Exploring the Impact of Artificial Intelligence on Investment Management
For a deeper dive into the role of artificial intelligence (AI) in investment management, make sure to check out The Handbook of Artificial Intelligence and Big Data Applications in Investments by Larry Cao, CFA, from the CFA Institute Research Foundation.
Understanding Performance and Data in AI
Delving into the realm of AI, particularly large language models like ChatGPT, reveals the intricate neural network behind these technologies. With numerous layers and hefty parameters, these models require extensive training on vast datasets to function effectively. The costs associated with training such models are significant, with estimates pointing to multimillion-dollar expenses and considerable electricity consumption.
Despite the investment in larger models like ChatGPT-4, the need for enhanced performance may necessitate alternative approaches beyond simply scaling up computing power. Researchers are exploring avenues for improvement that extend beyond raw processing capability.
One key challenge lies in accessing diverse and high-quality datasets, a crucial factor in enhancing the performance of language models. While existing data from the internet forms a substantial foundation, unlocking additional curated data from various sources could further refine these models for domain-specific tasks.
Addressing Challenges in AI Deployment
As AI applications like ChatGPT find their place in industries such as legal services, concerns around accuracy and misuse come to the forefront. While these models showcase impressive capabilities, their statistical nature can lead to inaccuracies, particularly in complex tasks like mathematics.
Moreover, the susceptibility of AI models to “hallucinations” presents a risk of spreading misinformation or facilitating unethical practices. To mitigate these challenges, strategies such as fine-tuning with domain-specific data and reinforcement learning from human feedback are being explored to enhance the reliability and ethical considerations of these AI systems.
Striving for transparency in AI models like ChatGPT is essential to build trust and address the inherent black-box nature of these technologies. Exploring avenues for explainable AI and establishing robust governance frameworks can pave the way for responsible AI deployment in various sectors.
Looking Ahead: Balancing Potential and Risks
The advancements in AI and machine learning hold immense promise for economic and societal transformation. However, embracing technologies like ChatGPT requires a thoughtful approach to risk governance and compliance. Organizations must prioritize safety and accountability in their AI strategies to harness the benefits of these cutting-edge tools.
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Disclaimer: The views expressed in this post are the author’s own and do not constitute investment advice. They do not necessarily reflect the opinions of CFA Institute or the author’s employer.
Image credit: ©Getty Images /Yuichiro Chino
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