Open and Reliable Language Model Adaptation
— Faeze
In this talk, Faeze explores two crucial frontiers in AI development: democratizing language model adaptation and enhancing their reliability in real-world deployment. She introduc…
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Talks & Events
Weekly talks, hack days, and symposia on responsible AI — open to all.
Past Events
Concrete Problems for Developing Human-Centered Agents
— Gagan
Reflecting on his experience developing AutoGen—an open-source framework for building agents and AutoGen-based applications—this talk outlines three concrete challenges in creating…
AI as Normal Technology
— Guest Speaker
Arvind Narayanan will present a new paper co-authored with Sayash Kapoo, in which they articulate a vision of artificial intelligence as a “normal technology,” standing in contrast…
Culture as a Lens on Responsible AI
— Dr. Prabhakaran
AI technologies are often developed within mono-cultural development contexts, but are meant to interact with multi-cultural usage contexts with divergent values, knowledge systems…
Beyond Scaling: Frontiers of Retrieval-Augmented Language Models
— Guest Speaker
Despite their success, Large Language Models (LLMs) remain limited by issues like hallucination and outdated knowledge. In this talk, Akari introduces Augmented LMs—a new paradigm …
Responsible AI for Enterprise Data Centers: Balancing Technical Excellence and Ethical Standards
— Shilpi
As AI transforms enterprise data center infrastructure, product managers face a critical challenge: driving innovation while upholding ethical standards. This session explores how …
Weak-to-Strong Generalization
— Pavel
As AI systems grow more capable, aligning them becomes increasingly challenging—especially when their behavior outpaces human understanding. This talk explores weak-to-strong gener…
Book Tour: The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want
— Emily
A smart, incisive look at the technologies sold as artificial intelligence, the drawbacks and pitfalls of technology sold under this banner, and why it’s crucial to recognize the m…
Bridging the AI-UX Divide: Responsible AI Design through Human-Centered Collaboration
— Hari
In traditional software development, UX design and engineering are distinct: designers create specs, and engineers build them. AI blurs this line, as systems evolve dynamically wit…
Scale Can’t Overcome Pragmatics: Instilling Spatial and Compositional Reasoning into Multimodal Language Models
— Ranjay
Compositionality is key to human vision and language, allowing us to interpret new scenes and sentences by combining familiar elements. While past research incorporated composition…
Toward Effective Data Governance in Data-Driven Systems
— Asia
Contemporary AI systems are characterized by extensive personal data collection despite the increasing societal costs associated with such practices. To prevent harm, data protecti…
Training Social Skill via Large Language Models
— Dr. Yang
Social skills are key to success in work and life, but finding good practice opportunities isn’t easy. Most training relies on expert supervision, which doesn’t scale well given th…
Human-AI Interaction Under Societal Disagreement
— Michael
How can we better model human attitudes and behaviors? Traditional simulations often fail to capture the complexity of human behavior, but AI opens up new possibilities. In this ta…
“It’s not a representation of me”: Examining Accent Bias and Digital Exclusion in Synthetic AI Voice Services
— Dr. Avijit Ghosh
AI speech generation and voice cloning technologies produce natural speech but may reinforce accent discrimination. A study of two synthetic AI voice services (Speechify and Eleven…
How Microsoft Blends Safety and Security in AI Red Teaming
— Tori
The Microsoft AI Red Team (AIRT)’s principles and methods combine security red teaming practices and adversarial ML techniques, with safety frameworks and perspectives. This talk w…
Generative Agents: Interactive Simulacra of Human Behavior
— Michael
How can we better model human attitudes and behaviors? Traditional simulations often fail to capture the complexity of human behavior, but AI opens up new possibilities. In this ta…
Philosophical Considerations in AI Alignment
— Pawan
The rapid rise of artificial intelligence brings challenges in ensuring it aligns with human values and ethics. This session dives into the philosophical core of AI Alignment—how t…
Long-term Societal Impacts of AI and the Role of Higher Education
— Jared
Jared recently joined UW-IT as the Lead AI Architect, bringing decades of expertise in enterprise-level AI solutions to education. He’ll share his insights on sustainability and en…
AI Ageism: studying age discrimination in the era of algorithms. Reflections and future directions for researching algorithmic inequalities
— Dr. Stypińska
In this talk, Dr. Stypińska will present findings from her AGEAI research on AI ageism, supported by empirical data from Germany, Spain, Great Britain, Poland, and the Netherlands.…
Auditing Automated Speech Recognition Systems for Disparities
— Dr. Allison Koenecke
Automated speech recognition (ASR) systems convert spoken language to text across applications, but Allison’s audit of commercial ASR systems (e.g., OpenAI, Amazon, Apple, Google, …
Illuminating Dark Data: Privacy-Preserving AI in Distributed Data Silos
— Sikha
Data is the lifeblood of AI. However, much of the most valuable data in the nation requires tight access control due to its sensitivity. As a result, AI remains heavily underutiliz…
Towards Bidirectional Human-AI Alignment via Interaction: Human-Centered AI Explanation, Evaluation, and Development
— Dr. Shen
In this talk, Dr. Shen will provide a comprehensive overview of “bidirectional human-AI alignment,” starting with gaps in how humans understand AI decision-making. She will discuss…
Sealed Knowledges: The Impact and Underlying Assumptions of Integrating Direct Answers into Online Search
— Nora
The integration of large language models (LLMs) to provide direct answers to online search queries signals a significant change in online search. Questioning the implications of th…
Operationalizing Responsible Machine Learning: From Equality Towards Equity
— Dr. Wang
With the widespread proliferation of machine learning, there arises both the opportunity for societal benefit as well as the risk of harm. Approaching responsible machine learning …
Open Source Software – Linux Kernel Communities and Lessons for AI development
— Dr. Do Yoon Kim
More broadly, he is interested in how knowledge flows across organizational boundaries, and firm strategies/government policies that can facilitate efficient transfers of knowledge…
The Uneven Impact of Generative AI on Entrepreneurial Performance
— Dr. Rem Koning
Building on this work, he is the co-director and co-founder of the Tech for All lab at The Digital, Data, and Design (D^3) Institute at Harvard, where he leads a group of interdisc…
Time and Value of Data
— Dr. Ehsan Valavi
His research interest is at the interface of digitization, strategy, and operations management. He is currently studying the growth of digital firms and the challenges they face in…
Human Capital Acquisition in Response to Data Breaches
— Dr. Xiupeng Wang
Given the rise in the frequency and cost of data security threats, it is critical to understand whether and how companies strategically adapt their operational workforce in respons…
Context and Participation in Machine Learning
— Guest Speaker
In AI & ML, participatory approaches hold promise to lend agency and decision-making power to marginalized stakeholders. But what does meaningful participation look like in practic…