Released
The New Skills in Finance Report 2022
In a digital-transforming era, there is a widening skills gap for those who cannot adapt to the new digital world in finance.
CFTE and Elevandi published the report with the discussion with leading experts to help governments, organisations and individuals address the current skills gap in finance and build a digital-resilient workforce in the industry.
Key Insights
The Future of Generative AI. What could we see five years following the launch of ChatGPT?
This first iteration of this foresight brief (May 2023) explores some potential shifts and disruptions that may arise due to generative artificial intelligence (AI) technologies in the next five years.
Key Aspects
- The report includes insights from interviews with experts like Sarah Guo, Gary Marcus, and Goldman Sachs analysts Kash Rangan and Eric Sheridan, analyzing the capabilities and limitations of generative AI at its current stage.
Table of Contents
- Introduction: Generative AI – Hype or Truly Transformative?
- Interviews with Experts: Sarah Guo, Gary Marcus, Kash Rangan, and Eric Sheridan
- AI’s Potentially Large Economic Impacts
- US Equities: Gauging the AI Upside
- Markets Around Past Productivity Booms
- What We’re Hearing from Public Investors
- Additional Contributions and Insights
Key Findings and Insights
This report will give you an insight into:
- Error-Prone Nature of Generative AI:
Generative AI technologies like ChatGPT, while advanced, are prone to generating text that may appear credible but can be incorrect or nonsensical. This presents challenges in detecting errors and raises questions about the reliability of these technologies. The brief discusses the need for possibly shifting to new kinds of AI to overcome these limitations, suggesting ongoing research and development in the field. - Privacy and Intellectual Property Concerns: The training of generative AI models on extensive internet datasets has led to concerns regarding privacy violations and intellectual property rights. There are ongoing investigations and legal actions, such as those by the Privacy Commissioner of Canada and Italy’s data protection authority, examining potential privacy issues with tools like ChatGPT. Additionally, there are copyright lawsuits faced by image generators and other AI tools, highlighting the legal complexities surrounding AI-generated content.
- Potential to Perpetuate Bias:
The use of internet data for training generative AI models risks amplifying the perspectives of overrepresented groups online, particularly English speakers. This could lead to the exclusion or underrepresentation of marginalized groups such as non-English speakers, women, older people, Indigenous peoples, and persons with disabilities. The brief notes that many AI models are closed-source, making it difficult to audit and address these biases - Unleashing Innovation and Productivity:
Despite these challenges, the brief acknowledges the potential of generative AI to drive significant innovation and productivity gains across various sectors. It could transform scientific developments, enhance sectoral productivity, improve accessibility, and reshape education. - Challenges in Local Innovation and Computing Power: The dominance of major U.S.-based companies in the generative AI space, combined with a lack of computing power in Canada, may limit the ability of Canadian companies and researchers to develop their own generative AI models. Additionally, legal and privacy risks associated with the use of foreign-hosted data are highlighted as potential barriers to research and development.
- Value Capture in the Generative AI Ecosystem:
The brief explores the uncertainty in how value from generative AI will be captured, given the presence of both open-access and proprietary models. It suggests that infrastructure providers might be well-positioned to capture value, but the extent of value generation within Canada is unclear. - Regulatory Gaps and Unforeseen Risks:
Rapid advancements in generative AI, coupled with existing regulatory gaps, could lead to unforeseen risks. The brief points out that current regulatory frameworks focus more on finished products rather than embedding standards into the technology development pipeline, which could be inadequate for addressing the fast-paced evolution of AI technologies. - Environmental Impact of Generative AI:
Generative AI is noted as being particularly energy- and water-intensive, raising significant environmental concerns. The technology's carbon footprint might exceed that of industries like commercial flights, indicating a need for sustainable approaches in AI development and deploymen
Key infographics
Be AI-ready in this digital era
In the News
Previous
Next
