Ping An: NLP Takes on Greater Importance in Turbulent Times

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As the recently released GPT-3 and several recent studies demonstrate, racial bias, as well as bias based on gender, occupation, and religion, can be found in popular NLP language models. But a team of AI researchers wants the NLP bias research community to more closely examine and explore relationships between language, power, and social hierarchies like racism in their work. That’s one of three major recommendations for NLP bias researchers a recent study makes. Each recommendation comes with a series of questions designed to spark future research with the recommendations in mind. Authors say the key question NLP bias researchers should ask is “How are social hierarchies, language ideologies, and NLP systems coproduced? ” This question, authors said, is in keeping with Ruha Benjamin’s recent insistence that AI researchers consider the historical and social context of their work or risk becoming like IBM researchers who supported the Holocaust during World War II.

• As part of a growing list of governance and policy assets available to those deploying and providing AI systems, AI-SIAs can provide analytical frameworks and approaches to SIAs supported through technical rigor.
• This has included two campaign weeks, the creation of the AI Adoption Hub (now the AI Hub), the AI Leader’s Event Series, the Putting AI into Action webinar series and the Industrial AI sprint campaign.
• SDOH, which include factors such as socioeconomic status, access to healthy food, education, housing and physical environment, are strong predictors of suicidal behaviors.
• “Without this grounding, researchers and practitioners risk measuring or mitigating only what is convenient to measure or mitigate, rather than what is most normatively concerning,” the paper reads.
• The study authors and editorialist report no relevant financial relationships.

Usman Ikhlaq

Several studies have identified a range of common risk factors for suicide using International Classification of Diseases (ICD) codes and other “structured” data from the EHR. However, the use of unstructured EHR data from clinician notes has received little attention in investigating potential associations between suicide and SDOH. Researchers found SDOH are risk factors for suicide among US veterans and NLP can be leveraged to extract SDOH information from unstructured data in the EHR. TechUK is the trade association which brings together people, companies and organisations to realise the positive outcomes of what digital technology can achieve.

Sue is a keen sportswoman and in 2016 achieved a lifelong ambition to swim the English Channel. This shift in terminology reflects a broader understanding of what it takes to make LLMs effective in real-world applications. Linguistic/context engineering, is not just about crafting a single sentence or paragraph to guide the model. It is about curating and structuring all the relevant information that the model needs to perform a task effectively.

This has included two campaign weeks, the creation of the AI Adoption Hub (now the AI Hub), the AI Leader’s Event Series, the Putting AI into Action webinar series and the Industrial AI sprint campaign. Our members develop strong networks, build meaningful partnerships and grow their businesses as we all work together to create a thriving environment where industry, government and stakeholders come together to realise the positive outcomes tech can deliver. The importance of context in LLMs has led to a shift in focus from fine-tuning to prompt engineering, or as some now prefer to call it, context engineering. A lot of early writing on LLMs focused on fine-tuning — changing the weights in the underlying neural nets to try to improve performance. Fine-tuning involves adapting a pre-trained model to perform better on specific tasks by training it further on a narrower dataset.

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“We recommend that researchers and practitioners similarly ask how existing social hierarchies and language ideologies drive the development and deployment of NLP systems, and how these systems therefore reproduce these hierarchies and ideologies,” the paper reads. Yu said it’s also important to note that their NLP system is built upon “the most advanced deep learning technologies and therefore is more generalizable than most existing work that mainly used rule-based approaches or traditional machine learning for identifying social determinants of health.” Given the significant progress made in deep learning and the emergence of powerful language models such as BERT and GPT in recent years, our aim is to continue helping businesses in leveraging these advancements across diverse industries and languages worldwide.

If you have any complaints or copyright issues related to this article, kindly contact the author above. Explore the future of AI on August 5 in San Francisco—join Block, GSK, and SAP at Autonomous Workforces to discover how enterprises are scaling multi-agent systems with real-world results. Join leaders from Block, GSK, and SAP for an exclusive look at how autonomous agents are reshaping enterprise workflows – from real-time decision-making to end-to-end automation. SDOH, which include factors such as socioeconomic status, access to healthy food, education, housing and physical environment, are strong predictors of suicidal behaviors. If you don’t have a WatersTechnology account, please register for a trial.

Chatham House has released a collection of essays that examines innovative approaches to AI regulation and governance. It presents and evaluates proposals and mechanisms for ensuring responsible AI, from EU-style regulations to open-source governance, from treaties to CERN-like research facilities and publicly owned corporations. Drawing on perspectives from around the world, the collection underscores the need to protect openness, ensure inclusivity and fairness in AI, and establish clear ethical frameworks and lines of cooperation between states and technology companies. With a background in research, policy, business development, and operational management, Sean has worked with some of the largest and most successful public service providers globally. He has designed and managed large-scale public service contracts overseeing businesses with revenues exceeding $100 million and leading teams of over 900 employees. She holds over seven years of Government Affairs and Tech Policy experience in the US and UK.

With over 1,000 members (the majority of which are SMEs) across the UK, techUK creates a network for innovation and collaboration across business, government and stakeholders to provide a better future for people, society, the economy and the planet. By providing expertise and insight, we support our members, partners and stakeholders as they prepare the UK for what comes next in a constantly changing world. July 13, 2023 — In this retrospective, Lexalytics co-founder Jeff Catlin chronicles the company’s pioneering role in AI and NLP since 2003. Notable for commercializing sentiment analysis and syntax-focused machine learning, Lexalytics continues to impact diverse industries. Their recent acquisition by InMoment underscores their dedication to harnessing advances like BERT and GPT to enhance business strategies worldwide.

He leads techUK’s AI Adoption programme, supporting members of all sizes and sectors in adopting AI at scale. His work involves identifying barriers to adoption, exploring solutions, and helping to unlock AI’s transformative potential, particularly its benefits for people, the economy, society, and the planet. He is also committed to advancing the UK’s AI sector and ensuring the UK remains a global leader in AI by working closely with techUK members, the UK Government, regulators, and devolved and local authorities. World and Middle East business and financial news, Stocks, Currencies, Market Data, Research, Weather and other data. The NLP-extracted SDOH were social isolation, job or financial insecurity, housing instability, legal problems, violence, barriers to care, transition of care, and food insecurity.

Humans rely on experience, intuition, sensory cues and a vast array of other factors to interpret context. This limitation means they depend on precise and specific prompts to deliver accurate and relevant responses. In an accompanying editorial, Ishanu Chattopadhyay, PhD, with University of Chicago, Chicago, Illinois, says this suggests that unstructured clinical notes “may efficiently identify at-risk individuals even when structured data on the relevant variables are missing or incomplete.”