AI-Related Research Guide: From Insights to Impact
Resources presented in this guide allow researchers and students to detect AI-related emerging trends, explore how AI can address business pain points, transform industries, and gain insights into new business practices. It covers a vast array of topics from diverse aspects across disciplines and real-world applications. The curated resource collections feature real-world news, data sources, in-depth studies and publications, professional networks, and expert insights.
Related: Learn with Baker Library: Generative AI for MBAs offers an introduction to the effective and responsible use of generative artificial intelligence tools to support your MBA learning at HBS.
Getting Started
Research
Harness critical data and practical insights from these resources to capitalize on opportunities in the AI era.
Data Sources and Tools
Consider copyright, ethical and legal issues, data security, accessibility, and stakeholders before collecting project data.
If you need to log in to access a dataset, your institution has negotiated terms of access to that data. Violating those terms could jeopardize future access for you and others.
Opensource content is not automatically free from copyright. Make sure you understand the license terms and respect the rights of the original creators when using opensource materials for AI training.
Find Datasets
Text Mining
Shape Responsible AI Practice
As businesses race to adapt operations around AI, rapid AI development is outpacing regulation. Bridging government-industry AI understanding is crucial. Contribute to the development of AI ethics and enforcement of AI governance with your research, knowledge sharing, and practice. In this section, the term “responsible AI” refers to AI governance that establishes the organizational processes for AI, guided by the ethical principles defined by AI ethics.
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