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Efficacy
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- Article
The Errors of Experts: When Expertise Hinders Effective Provision and Seeking of Advice and Feedback
By: Ting Zhang, Kelly Harrington and Elad Sherf
To be effective, experts need to simultaneously develop others (i.e. provide advice and feedback to novices) and advance their own learning (i.e. seek and incorporate advice and feedback from others). However, expertise, and the state of efficacy associated with it,...
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Keywords:
Expertise;
Self-efficacy;
Feedback;
Perspective Taking;
Cognitive Entrenchment;
Interpersonal Communication
Zhang, Ting, Kelly Harrington, and Elad Sherf. "The Errors of Experts: When Expertise Hinders Effective Provision and Seeking of Advice and Feedback." Current Opinion in Psychology 43 (February 2022): 91–95.
- 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...
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Keywords:
Black Box Explanations;
Bayesian Modeling;
Decision Making;
Risk and Uncertainty;
Information Technology
Slack, Dylan, Sophie Hilgard, Sameer Singh, and Himabindu Lakkaraju. "Reliable Post hoc Explanations: Modeling Uncertainty in Explainability." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- Article
Learning Models for Actionable Recourse
By: Alexis Ross, Himabindu Lakkaraju and Osbert Bastani
As machine learning models are increasingly deployed in high-stakes domains such as legal and financial decision-making, there has been growing interest in post-hoc methods for generating counterfactual explanations. Such explanations provide individuals adversely...
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Ross, Alexis, Himabindu Lakkaraju, and Osbert Bastani. "Learning Models for Actionable Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- June 2021
- Teaching Note
Pearson: Efficacy 2.0
By: Elie Ofek and Marco Bertini
Teaching Note for HBS Case No. 521-012.
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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...
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Sühr, Tom, Sophie Hilgard, and Himabindu Lakkaraju. "Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society 4th (2021).
- 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...
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Rahmattalabi, Aida, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, and Milind Tambe. "Fair Influence Maximization: A Welfare Optimization Approach." Proceedings of the AAAI Conference on Artificial Intelligence 35th (2021).
- 2021
- Working Paper
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...
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Keywords:
Machine Learning;
Econometric Analysis;
Instrumental Variable;
Random Forest;
Causal Inference;
Analysis;
Theory;
Measurement and Metrics;
Performance Consistency
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." Working Paper, 2021. (3rd Round Revision.)
- January 2021 (Revised March 2021)
- Case
Serum Institute of India (SII): Racing to Save Lives During a Pandemic
By: Rohit Deshpandé, Anjali Raina and Rachna Chawla
The CEO of Serum Institute of India (SII), a $12.8 billion Indian Family business is faced with a risky choice between principles and profit. SII is the largest manufacturer of vaccines in the world and Adar Poonawalla, the CEO and son of the founder has to decide how...
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Keywords:
Business Ethics;
Healthcare;
COVID-19;
Vaccines;
Family Business;
Ethics;
Health Care and Treatment;
Health Pandemics;
Leadership;
Corporate Accountability;
Fairness;
Growth and Development Strategy;
Health Industry;
India;
South Asia
Deshpandé, Rohit, Anjali Raina, and Rachna Chawla. "Serum Institute of India (SII): Racing to Save Lives During a Pandemic." Harvard Business School Case 521-028, January 2021. (Revised March 2021.)
- January 2021
- Case
Pearson: Efficacy 2.0
By: Elie Ofek, Marco Bertini, Oded Koenigsberg and James Weber
Pearson, which billed itself as the "world's learning company," faced a host of critical decisions in mid-2020. Several years prior, it had embarked on a new path that put the learner at the heart of the business and committed to a new strategic orientation. The new...
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Keywords:
Efficacy;
Learning;
Outcome or Result;
Measurement and Metrics;
Brands and Branding;
Marketing Communications;
Strategic Planning;
Education Industry
Ofek, Elie, Marco Bertini, Oded Koenigsberg, and James Weber. "Pearson: Efficacy 2.0." Harvard Business School Case 521-012, January 2021.
- Article
Towards Robust and Reliable Algorithmic Recourse
By: Sohini Upadhyay, Shalmali Joshi and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision making (e.g., loan
approvals), there has been growing interest in post-hoc techniques which provide recourse to affected
individuals. These techniques generate recourses under the assumption...
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Keywords:
Machine Learning Models;
Algorithmic Recourse;
Decision Making;
Forecasting and Prediction
Upadhyay, Sohini, Shalmali Joshi, and Himabindu Lakkaraju. "Towards Robust and Reliable Algorithmic Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- December 2020 (Revised April 2021)
- Case
IBM Watson at MD Anderson Cancer Center
By: Shane Greenstein, Mel Martin and Sarkis Agaian
After discovering that their cancer diagnostic tool, designed to leverage the cloud computing power of IBM Watson, needed greater integration into the clinical processes at the MD Anderson Cancer Center, the development team had difficult choices to make. The Oncology...
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Keywords:
Decision Making;
Innovation Strategy;
Knowledge Management;
Knowledge Use and Leverage;
Operations;
Failure;
Information Technology;
Applications and Software;
Health Care and Treatment;
Product Development;
Health Industry;
Information Technology Industry;
Technology Industry;
United States;
Houston;
Texas
Greenstein, Shane, Mel Martin, and Sarkis Agaian. "IBM Watson at MD Anderson Cancer Center." Harvard Business School Case 621-022, December 2020. (Revised April 2021.)
- Article
Incorporating Interpretable Output Constraints in Bayesian Neural Networks
By: Wanqian Yang, Lars Lorch, Moritz Graule, Himabindu Lakkaraju and Finale Doshi-Velez
Domains where supervised models are deployed often come with task-specific constraints, such as prior expert knowledge on the ground-truth function, or desiderata like safety and fairness. We introduce a novel probabilistic framework for reasoning with such constraints...
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Yang, Wanqian, Lars Lorch, Moritz Graule, Himabindu Lakkaraju, and Finale Doshi-Velez. "Incorporating Interpretable Output Constraints in Bayesian Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) 33 (2020).
- March 2020
- 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...
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- Article
What We Can Learn from Five Naturalistic Field Experiments That Failed to Shift Commuter Behaviour
By: Ariella S. Kristal and A.V. Whillans
Across five field experiments with employees of a large organization (n = 68,915), we examined whether standard behavioural interventions (“nudges”) successfully reduced single-occupancy vehicle commutes. In Studies 1 and 2, we sent letters and emails with nudges...
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Kristal, Ariella S., and A.V. Whillans. "What We Can Learn from Five Naturalistic Field Experiments That Failed to Shift Commuter Behaviour." Nature Human Behaviour 4, no. 2 (February 2020): 169–176. (This article was featured on the cover as the lead article.)
- Article
The Mixed Effects of Online Diversity Training
By: Edward H. Chang, Katherine L. Milkman, Dena M. Gromet, Robert W. Rebele, Cade Massey, Angela L. Duckworth and Adam M. Grant
We present results from a large (n = 3,016) field experiment at a global organization testing whether a brief science-based online diversity training can change attitudes and behaviors toward
women in the workplace. Our preregistered field experiment included an...
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Chang, Edward H., Katherine L. Milkman, Dena M. Gromet, Robert W. Rebele, Cade Massey, Angela L. Duckworth, and Adam M. Grant. "The Mixed Effects of Online Diversity Training." Proceedings of the National Academy of Sciences 116, no. 16 (April 16, 2019): 7778–7783.
- April 2019 (Revised January 2022)
- Case
Clear Link Technologies, LLC: Driving Sales with Peer Effects
By: Christopher Stanton, Richard Saouma and Olivia Hull
The importance of a good peer or coworker is widely discussed, but understanding the glue that makes coworkers valuable is less understood. This case sheds light on the importance of peers and the practices and environments that make a group greater than the sum of its...
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Keywords:
Talent and Talent Management;
Interactive Communication;
Experience and Expertise;
Decision Making;
Training;
Design;
Compensation and Benefits;
Knowledge Acquisition;
Knowledge Sharing;
Human Capital;
Working Conditions;
Measurement and Metrics;
Outcome or Result;
Performance;
Performance Improvement;
Research;
Sales;
Salesforce Management;
Motivation and Incentives;
Telecommunications Industry;
Utah;
United States
Stanton, Christopher, Richard Saouma, and Olivia Hull. "Clear Link Technologies, LLC: Driving Sales with Peer Effects." Harvard Business School Case 819-072, April 2019. (Revised January 2022.)
- September 2018
- Case
Kevin Ryan Inc.
By: Shikhar Ghosh and Greg Marsh
The case focuses on the hiring process for a CEO. Kevin Ryan had a solid trajectory as a serial entrepreneur of well-known ventures like Gilt Group, DoubleClick, Business Insider, among others. Ryan tended to involve himself in all aspects of his ventures: ideation,...
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Keywords:
Hiring;
Team Building;
Interviews;
CEO;
Human Resources;
Selection and Staffing;
Entrepreneurship;
Business Startups;
United States;
North America
Ghosh, Shikhar, and Greg Marsh. "Kevin Ryan Inc." Harvard Business School Case 819-047, September 2018.
- Article
Evaluating the Effectiveness of Corporate Compliance Programs: Establishing a Model for Prosecutors, Courts, and Firms
By: Eugene F. Soltes
When prosecutors, courts, and regulators make charging and sentencing decisions, they must evaluate whether firms have effective compliance programs. Such evaluations are difficult because of the challenges associated with measuring effectiveness. Notably, these...
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Keywords:
Corporate Governance;
Governance Compliance;
Performance Effectiveness;
Performance Evaluation
Soltes, Eugene F. "Evaluating the Effectiveness of Corporate Compliance Programs: Establishing a Model for Prosecutors, Courts, and Firms." NYU Journal of Law & Business 14, no. 3 (Summer 2018): 965–1011.
- May–June 2018
- Article
The Surprising Power of Questions
By: Alison Wood Brooks and Leslie K. John
Much of an executive’s workday is spent asking others for information—requesting status updates from a team leader, for example, or questioning a counterpart in a tense negotiation. Yet unlike professionals such as litigators, journalists, and doctors, who are taught...
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Keywords:
Interpersonal Communication;
Communication Strategy;
Information;
Knowledge Sharing;
Performance Effectiveness
Brooks, Alison Wood, and Leslie K. John. "The Surprising Power of Questions." Harvard Business Review 96, no. 3 (May–June 2018): 60–67.
- 2018
- Working Paper
Zig-Zagging Your Way to Transformative Impact
By: V. Kasturi Rangan and Tricia Gregg
Achieving transformative impact has been much discussed by social entrepreneurs, funders, and consultants. These discussions have focused on issues of increasing impact and scale, but often with no clear distinction between the two terms. In order to provide clarity,...
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Keywords:
Social Entrepreneurship;
Performance Efficiency;
Growth and Development;
Outcome or Result;
Strategy
Rangan, V. Kasturi, and Tricia Gregg. "Zig-Zagging Your Way to Transformative Impact." Harvard Business School Working Paper, No. 18-062, January 2018.