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  • Research Summary

Business and Low Income Sectors: The Creation of Economic and Social Value

In the last three decades, innovative commercial solutions have emerged in developing nations focusing on providing effective responses to the hugely underserved needs of low-income populations, both as consumers as well as active participants in productive value... View Details
  • 2023
  • Article

Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten

By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms
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  • 2020
  • Working Paper

Fresh Fruit and Vegetable Consumption: The Impact of Access and Value

By: Retsef Levi, Elisabeth Paulson and Georgia Perakis
The goal of this paper is to leverage household-level data to improve food-related policies aimed at increasing the consumption of fruits and vegetables (FVs) among low-income households. Currently, several interventions target areas where residents have limited... View Details
Keywords: Food Deserts; Food Access; Food Policy; Causal Inference; Food; Nutrition; Poverty; Government Administration
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  • 2021
  • Article

Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring

By: Tom Sühr, Sophie Hilgard and Himabindu Lakkaraju
Ranking algorithms are being widely employed in various online hiring platforms including LinkedIn, TaskRabbit, and Fiverr. Prior research has demonstrated that ranking algorithms employed by these platforms are prone to a variety of undesirable biases, leading to the... View Details
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  • 30 May 2013
  • Working Paper Summaries

Non-Standard Matches and Charitable Giving

Keywords: by Michael Sanders, Sarah Smith & Michael I. Norton
  • 05 Sep 2023
  • Book

Failing Well: How Your ‘Intelligent Failure’ Unlocks Your Full Potential

acid deficiency. When the drug was reformulated with folic acid, it passed its efficacy trials, eventually becoming a multibillion-dollar pharmaceutical that helped thousands of lung cancer patients. How to fail intelligently Edmondson,... View Details
Keywords: by Michael Blanding
  • 17 Dec 2013
  • First Look

First Look: December 17

  Publications August 2013 Harvard Business Review Press Can China Lead? Reaching the Limits of Power and Growth By: Abrami, Regina M., William C. Kirby, and F. Warren McFarlan Abstract—At the time of the American Revolution, China was the strongest, richest, and most... View Details
Keywords: Carmen Nobel
  • Article

Reliable Post hoc Explanations: Modeling Uncertainty in Explainability

By: Dylan Slack, Sophie Hilgard, Sameer Singh and Himabindu Lakkaraju
As black box explanations are increasingly being employed to establish model credibility in high stakes settings, it is important to ensure that these explanations are accurate and reliable. However, prior work demonstrates that explanations generated by... View Details
Keywords: Black Box Explanations; Bayesian Modeling; Decision Making; Risk and Uncertainty; Information Technology
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  • 2014
  • Working Paper

Bridging Science and Technology Through Academic-Industry Partnerships

By: Sen Chai and Willy C. Shih
Scientific research and its translation into commercialized technology is a driver of wealth creation and economic growth. Partnerships to foster the translational processes from public research organizations, such as universities and hospitals, to private firms are a... View Details
Keywords: Innovation; Firm Performance; Public-private Partnership Funding; Translational Research; Small And Medium Enterprises; Partners and Partnerships; Public Sector; Private Sector; Performance; Science-Based Business; Innovation and Invention
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  • 2021
  • Article

Fair Influence Maximization: A Welfare Optimization Approach

By: Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice and Milind Tambe
Several behavioral, social, and public health interventions, such as suicide/HIV prevention or community preparedness against natural disasters, leverage social network information to maximize outreach. Algorithmic influence maximization techniques have been proposed... View Details
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  • October–December 2022
  • Article

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
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  • 11 Apr 2017
  • First Look

First Look at New Research, April 11

forthcoming Journal of Accounting & Economics Career Concerns of Banking Analysts By: Horton, Joanne, George Serafeim, and Shan Wu Abstract—We study how career concerns influence banking analysts' forecasts and how their forecasting behavior benefits both them and... View Details
  • Research Summary

Of Measurement and Mission: Accounting for Performance in Non-Governmental Organizations

By: Debora L. Spar
As members of civil society NGOs would seem to have a built-in proclivity towards representation: towards working on behalf of some group of people, or toward some specific goal. Yet in practice such moments of accountability are rare. Unlike other social agents,... View Details
  • 2023
  • Article

Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse

By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means... View Details
Keywords: AI and Machine Learning; Decision Choices and Conditions; Mathematical Methods
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    Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

    Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data,... View Details
    • March 2020 (Revised June 2023)
    • Case

    EyeControl: Inspiring Communication

    By: Paul A. Gompers and Danielle Golan
    Eye-controlled communication device startup EyeControl was founded in Tel Aviv, Israel in 2016 by cofounders with a shared personal connection to locked-in syndrome—a neurological disorder that left sufferers cognitively sound, yet paralyzed, with the exception of eye... View Details
    Keywords: Health Disorders; Communication Technology; Business Startups; Expansion; Finance; Decision Making; Social Enterprise; Medical Devices and Supplies Industry
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    • May 15, 2012
    • Article

    Ensuring Quality Cancer Care: A Follow-Up Review of the Institute of Medicine’s 10 Recommendations for Improving the Quality of Cancer Care in America

    By: Tracy E. Spinks, Heidi W. Albright, Thomas W. Feeley, Ron Walters, Thomas W. Burke, Thomas Aloia, Eduardo Bruera, Aman Buzdar, Lewis Foxhall, David Hui, Barbara Summers, Alma Rodriguez, Raymond DuBois and Kenneth I. Shine
    Responding to growing concerns regarding the safety, quality, and efficacy of cancer care in the United States, the Institute of Medicine (IOM) of the National Academy of Sciences commissioned a comprehensive review of cancer care delivery in the US health care system... View Details
    Keywords: Cancer; Quality; Cancer Care In The U.S.; Quality Improvement; Health Care and Treatment; Health Industry; North and Central America
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    • 09 May 2013
    • Working Paper Summaries

    Clusters of Entrepreneurship and Innovation

    Keywords: by Aaron Chatterji, Edward Glaeser & William Kerr
    • May 2024
    • Article

    Design of Off-Grid Lighting Business Models to Serve the Poor: Field Experiments and Structural Analysis

    By: Bhavani Shanker Uppari, Serguei Netessine, Ioanna Popescu and Rowan P. Clarke
    A significant proportion of the world's population has no access to grid-based electricity and so relies on off-grid lighting solutions. Rechargeable lamp technology is gaining popularity as an alternative off-grid lighting model in developing countries. In this paper,... View Details
    Keywords: Technological Innovation; Developing Countries and Economies; Consumer Behavior; Poverty; Logistics; Business Model; Utilities Industry
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    • January–February 2023
    • Article

    Data-Driven COVID-19 Vaccine Development for Janssen

    By: Dimitris Bertsimas, Michael Lingzhi Li, Xinggang Liu, Jennings Xu and Najat Khan
    The COVID-19 pandemic has spurred extensive vaccine research worldwide. One crucial part of vaccine development is the phase III clinical trial that assesses the vaccine for safety and efficacy in the prevention of COVID-19. In this work, we enumerate the first... View Details
    Keywords: COVID-19; Health Testing and Trials; Forecasting and Prediction; AI and Machine Learning; Research; Pharmaceutical Industry
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