The Federation of Analytical Chemistry and Spectroscopy Societies (FACSS) announced that James Hendler will deliver the keynote address at the SciX Conference this year.
Since 1974, the Federation of Analytical Chemistry and Spectroscopy Societies (FACSS) has hosted the annual Scientific Exchange, also known as SciX, conference (1). This annual conference brings together researchers, academics, and industry leaders in analytical chemistry and spectroscopy to share their latest research, products, and innovations. Conference attendees have the unique opportunity for in-person discussions of the most recent research and developments in the field of spectroscopy. Last year, the SciX 2023 Conference was held in Sparks, Nevada.
This year, the SciX Conference will take place on the east coast. From October 20–25th, the SciX 2024 Conference will be held at the Raleigh Convention Center, in Raleigh, North Carolina. To kick off the SciX 2024 Conference, James Hendler of Rensselaer Polytechnic Institute (RPI) will deliver the opening keynote address, which is titled “The Foundations of AI: Exploring the Spectrum” (2).
Downtown Raleigh, North Carolina, USA Skyline Aerial | | Image Credit: © Kevin Ruck - stock.adobe.com
Artificial intelligence (AI) is a hot topic in analytical chemistry and analytical spectroscopy. The biggest impact AI has had on the scientific field is automating several tasks related to data analysis. Because chromatographers and spectroscopists often deal with complex data sets in their work, AI has been used to simplify this process by interpreting large data sets to drive increases in efficiency and accuracy (3). The challenges of using AI are related to interpreting AI models, which require large data sets for training (3). Scientists also have expressed concerns regarding data security and scientific integrity (3). As an example, the main questions regarding the integration of AI is how and when it should be used? Full AI integration brings about a host of issues that scientists would prefer not to have to delve into at this point.
Hendler will touch upon these topics in his keynote address. Hendler is the Director of the Future of Computing Institute and the Tetherless World Professor at Rensselaer Polytechnic Institute (RPI) (2). As a data scientist, he is recognized as one of the creators of the Semantic Web and has authored over 450 publications on topics such as AI, Open Data, and data governance. Hendler has held key roles, including Chief Scientist at DARPA and Open Data Advisor to New York State (2). He has also served on various advisory boards, including the U.S. Homeland Security Science and Technology Committee and the National Academies Board on Research Data (2). Hendler is a Fellow of several prestigious organizations, including the AAAI and IEEE (2).
Hendler’s talk will take place from 6:00 pm–7:15 pm in Ballroom A (4). It will address the breakthroughs in AI, particularly large language models (LLMs) like ChatGPT, which have captured public attention. Hendler will highlight that foundational models, central to AI development, often overshadow other crucial areas of AI and machine learning (ML) (4). Hendler will touch upon how LLMs work, their potential applications in scientific research, and their limitations. He will emphasize the importance of data sharing and information provenance for scientific integrity, particularly for bench scientists focused on curiosity-driven discoveries (4). This talk will push for a balanced approach to AI, recognizing both its strengths and limitations in advancing scientific research.
The potential of AI is extraordinary, and if used properly, it could drive scientific breakthroughs for generations to come. However, Hendler advocates for a popular position in the scientific community, and that is to have a balanced approach with using AI and human ingenuity. A balanced approach will, as Spectroscopy executive editor Jerome Workman, Jr. stated in a recent news article, “ensure technological advances go hand in hand with sustainable human and environmental progress” (3).
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