Amanda Stent stands at the forefront of artificial intelligence advancements at Bloomberg, drawing on a rich career that began in the early days of natural language processing (NLP). With a PhD focused on NLP from the University of Rochester, completed in 2001, Stent has cultivated a unique expertise that positions her as a leader in this rapidly evolving field. Reflecting on her journey, she quips, “Someone quite notable once said to me, ‘You have been doing AI for a very, very, very long time’ – that’s three verys,” showcasing her long-standing commitment to AI research even before it gained widespread popularity.
In her early career at AT&T, Stent was part of pioneering efforts in speech and language processing, working on “computational journalism." This initiative sought to automate the process of generating news articles from structured data, such as stock price changes, well ahead of the generative AI boom that is shaping industries today. The concept of leveraging AI to create journalistic content reflects a visionary approach to technology that Stent carried with her through subsequent roles at Yahoo Labs and, ultimately, Bloomberg.
Upon her return to Bloomberg in 2016 as head of AI strategy and research, Stent encountered a company well-acquainted with AI, having utilised the technology since 2009. At that time, Bloomberg was ahead of the curve, offering clients sentiment analysis tools that provided insights into market behaviours—reflecting Stent's belief that AI technologies must serve practical client needs. Presently, her focus has shifted significantly towards generative AI, which she describes as crucial for generating actionable insights from three categories of data: structured (like price time series), unstructured (including news and research), and communications data. In her words, “Our focus these days… is on GenAI and how we can make the most effective use of it to solve real client problems.”
One specific application of generative AI that has gained traction is the summarisation of earnings call transcripts, allowing clients to access critical information efficiently. These summaries adhere to specific themes of interest identified by subject matter experts at Bloomberg, ensuring that clients receive bespoke insights without the need for exhaustive questioning. Stent emphasises the importance of “transparent attribution,” which allows clients to trace back the generated insights to their original context in the earnings calls.
However, as generative AI becomes more integral to financial services, so too do the risks associated with its use. Stent warns of the phenomenon often referred to as "AI hallucinations," where the technology may create false information or misrepresent data. This is particularly concerning in finance, where decision-making relies heavily on accuracy. Stent asserts, “You need to make sure that you are identifying the source or the provenance of the information the GenAI is using.” Ensuring objective outputs from AI systems is essential, especially as these technologies evolve to better integrate into human decision-making processes.
Stent’s insights are crucial as financial institutions grapple with harnessing AI’s potential, while ensuring ethical practices and transparency. She stresses the necessity of interdisciplinary collaboration and a diverse technological workforce to address the complex challenges posed by AI in finance. As Stent aptly puts it, “It affects everybody today, and we should all be informed and critical users,” reflecting a broader call for awareness not just among AI engineers, but across all sectors affected by these transformative technologies.
Despite her impressive achievements and deep expertise, Stent continues to actively engage with the academic community, advocating for diversity in the tech industry and the ethical implications of AI research. Her participation in conferences and collaborations highlights the importance of maintaining an informed dialogue in the AI community, inspiring the next generation of engineers and leaders in this pivotal field.
As AI continues to evolve, leaders like Amanda Stent are redefining its integration into not only the financial world but also the broader societal context, paving the way for responsible and informed use of advanced technologies.
Reference Map
- Lead article
- Related context on Stent's advocacy for NLP and machine learning
- Insights on Bloomberg's research publications
- Reflections on AI's evolution from academia to industry
- Exploration of ethical considerations in NLP
- Overview of financial text analytics techniques
- Best practices in managing data annotation projects
Source: Noah Wire Services