Publications

01 Nov 1999
Research & Ideas

John H. Patterson and the Sales Strategy of the National Cash Register Company, 1884 to 1922

objection, he acknowledged the legitimacy of the complaint, and then tried to counter. My method of taking orders, I presume, does not vary much from that of other managers. If the party calling is a... View Details

Keywords: by Walter A. Friedman

Teaching Interest

Data Science for Managers

Served as a teaching fellow; assisted MBA students with classroom coding exercises.
Developed course materials, including new case studies, technical notes, and code notebooks students used to analzye case data.
Developed interactive web... View Details

Teaching Interest

Applied Business Analytics

Course Overview:

Business Analytics has become a core function in many firms today and is driving innovation in the form of new business and operating models. Data-driven decision-making requires understanding of statistics, computer... View Details

06 Feb 2018
First Look

First Look at New Research and Ideas: February 6, 2018

and Machine Learning By: Choudhury, Prithwiraj, Evan Starr, and Rajshree Agarwal Abstract—The advent of artificial intelligence in the form of... View Details

2023
Working Paper

In-Context Unlearning: Language Models as Few Shot Unlearners

By: Martin Pawelczyk, Seth Neel and Himabindu Lakkaraju

Machine unlearning, the study of efficiently removing the impact of specific training points on the trained model, has garnered increased attention of late, driven by the need to comply with privacy regulations like the Right to be Forgotten. Although unlearning is... View Details

Keywords: AI and Machine Learning; Copyright; Information

February 2021
Tutorial

What is AI?

By: Tsedal Neeley

This video explores the elements that constitute artificial intelligence (AI). From its mathematical basis to current advances in AI, this video introduces students to data, tools, and statistical models that make a computer 'intelligent.' Through an explanation of... View Details

Keywords: Artificial Intelligence; Digital; Technological Innovation; Leadership; AI and Machine Learning; Mathematical Methods

2024
Working Paper

Using LLMs for Market Research

By: James Brand, Ayelet Israeli and Donald Ngwe

Large language models (LLMs) have rapidly gained popularity as labor-augmenting tools for programming, writing, and many other processes that benefit from quick text generation. In this paper we explore the uses and benefits of LLMs for researchers and practitioners... View Details

Keywords: Large Language Model; Research; AI and Machine Learning; Analysis; Customers; Consumer Behavior; Technology Industry; Information Technology Industry

SSRN

Article

Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

By: Eva Ascarza and Ayelet Israeli

An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details

Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods

2023
Article

Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators

By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill

Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details

Keywords: Regression Discontinuity Design; Analytics and Data Science; AI and Machine Learning

Forthcoming
Book

The Experimentation Machine: Finding Product–Market Fit in the Age of AI

By: Jeffrey J. Bussgang

Leverage AI to be a 10x Founder

Today’s most successful founders know that the startups that learn the fastest will win. In The Experimentation Machine, I reveal how AI is transforming the way startups find product-market fit and scale.... View Details

Keywords: AI; Founder; Startup; AI and Machine Learning; Technology Adoption; Business Startups; Entrepreneurship; Market Entry and Exit

22 Aug 2005
Research & Ideas

The Hard Work of Failure Analysis

outside facilitators, can help keep the process productive. Next, skills for managing a group process of analyzing a failure with a spirit of inquiry and sufficient understanding of the scientific method are... View Details

Keywords: by Amy Edmondson & Mark D. Cannon

Research Summary

Overview

Over the last decade, technology companies like Amazon, Google, and Netflix have pioneered data-driven research and development processes centered on massive experimentation. However, as companies increase the breadth and scale of their experiments to millions of... View Details

Research Summary

Overview

By: Iavor I. Bojinov

Over the last decade, technology companies like Amazon, Google, and Netflix have pioneered data-driven research and development processes centered on massive experimentation. However, as companies increase the breadth and scale of their experiments to millions of... View Details

2023
Working Paper

An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits

By: Biyonka Liang and Iavor I. Bojinov

Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details

Keywords: Analytics and Data Science; AI and Machine Learning; Mathematical Methods

2023
Article

Post Hoc Explanations of Language Models Can Improve Language Models

By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju

Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance... View Details

Keywords: AI and Machine Learning; Performance Effectiveness

January 2017 (Revised March 2017)
Case

IBM Transforming, 2012–2016: Ginni Rometty Steers Watson

By: Rosabeth Moss Kanter and Jonathan Cohen

To transform IBM for the next technology wave, Ginni Rometty, who became CEO in 2012, led divestment of declining businesses, made acquisitions in digital innovation and cloud computing, formed partnerships with former competitors such as Apple and tech startups, and... View Details

Keywords: Digital; Technological Change; Artificial Intelligence; Data; IBM; Watson; Internet Of Things; Innovation and Invention; Management; Sales; Information Technology; Technological Innovation; Transformation; AI and Machine Learning

Educators

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

September 2011 (Revised July 2012)
Case

Building Watson: Not So Elementary, My Dear!

By: Willy Shih

This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the... View Details

Keywords: Technological Innovation; Standards; Product Development; Organizational Change and Adaptation; Mathematical Methods; Research and Development; Information Technology

Educators

2023
Working Paper

Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness

By: Neil Menghani, Edward McFowland III and Daniel B. Neill

In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details

Keywords: AI and Machine Learning; Forecasting and Prediction; Prejudice and Bias