Bio:

Saeed Amidi is a seasoned investor and executive with over 30 years of experience growing businesses in numerous industries, including real estate, bottled water, packaging, and technology investing. Following the early success of his various businesses, The Amidi Group initially purchased a building in Palo Alto, deemed the “Lucky Building,” and decided to rent the extra office spaces to startups including Google, Logitech, PayPal, and Danger.

As the CEO and founder of Plug and Play, Saeed applies his passion for the tech industry daily by working with forward-thinking partners and the best global startups to facilitate positive change worldwide. Since Plug and Play’s launch in 2006, the company has worked with over 50,000 startups, made over 1,500 investments, and boasts over 30 unicorns including Dropbox, PayPal, Lending Club, N26, and Honey.

In the midst of all his entrepreneurial pursuits, Saeed never lost sight of what matters most: family. He has encouraged the importance of building strong relationships both personally and professionally. His contributions to the technology industry and charitable efforts supporting disruptive startups have made him a notable professional in many circles.

Key topics addressed:

Title:

It takes two to thinklet: adapting collaboration engineering for human-AI partnerships

Description:

The emergence of sophisticated generative AI has fundamentally transformed the landscape of collaborative work. No longer confined to the role of passive tools, modern AI systems now function as autonomous agents capable of meaningful participation in teamwork. From co-authoring documents to contributing creative ideas and making decisions, these AI systems are increasingly becoming active teammates in collaborative scenarios. This evolution signals a shift from AI as productivity software to AI as collaborative partners with unique capabilities to augment collaborative work.

For over two decades, the field of Collaboration Engineering has developed rigorous approaches to designing and deploying repeatable collaboration processes for high-value organizational tasks. Collaboration Engineering has introduced the concept of "thinkLets" – modular, reusable building blocks that encapsulate facilitation expertise and enable predictable patterns of collaboration. Through careful sequencing of thinkLets, organizations can create sustainable collaborative work practices that deliver consistent value without requiring professional facilitators.

However, the existing Collaboration Engineering approach and concepts were conceived exclusively for human teams. Its foundational assumptions, design methodologies, and implementation approaches were developed with human cognitive capabilities, social dynamics, and communication practices in mind. The theories, models, and practices that have proven effective for human collaboration are not necessarily directly applicable to teams where one or more members is an AI. The asymmetric capabilities between human and AI participants, unique interaction challenges, and novel team dynamics create a fundamentally different collaborative environment requiring rethinking of our established approaches to design collaboration processes and techniques.
This keynote addresses the critical question: How must Collaboration Engineering evolve to accommodate and leverage AI teammates in collaborative processes? What adaptations to its core concepts, design methodologies, and implementation strategies are necessary to create effective, sustainable Human-AI collaboration processes?

Drawing on insights from both Collaboration Engineering research and recent advances in AI capabilities, I will present several key adaptations required for this new frontier. These include modifications to the thinkLet concept to accommodate AI-specific roles and interaction patterns, extensions to process design methodologies that account for AI capabilities and limitations, and new approaches to facilitate knowledge transfer to practitioners leading Human-AI teams. Additionally, I will outline a research agenda organized around the Ways Framework (Thinking, Working, Modeling, Supporting, and Controlling) to guide future investigation in this emerging field. This agenda identifies research questions whose answers will help organizations successfully integrate AI teammates into their collaborative work practices.

As AI continues to evolve from tools to powerful teammates, Collaboration Engineering must similarly evolve to provide theoretically-grounded, practically-applicable approaches to designing effective hybrid collaborative processes. This presentation aims to lay the foundation for this essential adaptation, ensuring that the valuable insights from decades of collaboration research can be effectively applied to our new reality of Human-AI teamwork.

Bio:

GJ de Vreede is Dean of the School of Business at Stevens Institute of Technology. Previously he served as Associate Dean and Interim Dean at the Muma College of Business of the University of South Florida and as Director of the Center for Collaboration Science at the University of Nebraska at Omaha. He received his PhD in Information Systems from Delft University of Technology, the Netherlands. He has been a visiting professor at Renmin University (China), the University of International Business & Economics (China), the University of Arizona, and the University of Pretoria (South Africa). He has worked as an international consultant in the area of collaboration technology & practice for over 30 years.

His research focuses on AI in teams, crowdsourcing, and Collaboration Engineering. He was the co-founder of the Collaboration Engineering research field and co-inventor of the thinkLet concept. His research has appeared in journals such as Information Systems Research, Journal of Management Information Systems, Journal of the Association for Information Systems, Information & Management, Management Information Systems Quarterly Executive, Small Group Research, and Communications of the ACM. He has extensive experience as a trainer, speaker, and consultant on the design and implementation of collaborative practices in a variety of business domains, focusing on areas such as strategy development, process engineering, crowdsourcing, risk management, Agile design & development, and product development.

Title:

Statistical network analysis: challenges and opportunities

Description:

Network data are found everywhere. A network can be conveniently thought of as a collection of nodes connected by edges. A node could be, for example, a business, an industry or even a country. And an edge could represent any relationship between any two nodes, for example, the amount of trade which flows from one business to another. Analysing and understanding the complex patterns that can arise in networks presents both a challenge, but also an opportunity togain insights, otherwise undiscovered. I will aim to highlight these aspects through a collection of diverse case studies.

Bio:

Nial Friel is a Professor of Statistics at University College Dublin (UCD) and currently serves as the Head of the School of Mathematics and Statistics at UCD. He has been at the forefront of research in Bayesian statistics, computation, and network analysis. His recent work focuses on developing dynamic models for predicting football outcomes. His research interests include intractable likelihoods, Bayesian inference for statistical network models, model selection, and Markov chain Monte Carlo methods. His work has been widely recognized, with recent contributions to understanding the competitiveness of the English Premier League and the role of superspreading in COVID-19 transmission. He has delivered keynote presentations and invited talks at international conferences, including the Royal Statistical Society Annual Conference, ISBA, and the Bayesian Methods for the Social Sciences workshop. His professional contributions include serving as Joint Editor of the Journal of the Royal Statistical Society, Series C, a member of the ISBA Board of Directors, and an associate editor for Statistics and Computing. He was also an elected member of the European Regional Committee of the Bernoulli Society.

Title:

Dealing with powerful, rapid technological transformation: shaping a new era for business schools and industry partnerships

Description:

AI is the latest and most powerful technological transformation wave upon us causing profound impact on every sector of the economy and society. Reflecting on preceding technology waves, and using information systems principles as analytical lens, we describe their impact on business education and industry connectivity. Tighter industry-university relationships are absolutely necessary moving forward.

Bio:

Paulo Goes is the Dean of the Freeman School of Business at Tulane University. He is positioning the school as a transformation engine for students and the New Orleans / Gulf South region, embracing experiential learning and industry connectivity as defining components of the future of business education. He was previously at the University of Arizona, where he served nearly eight years as Head of Management Information Systems and close to six years as Dean and Halle Chair in Leadership. He received his Ph.D. in Business Administration from the University of Rochester and spent the first part of his academic career at the University of Connecticut.

Dr. Goes served as the Editor-in-Chief of Management Information Systems Quarterly during 2013-2015. He also served as Senior Editor or associate editor of several top tier journals in information systems and business. He has published extensively in the top journals of the field. He has been recognized as a fellow of both the Association for Information Systems and the INFORMS Information Systems Society. In 2022 he received the Presidential Award for Lifelong Service from the INFORMS Information Systems Society.

Title:

Rethinking AI and its impact on Business and Humanity

Description:

Working in academia, the public and private sectors, Daniel is a globally recognised expert in Artificial Intelligence as well as its applications and the social, commercial, economic and ethical implications. In a world where many believe access to more and more data will lead to ever better decision-making, he looks at what AI really is, as well as identifying the current and future challenges and opportunities for emerging technologies. Daniel provides a radical new framework for thinking about AI, and discusses how organisations can practically adopt these technologies and avoid being seduced by the hype. He argues that whilst these technologies are incredible at creating growth and streamlining operations, for companies to stay innovative they need to also use AI to unlock the creative capacity of their workforce. Daniel also covers the macro impact these technologies may have on business and humanity over the coming decades.

Bio:

Dr. Daniel Hulme is a globally recognised expert in Artificial Intelligence (AI) and investor in emerging technologies. He's the CEO of Satalia, an award-winning AI company that was acquired by the world's largest marketing company in 2021, WPP, where he is now the Chief AI Officer. Daniel has been recognised as one of the world's leading keynote speakers as well as one of the top ten Chief AI Officers globally. Amongst his many technology investments, Daniel is also Founder and CEO of the World's first commercial research organisation to understand Machine Consciousness, Conscium.

With over 25 years academic experience with AI, Daniel received his Masters and Doctorate in AI at UCL. He was previously Director of UCL’s Applied AI Masters Programme, where he is now UCL’s Computer Science Entrepreneur-in-Residence. Daniel is also an Impact Board Member of St Andrew’s University Computer Science department, focused on using AI to solve business and social problems

Passionate about how technology can be used to govern organisations and bring positive social impact, Daniel is a prolific keynote speaker for the world's largest technology companies, TEDx, and is faculty member of Singularity University, specialising in AI, ethics, innovation and organisational design. Daniel is a contributor to numerous books, podcasts and articles on AI. His mission is to create a world where everyone has the freedom to innovate, and have those innovations become free to everyone. He has advisory and executive positions across companies and governments, and actively promotes purposeful entrepreneurship across the globe.

Key topics addressed:

• There's much misunderstanding about AI. What is AI?
• Is AI a buzzword, or is it here to stay? And why?
• What are the possible and actual uses of AI?
• What are the different kinds of AI, and their strengths and weaknesses?
• What are the biggest mistakes you see companies and governments making when approaching using AI?
• How to identify and prioritise AI opportunities?
• How can AI and people work together most effectively?
• How will Generative AI technologies impact business and society?
• What will be the long term impact of AI on society?
• What are the main safety and ethical concerns/considerations with respect to AI? 
• What regulations do organisations need to be aware of?

Title:

Rethinking AI and its impact on Business and Humanity

Description:

Research on the organizational implications of AI is commonly framed in terms of the specific character of AI applications and the tasks such applications are brought to bear upon. Medical diagnoses, hiring or investment decisions, industrial engineering, language translation and content creation, autonomous driving, authentication through voice or face recognition represent typical examples. Important as it may be, such an understanding of AI ends up with a scattered list of possible AI interventions that fail to capture the core of ongoing changes and the distinct patterns by which AI reweaves the fabric of knowledge making and organizing. In my talk, I single out essential behavioural modalities through which social agents enact and shape organizational operations and map the likely e ects of AI on perception (e.g. object recognition), interactive cognition (e.g. natural language processing and LLMs) and action (e.g. robotics). The objective is to outline the larger picture and spell out the key premises by which AI is involved in the exercise of expertise and the making of organizations.

Bio:

Jannis Kallinikos is professor of Organization Studies at Luiss University, Rome, Italy where he holds the Cisco Chair on Digital Transformation and Data-Driven Innovation and professor emeritus at the Department of Management, London School of Economics. His research focuses on the impact of data and digital technologies on organizations, economic institutions and practices. He has published widely in Management, Information Systems and Sociology journals and written several monographs including the recent Data Rules: Reinventing the Market Economy, The MIT Press, 2024 (co-authored with Cristina Alaimo). Prof Kallinikos is advisor of the Royal Swedish Academy of Sciences for the nomination of Nobel Prize candidates in Economics.