Event Type: panel
- Presented By: ForeNex
Contributors
- Eva Vivalt
- Charlie Fink
- Parisa Kordjamshidi
- David Weeks
Raw Event JSON
Large nested arrays are compacted for page readability. Full payload remains in dataset files.
Open JSON payload
{
"id": "PP1162835",
"track": "Tech & AI",
"focus_area": null,
"category": "Panel",
"event_id": "PP1162835",
"event_type": "panel",
"format": "Panel",
"genre": null,
"subgenre": null,
"name": "Who Predicts Better and Why? Humans, AI, and the Anatomy of a Forecast",
"presented_by": "ForeNex",
"publish_at": "2025-12-11T10:41:00.000-06:00",
"reservable": true,
"reservable_id": "PP1162835",
"reserved": false,
"date": "2026-03-16",
"end_time": "2026-03-16T11:00:00.000-05:00",
"start_time": "2026-03-16T10:00:00.000-05:00",
"message": null,
"image": null,
"credentials": [
{
"name": "Platinum Badge",
"type": "platinum"
},
{
"name": "Innovation Badge",
"type": "innovation"
}
],
"contributors": [
{
"id": 82446,
"company": "University of Toronto",
"credential_types": [
"innovation"
],
"entity_id": 2244127,
"name": "Eva Vivalt",
"speaker_types": [],
"title": "Professor",
"image": {
"alt_text": "Eva Vivalt",
"credit": "",
"url": "https://images.sxsw.com/AcclgzoJykrnQn6fl2oxV16BeOY=/71x0:494x423/600x600/images.sxsw.com/48/557e3b49-5cc9-4299-acb7-9d5a7c26aa98/pcid-1632435"
},
"speaker_type": "Speaker",
"details": "Eva Vivalt is an Assistant Professor of Economics at the University of Toronto whose research examines why evidence does - or does not - inform public policy, with particular attention to uncertainty, behavioral biases, and forecasting. This work includes meta-research and research on AI-based forecasting, with a focus on improving decision-making in science and policy. Vivalt is a principal investigator on multiple randomized controlled trials of guaranteed income and a co-founder of the Social Science Prediction Platform, which coordinates and evaluates forecasts of research results. Across this research agenda, Vivalt’s work has been supported by major public and philanthropic funders, including the NIH, NSF, and the Alfred P. Sloan Foundation. After completing a PhD in Economics at the University of California, Berkeley, and postdoctoral work at New York University, Vivalt held roles at the World Bank and the Australian National University before joining the University of Toronto.",
"links": {},
"type": "person"
},
{
"id": 17888,
"company": "Forbes",
"credential_types": [
"innovation"
],
"entity_id": 2005201,
"name": "Charlie Fink",
"speaker_types": [],
"title": "Consultant, Columnist, & Author",
"image": {
"alt_text": "Charlie Fink",
"credit": null,
"url": "https://images.sxsw.com/IQEZ3NSz_8tLHPyOu4LPfbjqv98=/336x91:1598x1353/600x600/images.sxsw.com/48/ed6a6720-fb3d-4795-87ed-a74b906947a8/pcid-860903"
},
"speaker_type": "Speaker",
"details": "Charlie Fink covers AI and XR for Forbes and co-hosts The AI/XR Podcast. He is the author of the critically acclaimed AR-enabled books Charlie Fink’s Metaverse (2017) and Convergence: How the World Will Be Painted With Data (2019). Fink teaches at Chapman University in Orange, CA, and at Arizona State University’s LA graduate program in Emerging Media. In 2024, he co-founded ANIM8 AI Studio with Lion King director Rob Minkoff.\rFink's forty-year career at the intersection of storytelling and technology began at Walt Disney Feature Animation in 1986, where he famously conceived the idea for The Lion King and subsequently became the studio’s youngest creative vice president.\rFink's work in immersive media began in 1992 as COO of Virtual World Entertainment, a groundbreaking location-based VR company founded by Tim Disney and Jordan Weisman. In 1995, AOL recruited him as Senior Vice President and Chief Creative Officer of AOL Studios. After selling his subsequent venture-backed startup, eAgents, to American Greetings Interactive, Fink spent a decade as Producer and Chairman of the New York Musical Festival, which nurtured Broadway hits \"Title of Show,\" \"Next to Normal,\" and \"Guttenberg!\"\rFink’s career as a tech writer began in 2016, where his blog post about VR and AR attracted the attention of a Forbes editor. Since then, he has written over 1,000 stories, moderated dozens of panels, delivered keynotes and book talks all over the world.\r\r",
"links": {},
"type": "person"
},
{
"id": 80898,
"company": "Michigan State Univeristy",
"credential_types": [
"innovation"
],
"entity_id": 2242488,
"name": "Parisa Kordjamshidi",
"speaker_types": [],
"title": "Associate Professor Computer Science",
"image": {
"alt_text": "Paris Kordjamshidi",
"credit": "",
"url": "https://images.sxsw.com/JrypKPY0Y2oSvPvAx9ZE3oo1aso=/0x6:796x802/600x600/images.sxsw.com/48/f3750dbb-c439-433a-a154-e4e7492d5eeb/pcid-1631252"
},
"speaker_type": "Speaker",
"details": "Parisa Kordjamshidi is an Associate Professor of Computer Science and\rEngineering at Michigan State University. Her research is on AI focusing on Spatial Intelligence, Multimodal reasoning with large vision and language models, and Neuro-symbolic learning. She received her Ph.D. from KU Leuven and conducted postdoctoral research at the University of Illinois Urbana-Champaign. She is a recipient of the NSF CAREER, Amazon Faculty Research, and Fulbright Scholar Awards, and her research team received the multiple Research Paper\rAwards at Major NLP conferences. Dr. Kordjamshidi serves as Associate Editor of Journal of AI Research (JAIR), Co-editor in chief of ACL rolling review (ARR 2026), Action Editor for TACL and has held roles in organization committee of major conferences in AI, Machine learning and Natural Language Processing conferences. Recently, she has been a visiting Associate Professor at UCLA and currently is a visiting professor at Bloomberg for her sabbatical.",
"links": {},
"type": "person"
},
{
"id": 79708,
"company": "Sunrise International",
"credential_types": [
"innovation"
],
"entity_id": 2240900,
"name": "David Weeks",
"speaker_types": [],
"title": "Co-Founder & COO",
"image": {
"alt_text": "David Weeks",
"credit": null,
"url": "https://images.sxsw.com/Br8YAwmXEtNziqiIbxxv76oSICc=/600x600/images.sxsw.com/48/f5a5d52e-3e68-ad16-6c13-a5459050bff4/pcid-1628705"
},
"speaker_type": "Speaker",
"details": "David Weeks is the Co-Founder and COO of Sunrise International. Over the past 14 years, David has led cross-border marketing and consulting projects in China and the broader APAC region for more than 250 clients in XR, higher education, and education technology. He has supported global product launches for multiple AI companies in East Asia, and he has steered the delivery of generative AI-based avatars for admissions offices, NGOs, overseas government agencies, and edtech firms. He also serves as the Content Director of AWE Asia, the region’s leading XR conference. A former national debate champion, he also co-founded the National High School Debate League of China in 2012. He is fluent in Mandarin and holds a BA in Asian Studies and Political Science from Swarthmore College.",
"links": {},
"type": "person"
}
],
"venue": {
"accessible": false,
"age_policy": null,
"floor": "3",
"id": "V0455",
"indoor_outdoor": "INDOOR",
"name": "Salon E",
"parent_id": "V0403",
"parent_venue_name": "JW Marriott",
"venue_entry_info": null,
"formats": null,
"location": {
"address": "110 E 2nd St.",
"lat_lon": [
30.2645713,
-97.743198
],
"city": "Austin",
"postal_code": "78701",
"state": "TX",
"name": "JW Marriott"
},
"root": {
"accessible": null,
"age_policy": null,
"floor": null,
"id": "V0403",
"indoor_outdoor": null,
"name": "JW Marriott",
"parent_id": null,
"parent_venue_name": null,
"venue_entry_info": null,
"formats": null
},
"events": "[omitted 5 venue events]"
},
"description": "AI models process vast signals; humans bring judgment and context. But who calls real-world outcomes better, and when? This session compares human and model forecasts on headline events, drawing on newsroom practice, product experience, and reasoning-centric AI research. We’ll map where models’ pattern breadth wins, where human context does, and why hybrids often work best. Instead of scoreboards alone, we’ll discuss how journalists and analysts should use uncertainty ranges, disclose methods and sources, and avoid feedback loops that can steer the story itself.",
"experience_level": "Beginner",
"accessibility": [],
"accessible_venue": false,
"add_bcl_url": false,
"add_slido": false,
"age_policy": null,
"american_sign_language": false,
"apple_url": null,
"audio_description": false,
"caption_url": null,
"closed_captioned": false,
"cpe_credit": false,
"has_subtitles": false,
"hash_tags": [],
"high_sensory_experience": false,
"live": false,
"long_description": "AI models process vast signals; humans bring judgment and context. But who calls real-world outcomes better, and when? This session compares human and model forecasts on headline events, drawing on newsroom practice, product experience, and reasoning-centric AI research. We’ll map where models’ pattern breadth wins, where human context does, and why hybrids often work best. Instead of scoreboards alone, we’ll discuss how journalists and analysts should use uncertainty ranges, disclose methods and sources, and avoid feedback loops that can steer the story itself.",
"meeting_url": null,
"meeting_url_live": false,
"mentorly_url": null,
"mobile_audio_url": null,
"open_captioned": false,
"playlist_tag": null,
"rebroadcast": false,
"recommended_ids": [],
"search_conversions": null,
"short_program": false,
"slido_url": null,
"sort": "WHO PREDICTS BETTER AND WHY? HUMANS, AI, AND THE ANATOMY OF A FORECAST",
"source": "Official",
"squad_up_url": null,
"stream_embed": null,
"stream_id": null,
"stream_url": null,
"strobe_warning": false,
"subdiscipline": null,
"summit": null,
"summit_display_name": null,
"tags": [
{
"id": 2014,
"name": "Journalism",
"created_at": "2018-02-02T16:00:42.138-06:00",
"updated_at": "2022-02-14T12:08:03.509-06:00",
"sort": "JOURNALISM",
"alpha": "J"
},
{
"id": 979,
"name": "Data",
"created_at": "2016-11-09T14:50:36.874-06:00",
"updated_at": "2026-02-08T12:40:06.216-06:00",
"sort": "DATA",
"alpha": "D"
},
{
"id": 2114,
"name": "AI",
"created_at": "2020-01-17T14:51:44.091-06:00",
"updated_at": "2026-02-17T20:42:14.828-06:00",
"sort": "AI",
"alpha": "A"
}
],
"talent_attending": null,
"title_only": false,
"track_display_name": "Tech & AI",
"trailer_id": null,
"trailer_url": null,
"video_on_demand": null,
"vimeo_id": null,
"vod": false,
"xr_project_type": null,
"youtube_id": null,
"related_sales_client": null
}