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2023
Article

M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models

By: Himabindu Lakkaraju, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai and Haoyi Xiong

While Explainable Artificial Intelligence (XAI) techniques have been widely studied to explain predictions made by deep neural networks, the way to evaluate the faithfulness of explanation results remains challenging, due to the heterogeneity of explanations for... View Details

Keywords: AI and Machine Learning

2023
Working Paper

Auditing Predictive Models for Intersectional Biases

By: Kate S. Boxer, Edward McFowland III and Daniel B. Neill

Predictive models that satisfy group fairness criteria in aggregate for members of a protected class, but do not guarantee subgroup fairness, could produce biased predictions for individuals at the intersection of two or more protected classes. To address this risk, we... View Details

Keywords: Predictive Models; Bias; AI and Machine Learning

March 2017
Supplement

Donna Dubinsky, Numenta and Artificial Intelligence

By: David B. Yoffie

Donna Dubinsky, CEO of Numenta, discusses her views of the future of artificial intelligence and the strategic challenges of building a new platform. View Details

Keywords: Artificial Intelligence; Strategy; Technological Change; AI and Machine Learning; Technology Industry

2024
Conference Paper

Quantifying Uncertainty in Natural Language Explanations of Large Language Models

By: Himabindu Lakkaraju, Sree Harsha Tanneru and Chirag Agarwal

Large Language Models (LLMs) are increasingly used as powerful tools for several high-stakes natural language processing (NLP) applications. Recent prompting works claim to elicit intermediate reasoning steps and key tokens that serve as proxy explanations for LLM... View Details

Keywords: Large Language Model; AI and Machine Learning

2022
Article

Efficiently Training Low-Curvature Neural Networks

By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret

Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Common methods to address these downstream issues, such as adversarial training, are expensive and often... View Details

Keywords: AI and Machine Learning

Web

Data Tips & Toolkits - Research Computing Services

supervised machine learning problems: it provides a uniform interface to a ton of machine learning algorithms. If... View Details

December 18, 2024
Article

Is AI the Right Tool to Solve That Problem?

By: Paolo Cervini, Chiara Farronato, Pushmeet Kohli and Marshall W Van Alstyne

While AI has the potential to solve major problems, organizations embarking on such journeys of often encounter obstacles. They include a dearth of high-quality data; too many possible solutions; the lack of a clear, measurable objective; and difficulty in identifying... View Details

Keywords: Artificial Intelligence; AI and Machine Learning; Problems and Challenges

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March 2024
Exercise

'Storrowed': A Generative AI Exercise

By: Mitchell Weiss

"Storrowed" is an exercise to help participants raise their capacity and curiosity for generative AI. It focuses on generative AI for problem understanding and ideation, but can be adapted for use more broadly. Participants use generative AI tools to understand a... View Details

Keywords: AI and Machine Learning; Problems and Challenges

Winter 2021
Editorial

Introduction

By: Michael A. Wheeler

This issue of Negotiation Journal is dedicated to the theme of artificial intelligence, technology, and negotiation. It arose from a Program on Negotiation (PON) working conference on that important topic held virtually on May 17–18. The conference was not the... View Details

Keywords: Artificial Intelligence; Information Technology; Negotiation; AI and Machine Learning

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April 2023
Article

On the Privacy Risks of Algorithmic Recourse

By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel

As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected... View Details

Keywords: Recourse; Privacy Threats; AI and Machine Learning; Information

May 2021
Supplement

Distinct Software Dataset

By: Das Narayandas

Keywords: Artificial Intelligence; Marketing; AI and Machine Learning

February 2024
Technical Note

AI Product Development Lifecycle

By: Michael Parzen, Jessie Li and Marily Nika

In this article, we will discuss the concept of AI Products, how they are changing our daily lives, how the field of AI & Product Management is evolving, and the AI Product Development Lifecycle. View Details

Keywords: Artificial Intelligence; Product Management; Product Life Cycle; Technology; AI and Machine Learning; Product Development

September 23, 2024
Article

AI Wants to Make You Less Lonely. Does It Work?

By: Julian De Freitas

Keywords: AI and Machine Learning; Well-being

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2023
Working Paper

Distributionally Robust Causal Inference with Observational Data

By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li

We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details

Keywords: AI and Machine Learning; Mathematical Methods

2023
Article

Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset

By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li

Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details

Keywords: Large Language Model; AI and Machine Learning; Analytics and Data Science; Health Industry

2022
Working Paper

The Evolution of ESG Reports and the Role of Voluntary Standards

By: Ethan Rouen, Kunal Sachdeva and Aaron Yoon

We examine the evolution of ESG reports of S&P 500 firms from 2010 to 2021. The percentage of firms releasing these voluntary disclosures increased from 35% to 86% during this period, although the length of these documents experienced more modest growth. Using a... View Details

Keywords: Voluntary Disclosure; Textual Analysis; Modeling And Analysis; Corporate Social Responsibility and Impact; AI and Machine Learning; Accounting

August 25, 2022
Article

Find the Right Pace for Your AI Rollout

By: Rebecca Karp and Aticus Peterson

Implementing AI can introduce disruptive change and disfranchise staff and employees. When members are reluctant to adopt a new technology, they might hesitate to use it, push back against its deployment, or use it in limited capacity — which affects the benefits an... View Details

Keywords: AI and Machine Learning; Technology Adoption; Change Management

Article

Fake AI People Won't Fix Online Dating

By: Scott Duke Kominers

Computer-generated images may inspire even more distrust and surely won’t lead to the love of a lifetime. View Details

Keywords: Artificial Intelligence; Dating Services; Internet and the Web; Ethics; AI and Machine Learning

02 Oct 2018
First Look

New Research and Ideas, October 2, 2018

policies. Download working paper: https://www.hbs.edu/faculty/Pages/item.aspx?num=55050 "Developing Theory Using Machine Learning Methods By: Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres... View Details

Keywords: Dina Gerdeman

June 2024
Teaching Note

Numenta in 2020: The Future of AI

By: David B. Yoffie

In 2020, Numenta’s co-founder, Jeff Hawkins, completed his pathbreaking research on artificial intelligence. His co-founder and CEO, Donna Dubinsky, had to find a business model to monetize the technology. This teaching note explores the challenges of building a... View Details

Keywords: Artificial Intelligence; Monetization; Strategy; Intellectual Property; AI and Machine Learning; Business Model; Entrepreneurship; Technology Industry

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