Generative AI Series: References and Navigation

Welcome to the comprehensive reference list for our 5-part series on Generative AI.

This page serves as a central resource for all the sources cited throughout the series, providing you with a deeper dive into the research, statistics, and expert opinions that inform our exploration of this transformative technology.

Navigate the Series

If you haven’t read all parts of the series yet, or if you’d like to revisit any section, you can find links to each article below.

The links are active once the post is published:

Part 1: Generative AI: Reshaping Our World
Published On: July 29, 2024

An introduction to generative AI and its potential to redefine our understanding of intelligence and creativity.

Part 2: Capabilities, Limitations, and Real-World Applications
Published On: July 30, 2024

Exploring the strengths and weaknesses of generative AI, with a focus on its application in pharmaceutical research.

Part 3: Impact and Adoption Across Industries
Published On: July 31, 2024

An examination of how various sectors are leveraging generative AI and its potential economic impact.

Part 4: Ethical Implications
Published On: August 1, 2024

A deep dive into the ethical challenges posed by generative AI and potential approaches to address them.

Part 5: Preparing Your Business for the AI Revolution
Published On: August 2, 2024

Practical steps for businesses to prepare for the integration of generative AI, from strategy development to fostering a culture of innovation.

About the References

The references listed below encompass a wide range of sources, including academic papers, industry reports, news articles, and expert analyses.

They have been carefully selected to provide a comprehensive and balanced view of the current state and future potential of generative AI.

We encourage readers to explore these sources for a deeper understanding of the topics discussed in our series.

Please note that the field of AI is rapidly evolving, and new research is constantly emerging.

While we strive to provide the most up-to-date information, we recommend checking for the latest developments in areas of particular interest.

Without further ado, here is the full list of references used throughout our Generative AI series:

Generative AI and Machine Learning

1. Brown, T., et al. (2020). Language Models are Few-Shot Learners. arXiv:2005.14165.
2. Bender, E. M., et al. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? FAccT ’21.
3. Maynez, J., et al. (2020). On Faithfulness and Factuality in Abstractive Summarization. arXiv:2005.00661.
4. Wiggers, K. (2020). OpenAI’s massive GPT-3 model is impressive, but size isn’t everything. VentureBeat.
5. Anthropic. (2024, June 20). Claude 3.5 Sonnet. LINK
6. OpenAI. (2023). ChatGPT reaches 100 million monthly active users.

AI Impact and Adoption

7. Chui, M., et al. (2023). The Economic Potential of Generative AI: The Next Productivity Frontier. McKinsey Global Institute.
8. PwC. (2023). Global AI Study: AI could contribute up to $15.7 trillion to the global economy by 2030.
9. Deloitte. (2022). State of AI in the Enterprise, 5th Edition.
10. Ernst & Young (EY). (2023). EY AI Adoption Index.
11. Bain & Company. (2023). AI Report: By 2030, 30% of all hours worked globally could be automated.
12. Gartner. (2023). Emerging Tech Impact Radar: By 2025, generative AI will be a workforce partner for 90% of companies worldwide.
13. IBM. (2022). Global AI Adoption Index.
14. NVIDIA. (2023). Financial Results, Q2 2023.
15. Microsoft. (2023). Press Release: $10 billion investment in OpenAI.
16. Google. (2023). AI Blog: Commitment to invest $25 billion in AI research and development.
17. MIT Technology Review. (2023). The Algorithm: 50% of organizations using ChatGPT for tasks.
18. Stanford University. (2023). AI Index Report.
19. Accenture. (2023). AI: Built to Scale.

Environmental Impact of AI

20. Microsoft. (2024). 2024 Environmental Sustainability Report. LINK
21. World Economic Forum. (2024, July 22). Generative AI: Energy and Emissions. LINK
22. Berreby, D. (2024, February 6). As Use of A.I. Soars, So Does the Energy and Water It Requires. Yale Environment 360, Yale School of the Environment.

AI and the Future of Work

23. World Economic Forum. (2020, October 20). Recession and Automation Changes Our Future of Work, But There are Jobs Coming, Report Says. LINK
24. Gregg, I. (2024, March 12). The Future Of Work: Embracing AI’s Job Creation Potential. Forbes. LINK

AI in Insurance and Finance

25. Rafique, A., & Woleben, J. (2022, April 4). US P&C insurers’ expense ratio falls to lowest level in 5 years. S&P Global. LINK
26. Statista. (n.d.). Life and non-life insurance direct premiums written globally from 2006 to 2022. LINK

Historical and Philosophical Context

27. Bentsen, S. (n.d.). Fire Use. Oxford Research Encyclopedia of Anthropology. LINK
28. Menick, J. (2016). Move 37: Artificial Intelligence, Randomness and Creativity: Part 2. Mousse Magazine. LINK
29. Jauk, E., Benedek, M., Dunst, B., & Neubauer, A. C. (2013). The relationship between intelligence and creativity: New support for the threshold hypothesis by means of empirical breakpoint detection.
30. Endsley, M. R. (n.d.). Theoretical underpinnings of situation awareness: a critical review. SA Technologies.

Archaeological Reference

31. Gobekli Tepe (Potbelly Hill), a Neolithic, pre-hieroglyphics, archaeological site in the Southeastern Anatolia Region of Turkey, dating back to 11,500 years ago. UNESCO

Visual References

32. Visual used on Part 2 is from BrainMaps.Org. https://brainmaps.org/ajax-viewer.html?path=http://brainmaps.org/HBP2/misc/graphgen-output-good4a/&width=2499&height=3618