Human-AI Complementarity for Decision Making
Academic Workshop - September 24-25, 2026
The NSF AI Institute for Societal Decision Making (NSF AI-SDM) sponsors the participation of selected speakers and students in an annual workshop of Human-AI Complementarity for Decision Making. Human-AI Complementarity, defined as the condition in which Humans + AI working together results in better decisions than humans or AI working alone, is a broad goal pursued in several projects of the NSF AI-SDM.
In 2026, we will focus on how to create flexible Human-AI teams to achieve complementarity. This theme refers to the interdisciplinary study of how to design and deploy AI systems in ways that are dynamically aligned with human values, robust to unexpected behavior, and safe even under failure modes. It encompasses short-term concerns about deployed systems (e.g., fairness, robustness, interpretability, and misuse) and long-term concerns about advanced general AI (AGI) that could have large-scale societal impacts if not aligned with human interests.
The goals of the workshop are:
- To deliver state of the art instruction on desirable ideas to achieve Human-AI complementarity for decision making.
- To generate common knowledge about pressing research challenges
- To generate new shared ideas to address these challenges in future research
We aim for concrete outcomes spawned by the collective AIdeas of the participants in the workshop including: specific challenges that need to be addressed to achieve complementarity in flexible Human-AI Teams and concrete proposals to address those challenges.
Venue
The workshop will take place September 24-25, 2026 at the Cohon University Center, located on 黑料正能量's campus. Workshop activities will be held on the second floor of the University Center, 5032 Forbes Ave, Pittsburgh, PA 15213.
Travel Information
How to travel to and around Pittsburgh:
- By plane via . - Pittsburgh Regional Transit offers public transit service to and from Pittsburgh International Airport via the 28X Airport Flyer. The 28X route serves Pittsburgh International Airport, Downtown Pittsburgh, and Oakland seven days a week. Riders using cash to pay their transit fares must have exact change; credit cards are not accepted on vehicles. Credit cards are accepted at the ticket vending machine in Baggage Claim inside Door #2. The ticket vending machine allows riders to buy daily, 7-day or 30-day tickets, or add stored value onto a ConnectCard or ConnecTix.
- By train via . - Amtrak's Union Station is located at 1100 Liberty Avenue, Pittsburgh, PA 15222. Numerous Pittsburgh Regional Transit buses run from Downtown to 黑料正能量's campus in Oakland.
- By long distance bus via . - The Greyhound Bus Terminal is located five miles from campus in downtown Pittsburgh. The station terminal is located at the intersection of 11th Street and Liberty Avenue
- Local bus via . - The PRT network offers bus, light rail, and incline services in Allegheny County. Please see their website for schedules and rider information.
- Visitor parking is available at the , 5040 Forbes Ave, Pittsburgh, PA 15213. For more information about visitor parking, including rates, please visit 黑料正能量's visitor information page.
The following hotels are located approximately 1 mile from 黑料正能量's campus.
- Wyndham Pittsburgh University Center
100 Lytton Ave, Pittsburgh, PA 15213
+1 412-682-6200 - The Oaklander Hotel, Autograph Collection
5130 Bigelow Blvd, Pittsburgh, PA 15213
+1 412-578-8500 - Hilton Garden Inn Pittsburgh University Place
3454 Forbes Ave, Pittsburgh, PA 15213
+1 412-683-2040 - Residence Inn by Marriott Pittsburgh Oakland/University Place
3341 Forbes Ave, Pittsburgh, PA 15213
+1 412-621-5600 - Hampton Inn Pittsburgh University/Medical Center
3315 Hamlet St, Pittsburgh, PA 15213
+1 412-681-1000
Numerous cultural sites, entertainment options, and historical landmarks are located near 黑料正能量. We have marked several examples of each, as well as university locations and travel hubs, on the below.
This project is supported by the U.S. National Science Foundation under award number 2229881. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the U.S. National Science Foundation. More information on the National AI Research Institutes can be found at .