Gain practical insights into the latest advancements in generative AI and learn to use them to your advantage.

As AI continues to rapidly develop and integrate itself into our daily lives, gaining a deeper understanding of this technology is becoming increasingly important. Whether you embrace this change or are wary of its potential impact on our future, acquiring knowledge about AI and how to leverage its capabilities can provide a significant advantage. 

That is why this class offers researchers in entrepreneurship the necessary skills to effectively use Large Language Models (LLM) — such as ChatGPT — in their academic research.

The class will cover different aspects of using generative AI, including the theoretical background and some examples of practical application in research; for example, how to use ChatGPT to generate high-quality content for research papers, proposals, and grant applications.

The class is held in one day, divided into 2 sessions: the first one in the morning to provide the necessary elements for effective use of ChatGPT, the second one in the afternoon to apply what has been learned. 

objectives

The class aims to show participants how to effectively integrate new generative AI tools within their research workflow. AI tools are not intended as substitutes, but rather as tools to support brainstorming, exploration, analysis and synthesis processes. Objectives include:

• Providing a background of the evolution of generative AI models
• Providing an overview of the features and capabilities of ChatGPT
• Analysing prompt engineering techniques for different purposes
• Exploring several applications of ChatGPT in academic research
• Providing hands-on experience with using ChatGPT for research purposes
• Critically evaluating the AI generated outcomes

who is this for?

The workshop is designed for PhD students and scholars in entrepreneurship who are approaching the use of new generative AI tools. No prior experience in machine learning or coding expertise is required.

schedule

MORNING

Introducing Generative AI

1.1. Brief historical background: from first AI to generative AI1.2. Focus on Natural Language Processing (NLP)

1.3. Mapping generative AI tools

1.4. ChatGPT and other competitors

Generative AI in Business

2.1. In Marketing: content generation, sentiment analysis, summarisation

2.2. In Product Development

2.3. In Art: generating images, music, and videos

2.4. In Research: the topic of this class

How to Use ChatGPT

3.1. Prompt engineering

ChatGPT in Entrepreneurship Research

4.1. Define an article structure

4.2. Conducting a literature review

4.3. Doing qualitative research

4.4. Doing quantitative research (data analysis)

4.5. Generating code

4.6. Writing an article (storytelling, etc.)

Discussion

5.1. Ethical considerations

5.2. Ownership, copyright, and authenticity

AFTERNOON

Hands-On Session — Write Your Own Paper Using Only AI

6.1. Explore and analyse prior literature

6.2. Find research gap

6.3. Generate synthetic data

6.4. Analyse data

6.5. Analyse results

6.6. Wrap up

Presenting Your Outcome

Feedback on Outcomes and Conclusion

ABOUT THE INSTRUCTOR

Francesco Ferrati holds a PhD in Management Engineering from the University of Padova, Italy. He is currently a research fellow in Entrepreneurship at the University of Padova where he also teaches a Master’s Degree course in “Business Administration and Organisation”. His research interests include the analysis of key success factors for tech-driven startups and equity investors’ decision-making processes. From a methodological perspective, he applies a strongly data-driven approach, based on the analysis of large business-related datasets through advanced data mining and machine learning techniques. He also has a general interest in artificial intelligence as a driver for new methodological approaches to entrepreneurship.