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- All HBS Web (96)
- Faculty Publications (12)
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- All HBS Web (96)
- Faculty Publications (12)
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- 06 Jun 2017
- First Look
First Look at New Research and Ideas: June 6, 2017
Quarterly Do Experts or Collective Intelligence Write with More Bias? Evidence from Encyclopædia Britannica and Wikipedia By: Greenstein, Shane, and Feng Zhu Abstract—Organizations today can use both crowds and experts to produce knowledge. While prior work compares...
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Sean Silverthorne
- 08 May 2018
- First Look
First Look at New Research and Ideas, May 8, 2018
Abstract—Many production processes are subject to inspection to ensure they meet quality, safety, and environmental standards imposed by companies and regulators. Inspection accuracy is critical to inspections being a useful input to...
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Sean Silverthorne
- 2024
- Working Paper
Mammography - Early Detection, Precise Diagnoses: Case Histories of Transformational Advances
By: Amar Bhidé, Srikant M. Datar and Katherine Stebbins
This case history describes how the development of x-ray-based techniques and equipment (“mammography”) led to widespread screening for breast cancer and enabled “minimally invasive” biopsies of breast tumors. Specifically, we chronicle how: 1) new protocols and...
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Keywords:
Health Care and Treatment;
Technological Innovation;
Innovation Strategy;
Technology Adoption;
Collaborative Innovation and Invention;
Innovation and Invention;
Governing Rules, Regulations, and Reforms
Bhidé, Amar, Srikant M. Datar, and Katherine Stebbins. "Mammography - Early Detection, Precise Diagnoses: Case Histories of Transformational Advances." Harvard Business School Working Paper, No. 20-002, July 2019. (Revised May 2024.)
- Research Summary
Sell-Side Analysts and Corporate Spinoffs
This study investigates the information content and accuracy of analyst reports written about companies that are about to undertake equity spinoffs. This research is among the first to provide a detailed look at the extent to which analysts evaluate upcoming...
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- Article
Oracle Efficient Private Non-Convex Optimization
By: Seth Neel, Aaron Leon Roth, Giuseppe Vietri and Zhiwei Steven Wu
One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and then exactly solves it....
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Neel, Seth, Aaron Leon Roth, Giuseppe Vietri, and Zhiwei Steven Wu. "Oracle Efficient Private Non-Convex Optimization." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020).
- September 2014
- Article
Advancing Consumer Neuroscience
By: Ale Smidts, Ming Hsu, Alan G. Sanfey, Maarten A. S. Boksem, Richard B. Ebstein, Scott A. Huettel, Joe W. Kable, Uma R. Karmarkar, Shinobu Kitayama, Brian Knutson, Israel Liberzon, Terry Lohrenz, Mirre Stallen and Carolyn Yoon
In the first decade of consumer neuroscience, strong progress has been made in understanding how neuroscience can inform consumer decision making. Here, we sketch the development of this discipline and compare it to that of the adjacent field of neuroeconomics. We...
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Keywords:
Consumer Neuroscience;
Neuroeconomics;
Social Neuroscience;
Genes;
Machine Learning;
Meta-analysis;
Consumer Behavior;
Decision Making;
Science
Smidts, Ale, Ming Hsu, Alan G. Sanfey, Maarten A. S. Boksem, Richard B. Ebstein, Scott A. Huettel, Joe W. Kable, Uma R. Karmarkar, Shinobu Kitayama, Brian Knutson, Israel Liberzon, Terry Lohrenz, Mirre Stallen, and Carolyn Yoon. "Advancing Consumer Neuroscience." Marketing Letters 25, no. 3 (September 2014): 257–267.
- 2011
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and...
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- 2015
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and...
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Speakman, Skyler, Edward McFowland III, and Daniel B. Neill. "Scalable Detection of Anomalous Patterns With Connectivity Constraints." Journal of Computational and Graphical Statistics 24, no. 4 (2015): 1014–1033.
- 2014
- Article
The Promise of Prediction Contests
By: Phillip E. Pfeifer, Yael Grushka-Cockayne and Kenneth C. Lichtendahl
This article examines the prediction contest as a vehicle for aggregating the opinions of a crowd of experts. After proposing a general definition distinguishing prediction contests from other mechanisms for harnessing the wisdom of crowds, we focus on...
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Pfeifer, Phillip E., Yael Grushka-Cockayne, and Kenneth C. Lichtendahl. "The Promise of Prediction Contests." American Statistician 68, no. 4 (2014): 264–270.
- Article
The Similarity Heuristic
By: Daniel Read and Yael Grushka-Cockayne
Decision makers often make snap judgments using fast‐and‐frugal decision rules called cognitive heuristics. Research into cognitive heuristics has been divided into two camps. One camp has emphasized the limitations and biases produced by the heuristics; another has...
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Read, Daniel, and Yael Grushka-Cockayne. "The Similarity Heuristic." Journal of Behavioral Decision Making 24, no. 1 (January 2011): 23–46.
- January 2008 (Revised July 2009)
- Case
Forecasting the Great Depression
What is proper role of professional economic forecasting in financial decision making? The case presents excerpts from three leading economic forecasters on the eve of, and just after, the stock market crash of October 1929. The first set of excerpts is from Roger...
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Keywords:
History;
Mathematical Methods;
Personal Development and Career;
Forecasting and Prediction;
Financial Crisis
Friedman, Walter A. "Forecasting the Great Depression." Harvard Business School Case 708-046, January 2008. (Revised July 2009.)
- 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,...
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Keywords:
Large Language Model;
AI and Machine Learning;
Analytics and Data Science;
Health Industry
Liu, Junling, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, and Michael Lingzhi Li. "Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
- 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...
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Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 21 Aug 2018
- First Look
New Research and Ideas, August 21, 2018
accuracy of daily sales forecasts. We collaborated with an online apparel retailer to assemble a dataset that combines (1) detailed internal operational information, including data on sales, advertising, and promotions, as well as (2)...
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Dina Gerdeman
- 05 Dec 2023
- Research & Ideas
Lessons in Decision-Making: Confident People Aren't Always Correct (Except When They Are)
University of California, Santa Barbara. How does one measure confidence? In the first phase of the study, the team invited more than 2,000 people to perform 15 classic cognitive bias tasks, including: The “knapsack problem”—a strategic...
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by Kara Baskin
- 22 Feb 2024
- Research & Ideas
How to Make AI 'Forget' All the Private Data It Shouldn't Have
generative AI. Prior machine learning systems did leak training data. The difference here is that first of all, these things are being so widely deployed. And so, there's just greater risk when so many systems are being built on top of...
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- 23 Apr 2024
- In Practice
Getting to Net Zero: The Climate Standards and Ecosystem the World Needs Now
With each month clocking record-breaking temperatures across the planet, this Earth Day reflected the renewed urgency of regulators and businesses to find climate-change solutions. The US Securities and Exchange Commission recently adopted new rules that will mandate...
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by Rachel Layne
- 19 Jan 2015
- Research & Ideas
Is Wikipedia More Biased Than Encyclopædia Britannica?
For more than a century, the long, stately rows of Encyclopædia Britannica have been a fixture on the shelves of many an educated person's home—the smooshed-together diphthong in the first word a symbol of old-world erudition and...
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- 24 Jan 2005
- Research & Ideas
Rethinking Activity-Based Costing
customer rather than assign resource costs first to activities and then to products or customers. For each group of resources, estimates of only two parameters are required: the cost per time unit of supplying resource capacity and the...
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by Robert S. Kaplan & Steven R. Anderson
- 21 Nov 2019
- Research & Ideas
Do TV Debates Sway Voters?
Intense preparation helped Hillary Clinton command the podium in her first debate with Donald Trump in September 2016—the most-watched presidential debate in US history. In one of the debate’s most memorable moments, Clinton called out...
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by Danielle Kost