machine learning - Publications - Faculty & Research - Harvard Business School

Filter Results: (950)

Filter Results: (950)

Show Results For

← Page 28 of 950 Results →

March 2025
Case

Mobvoi’s Path Through Market Challenges and Business Reinvention

By: Paul A. Gompers and Shu Lin

Founded in 2012, Mobvoi evolved through multiple transformations—from AI-driven voice technology to smart wearables and later AI-generated content. Backed by major investors, the company navigated shifts in strategy while facing two failed IPO attempts. As market... View Details

Keywords: Business Startups; Entrepreneurship; AI and Machine Learning; Technology Industry; China

July–August 2021
Article

Why You Aren't Getting More from Your Marketing AI

By: Eva Ascarza, Michael Ross and Bruce G.S. Hardie

Fewer than 40% of companies that invest in AI see gains from it, usually because of one or more of these errors: (1) They don’t ask the right question, and end up directing AI to solve the wrong problem. (2) They don’t recognize the differences between the value of... View Details

Keywords: Artificial Intelligence; Marketing; Decision Making; Communication; Framework; AI and Machine Learning

Find at Harvard

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,... View Details

Keywords: Large Language Model; AI and Machine Learning; Analytics and Data Science; Health Industry

October 14, 2023
Article

Will Consumers Buy Selfish Self-Driving Cars?

By: Julian De Freitas

Keywords: AI and Machine Learning; Ethics; Technological Innovation; Safety; Auto Industry

Find at Harvard

Register to Read

May 9, 2023
Article

8 Questions About Using AI Responsibly, Answered

By: Tsedal Neeley

Generative AI tools are poised to change the way every business operates. As your own organization begins strategizing which to use, and how, operational and ethical considerations are inevitable. This article delves into eight of them, including how your organization... View Details

Keywords: AI and Machine Learning; Organizational Change and Adaptation; Prejudice and Bias; Ethics

Register to Read

2025
Article

Humor as a Window into Generative AI Bias

By: Roger Samure, Julian De Freitas and Stefano Puntoni

A preregistered audit of 600 images by generative AI across 150 different prompts explores the link between humor and discrimination in consumer-facing AI solutions. When ChatGPT updates images to make them “funnier”, the prevalence of stereotyped groups changes. While... View Details

Keywords: AI and Machine Learning; Demographics; Prejudice and Bias

2025
Working Paper

The Impact of Input Inaccuracy on Leveraging AI Tools: Evidence from Algorithmic Labor Scheduling

By: Caleb Kwon, Antonio Moreno and Ananth Raman

Problem Definition: Considerable academic and practitioner attention is placed on the value of ex-post interactions (i.e., overrides) in the human-AI interface. In contrast, relatively little attention has been paid to ex-ante human-AI interactions (e.g., the... View Details

Keywords: AI and Machine Learning; Employees; Performance Effectiveness

June 20, 2023
Article

Cautious Adoption of AI Can Create Positive Company Culture

By: Joseph Pacelli and Jonas Heese

Keywords: AI and Machine Learning; Organizational Culture; Employees

September 2024
Background Note

Copyright and Fair Use

By: David B. Yoffie

The U.S. Copyright Office defines a copyright as “a type of intellectual property that protects original works of authorship as soon as an author fixes the work in a tangible form of expression.” Two core principles of copyright are originality and fixation. A work is... View Details

Keywords: AI and Machine Learning; Copyright; Lawsuits and Litigation; United States

August 25, 2022
Article

Find the Right Pace for Your AI Rollout

By: Rebecca Karp and Aticus Peterson

Implementing AI can introduce disruptive change and disfranchise staff and employees. When members are reluctant to adopt a new technology, they might hesitate to use it, push back against its deployment, or use it in limited capacity — which affects the benefits an... View Details

Keywords: AI and Machine Learning; Technology Adoption; Change Management

Article

Fake AI People Won't Fix Online Dating

By: Scott Duke Kominers

Computer-generated images may inspire even more distrust and surely won’t lead to the love of a lifetime. View Details

Keywords: Artificial Intelligence; Dating Services; Internet and the Web; Ethics; AI and Machine Learning

11 Oct 2024
Research & Ideas

How AI Could Ease the Refugee Crisis and Bring New Talent to Businesses

says. “What we’re asking is, can we build algorithms that will help find better matches that will allow people to integrate more easily?” The paper presents data from Switzerland and the United States that showed promise in using machine... View Details

Keywords: by Ben Rand; Technology; Information Technology

2023
Working Paper

Black-box Training Data Identification in GANs via Detector Networks

By: Lukman Olagoke, Salil Vadhan and Seth Neel

Since their inception Generative Adversarial Networks (GANs) have been popular generative models across images, audio, video, and tabular data. In this paper we study whether given access to a trained GAN, as well as fresh samples from the underlying distribution, if... View Details

Keywords: Cybersecurity; Copyright; AI and Machine Learning; Analytics and Data Science

2023
Article

MoPe: Model Perturbation-based Privacy Attacks on Language Models

By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel

Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details

Keywords: Large Language Model; AI and Machine Learning; Cybersecurity

2023
Article

Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness

By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju

One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details

Keywords: AI and Machine Learning; Mathematical Methods

8 Sep 2023
Conference Presentation

Chatbots and Mental Health: Insights into the Safety of Generative AI

By: Julian De Freitas, K. Uguralp, Z. Uguralp and Stefano Puntoni

Keywords: AI and Machine Learning; Well-being

Article

Why Boards Aren't Dealing with Cyberthreats

By: J. Yo-Jud Cheng and Boris Groysberg

Keywords: Board Of Directors; Cybersecurity; Corporate Governance; AI and Machine Learning

Register to Read

January 2024
Case

The Financial Times (FT) and Generative AI

By: Andrew Rashbass, Ramon Casadesus-Masanell and Jordan Mitchell

In September 2023, John Ridding, CEO of the Financial Times, was considering the possible impact of Generative AI on the industry and his business. Having navigated successfully the seismic shift from print to digital, and reporting record results, the company... View Details

Keywords: AI and Machine Learning; Technology Adoption; Change Management; Journalism and News Industry

January 2024 (Revised February 2024)
Case

OpenAI: Idealism Meets Capitalism

By: Shikhar Ghosh and Shweta Bagai

In November 2023, the board of OpenAI, one of the most successful companies in the history of technology, decided to fire Sam Altman, its charismatic and influential CEO. Their decision shocked the corporate world and had people wondering why OpenAI had designed a... View Details

Keywords: AI; AI and Machine Learning; Governing and Advisory Boards; Ethics; Strategy; Technological Innovation; Leadership

2025
Article

Ideation with Generative AI—In Consumer Research and Beyond

By: Julian De Freitas, G. Nave and Stefano Puntoni

The use of large language models (LLMs) in consumer research is rapidly evolving, with applications including synthetic data generation, data analysis, and more. However, their role in creative ideation—a cornerstone of consumer research—remains underexplored. Drawing... View Details

Keywords: Large Language Model; AI and Machine Learning; Creativity; Innovation Strategy

←
28
29
…
47
48
→