Author and Affiliation: Helena Moniz, University of Lisbon/INESC-ID
Title: Human Language Technologies in the era of Large Language Models (LLMs): Responsible Artificial Intelligence (AI) in research and product

Bio: Helena Moniz is the President of the European Association for Machine Translation (2021-) and President of the International Association for Machine Translation (2023-). She is also the Vice-Coordinator of the Human Language Technologies Lab at INESC-ID, Lisbon. Helena is an Assistant Professor at the School of Arts and Humanities at the University of Lisbon, where she teaches Computational Linguistics, Computer Assisted Translation, and Machine Translation Systems and Post-editing. She is the as Chair of the Ethics Committee of the Center for Responsible AI (https://centerforresponsible.ai), and the coordinator of the project Bridge AI (https://bridge-ai.eu).
Helena graduated in Modern Languages and Literature at the School of Arts and Humanities, University of Lisbon (FLUL), in 1998. She took a Teacher Training graduation course in 2000, a Master’s degree in Linguistics in 2007, and a PhD in Linguistics at FLUL in cooperation with the Technical University of Lisbon (IST) in 2013. She has been working at INESC-ID/CLUL since 2000, in several national and international projects involving multidisciplinary teams of linguists and speech processing engineers. Within these fruitful collaborations, she participated in more than 20 national and international projects.
From 2015/09 to 2024/04, she was the PI of a bilateral project between INESC-ID and Unbabel, a translation company combining AI + post-editing, working on scalable Linguistic Quality Assurance processes for crowdsourcing. She was responsible for the implementation on 2015 of the MQM metric, the creation of the Linguistic Quality Assurance processes developed at Unbabel for Linguistic Annotation and Editors' Evaluation. She also worked on research projects, involving Linguistics, Translation, and Responsible AI, and products developed by the Labs Team, mostly cultural transcreation, high risk products, and silently controlled language metrics for dialogues.
She is in an Editorial Board Member of the Journal of Natural Language Processing, Cambridge University Press, and Advisory Board of the New Research Methods in Translation and Interpreting Studies, Routledge.

Abstract: Since 2001, I entered INESC-ID as an annotator and I was far from knowing that working on DIXI+1 would make a drastic change in my professional options. I felt that I could apply my linguistic knowledge and see it being used in a synthesizer. This connection of knowledge and product will always be transversal in my path and will mark my research options along the way. In the presentation, building upon the research and teaching plan, I will show that Speech Processing (SP) and Natural Language Processing (NLP), more broadly, have changed drastically and the scenario is now even faster with Large Language Models (LLMs). I ended my Ph.D (2013) before the Neural Networks disruptive moment, but the sense of rapid change was there and now is very vivid and urges us as researchers to keep the pace. During all those stages, I had the opportunity of being in an environment and working along with colleagues that would become CTOs or CEOs of spin-offs of the lab. With them and in very cooperative projects, I had the opportunity of using my skills and willing to make it concrete to impact products and features in companies such as Defined.ai, ELSA, Unbabel and VoiceInteraction, even Baidu, but just in a very punctual cooperation for assessment of Baidu’s LLMs for text classification. The rapid landscape of changes in AI is promoted by new methods in machine learning, computational power, large corpora, industry players and is taking the world as spectators, who want to be involved, since AI impacts everyone’s life.
This rapid change faces several research and application challenges, which are the core of my research work. As a first entrance point and as a linguist, I am interested in knowing what the embeddings are capturing and how these really align with how humans process language. I am also very interested in understanding the limitations of AI systems and its disruptive impacts. Moreover, I am very involved in how to create awareness to different audiences, public administration, industry and civil society on Responsible AI initiatives and concrete actions, through two core projects: Center for Responsible AI and Bridge AI. The idea that products should be ethically designed in a human-centric approach can not be wishful thinking and innovation should be driven by moral conduct and ethical/legal frameworks, such as the AI4People. Only then will we be promoting true literacy on AI, both in research and innovation, that benefits society and we can then use “social impact” in a very proper way.
The need to create a course on Responsible AI is paramount these days, industry leaders, researchers and students are requiring these and training for such skills is core. It is thus very relevant that the two HORIZON-MSCA proposals that I am involved in are very focused on training holistic and multidisciplinary skills to students in Europe tackling Responsible AI, either assessing existing algorithms, creating new ones, or even developing algorithms on bias mitigation for instance.
Although not an IST teacher, I have the pleasure of working and cosupervising MSc. and Ph.D theses with INESC-ID colleagues on SP and NLP. It is quite clear to me that there are several challenges and research paths needed to really speak of a human-centric approach, without that being just keywords in conference calls or marketing strategies for products.
Based on the research and teaching plan, this presentation will be a helicopter view of how Responsible AI can be applied to human language technologies and how to create virtuous cycles with industry to accomplish that. The core of my statement will be that new skills are needed to face the changes and anticipate research paths. IST aligned with INESC-ID has a word to say on this topic, not only in a national panorama, but also worldwide. The proposal could be applied to both master and doctoral courses, obviously adapting and leveraging to the development of the students of such distinctive courses.

---

Author and Affiliation: David Obershaw, Stanford University, Department of Electrical Engineering
Title: From Lab to Market: Fostering Economic Growth Via Technology Transfer

Bio: David Obershaw is an Adjunct Lecturer at Stanford University in the Department of Electrical Engineering. Starting in 2008, he initiated and taught Stanford's Insanely Great Products seminar. In 2019, the Stanford Tau Beta Pi Engineering Honor Society named David to their teaching Honor Roll. Previously, David was Vice President of Business Development for Proofpoint, a leading enterprise email security and data loss prevention company.

He also worked for PeopleSoft (now part of Oracle) in various roles, including Vice President of Marketing and Merchant Sales for PeopleSoft’s eBusiness Division and Vice President of Marketing and Industry Strategy for PeopleSoft’s Products Division. He came to PeopleSoft via its acquisition of Red Pepper Software in 1996, where he served as Director of Marketing and Business Development.

David also served as Director of Product and Federal Marketing for MasPar Computer Corporation and held various product management positions within the Hewlett-Packard Company. He initiated his career in field sales with IBM Corporation. In the non-profit world, David has served on the Board of Trustees for the El Camino YMCA in Mountain View and served as President of the Board of Trustees at Charles Armstrong School in Belmont, CA – a specialty school serving grades 2-8 students with language-based learning differences such as dyslexia. 

David is dyslexic and is happy to share the associated challenges and benefits. He earned his MBA degree from Stanford Graduate School of Business and BA degrees from UCLA.

Abstract:  This talk will highlight Stanford’s history in fostering partnerships with industry and encouraging students to become entrepreneurs.

_{(AI generated image)}