Theory Of Machine - Publications - Faculty & Research - Harvard Business School

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July 2019 (Revised November 2019)
Case

Osaro: Picking the Best Path

By: William R. Kerr, James Palano and Bastiane Huang

The founder of Osaro saw the potential of deep reinforcement learning to allow robots to be applied to new applications. Osaro targeted warehousing, already a dynamic industry for robotics and automation, for its initial product—a system which would allow robotic arms... View Details

June 2012 (Revised December 2017)
Technical Note

Strategy and Strategic Decisions

By: Eric Van den Steen

This note introduces a framework for formulating strategy that helps a manager identify which decisions are strategic—and thus which decisions to focus on (both when developing strategy and when executing it)—and that provides a practical test for whether a particular... View Details

Keywords: Formulating Strategy; Strategic Theory; Strategy Test; Strategic Analysis; Strategy; Theory; Strategic Planning

Article

Experience Theory, or How Desserts Are Like Losses

By: Jolie M. Martin, Martin Reimann and Michael I. Norton

While many experiments have explored risk preferences for money, few have systematically assessed risk preferences for everyday experiences. We propose a conceptual model and provide convergent evidence from seven experiments that, in contrast to a typical “zero”... View Details

Keywords: Experiences; Monetary Gambles; Risk Preferences; Experience Theory; Risk and Uncertainty; Behavior; Decision Choices and Conditions

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Forthcoming
Article

Beefing IT Up for Your Investor? Engagement with Open Source Communities, Innovation, and Startup Funding: Evidence from GitHub

By: Annamaria Conti, Christian Peukert and Maria P. Roche

We study the engagement of nascent firms with open source communities and its implications for innovation and attracting funding. To do so, we link data on 160,065 U.S. startups from Crunchbase to their activities on the open source software development platform... View Details

Keywords: Startups; Knowledge; Open Source Communities; GitHub; Machine Learning; Innovation; Business Startups; Venture Capital; Information Technology; Strategy

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spring 2006
Article

All's Fair in Love, War, & Bankruptcy: Corporate Governance Implications of CEO Turnover in Financial Distress

By: Ethan S. Bernstein

Prior discussions of management turnover during financial distress have examined bankrupt and non-bankrupt firms as distinct groupings with little overlap. Separately investigating rates of turnover in-bankruptcy and out-of-bankruptcy, without a direct comparison... View Details

Keywords: CEO Turnover; Bankruptcy; Restructuring; Shadow Of Bankruptcy; Borrowing and Debt; Credit; Financing and Loans; Corporate Governance; Finance; Theory; Markets; United States

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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.... View Details

Keywords: Machine Learning; Algorithms; Objective Perturbation; Mathematical Methods

May 2000
Article

Maxmin Expected Utility over Savage Acts with a Set of Priors

By: Ramon Casadesus-Masanell, Peter Klibanoff and Emre Ozdenoren

This paper provides an axiomatic foundation for a maxmin expected utility over a set of priors (MMEU) decision rule in an environment where the elements of choice are Savage acts. This characterization complements the original axiomatizations of MMEU developed in a... View Details

Keywords: Uncertainty Aversion; Ambiguity; Expected Utility; Set Of Priors; Knightian Uncertainty; Decision Making; Game Theory; Risk and Uncertainty; Mathematical Methods

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August 2018 (Revised October 2019)
Case

C3.ai—Driven to Succeed

By: Robert Simons and George Gonzalez

CEO Tom Siebel navigates his artificial intelligence (ai) startup through a series of pivots, market expansions, and even an elephant attack to become a leading platform ad service provider. The case describes his unusual management approach emphasizing employee... View Details

Article

Counterfactual Explanations Can Be Manipulated

By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh

Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate... View Details

Keywords: Machine Learning Models; Counterfactual Explanations

15 Dec 2016
HBS Seminar

Joel Isaac, University of Cambridge

May 2016 (Revised April 2018)
Case

Building the Digital Manufacturing Enterprise of the Future at Siemens

This case describes the motivation for and the development of Siemens' digital manufacturing enterprise vision, which became the foundation for its implementation of Industrie 4.0. While the effort started with a purely defensive move by Anton Huber, head of the... View Details

Empire of Cotton

The epic story of the rise and fall of the empire of cotton, its centrality to the world economy, and its making and remaking of global capitalism.

Cotton is so ubiquitous as to be almost invisible, yet understanding its history is key to understanding the... View Details

16 Oct 2019
Research & Ideas

Read Our Most Popular Stories of the Quarter

What stories were readers like you diving into this summer on HBS Working Knowledge? Your interests varied dramatically, everything from how researchers use machine learning technology to predict CEO performance to the power View Details

Keywords: by Sean Silverthorne

2021
Working Paper

Time Dependency, Data Flow, and Competitive Advantage

By: Ehsan Valavi, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu and Karim R. Lakhani

Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government... View Details

Keywords: Economics Of AI; Value Of Data; Perishability; Time Dependency; Flow Of Data; Data Strategy; Analytics and Data Science; Value; Strategy; Competitive Advantage

December 2020
Case

VIA Science (A)

By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman

Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details

Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; Markets; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan

A Causal Test of the Strength of Weak Ties

The strength of weak ties is an influential social-scientific theory that stresses the importance of weak associations (e.g., acquaintance versus close friendship) in influencing the transmission of information through social networks. However, causal tests of... View Details

Article

Games of Threats

By: Elon Kohlberg and Abraham Neyman

A game of threats on a finite set of players, N, is a function d that assigns a real number to any coalition, S ⊆ N, such that d(S) = -d(N\S). A game of threats is not necessarily a coalitional game as it may fail to satisfy the condition d(Ø) = 0. We show that analogs... View Details

Keywords: Shapley Value; Coalitional Game; Game Theory; Mathematical Methods

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Research Summary

Understanding the Limitations of Model Explanations

By: Himabindu Lakkaraju

The goal of this research is to understand how adversaries can exploit various algorithms used for explaining complex machine learning models with an intention to mislead end users. For instance, can adversaries trick these algorithms into masking their racial and... View Details

2010
Article

On the Classification of Type II Codes of Length 24

By: Noam D. Elkies and Scott Duke Kominers

We give a new, purely coding-theoretic proof of Koch's criterion on the tetrad systems of Type II codes of length 24 using the theory of harmonic weight enumerators. This approach is inspired by Venkov's approach to the classification of the root systems of Type II... View Details

Keywords: Mathematical Methods

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August 2018 (Revised October 2020)
Case

Tailor Brands: Artificial Intelligence-Driven Branding

Using proprietary artificial intelligence technology, startup Tailor Brands set out to democratize branding by allowing small businesses to create their brand identities by automatically generating logos in just minutes at minimal cost with no branding or design skills... View Details

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