Alix Rübsaam

Location
The Netherlands
Areas of Expertise
Artificial Intelligence
Ethics
Exponential Thinking

Expert Bio

Alix Rübsaam is a philosopher of technology and cultural analyst specializing in the societal and cultural impact of exponential technologies, with a focus on Artificial Intelligence, autonomous robotics, information technologies, and digital environments. She currently serves as Vice President of Research, Expertise and Knowledge at Singularity University, where she oversees the organization's research efforts, body of knowledge, and global community of experts. Alix leads two major research initiatives: one centered on responsible AI, algorithmic bias, and exclusion — empowering leaders to design equitable, fair, and just AI systems — and another examining the digitalization of information, its effects on decision-making, and 21st-century ethics. Prior to joining Singularity University, she pursued her PhD at the University of Amsterdam and the Amsterdam School for Cultural Analysis (ASCA), where she researched human-nonhuman collaboration at the intersection of humans and computational systems. A sought-after speaker and writer, Alix has contributed thought leadership on topics ranging from AI bias and autonomous weapon systems to embodied robotics, cyberpunk literature, and science fiction, making her a leading voice in the responsible and thoughtful deployment of emerging technologies.

Sessions

AI, Unintended Outcomes & The Opportunities of Responsible Technologies

Responsible AI Workshop

This immersive and hands-on simulation exercise goes through the steps of designing and training an AI. Participants learn how decisions made in the design phase influence the workings and outcomes of the algorithms built during the simulation. They learn how to identify and analyze the mechanisms that lead to unwanted and unintended outcomes in AI, as well as how to advocate for and build more socially responsible algorithms. No formal training needed to participate.

During the workshop, participants will make decisions about the training and designing of algorithms in a simulation of real world implementation of technologies across industries. Shortening the distance between design, implementation, and outcomes, increases understanding of how our cultural background and assumptions become programmed into data-driven technologies.

Then, participants will learn to identify opportunities for responsible AI; pinpoint potential pitfalls for algorithmic bias; and learn to assess the risks for unintended outcomes. During the simulation, they will also become familiar with the design, implementation, and use of automated decision-making algorithms and Machine Learning systems.

AI or Die? Redefining the Human in the Digital Age

AI as an existential risk for humanity has become a mainstay in news headlines. While some predict that the rise of Artificial Intelligence will mean the "end of humankind", others see no future without algorithms and data-driven systems. What sense can we make from these predictions and warnings? This talk unpacks the effects of thinking about our brain as a computer and what the impact of this thinking has on how we leverage a technology like AI. Our current "computational" way of thinking has major impact on our culture and our sense of self. At a macro level, software has come to function as a metaphor for humanity as a whole. We will investigate what it means to be human in the digital age, and challenge our understanding of Artificial Intelligence as a threat to humanity.

Critical Thinking & Decision Making

This module on critical thinking and decision making in the age of exponential technologies consists of three parts.

The first part on information is designed to help participants navigate an environment with abundant information. Converging exponential technologies have radically changed our relation to information. As available insights continue to increase and data-processing technologies become ever cheaper, we need a new skill set to make sense of this abundance of information. We explore the shift in how we build knowledge, and the skills we need to address this shift.

Part two dives into the computational perspective with which we engage with our surroundings. As computers and information-processing technologies continue to influence ever more aspects of our life, it is difficult to think outside of the data-driven lens through which we understand the world around us. We explore the entanglement of our culture and our digital technologies, discuss the risks and limitations of computational thinking, and offer skills to disrupt these risks.

Weaving these threads together in part three, we now find ourselves in a time and space where each of us have the tools and the information available to us to be critical decision makers. Participants are empowered to utilize the tools they now have available to tackle decisions they face individually, as a leader, and as part of a company, while avoiding the pitfalls of computational reasoning.

Three separate parts can be delivered as standalone sessions as well.

Leveraging Exponential Technologies for Positive Impact

The ongoing democratization of exponential technologies means that more and more people play a role in deciding how we use these technologies, and to what end. This shift brings new opportunities to address global challenges. With the increase in agency and ability that exponential technology offers us, we have to consider how we innovate thoughtfully and responsibly.

In this session we'll explore applying exponential technologies towards some of the most pressing problems of our time. Singularity's Global Grand Challenges offer the lens with which we approach these new applications. This session covers how technologies are empowering leaders to create positive impact in their communities and their businesses.

Participants will gain understanding in how the convergence of technologies and industries creates new opportunities for positive impact; how technological advancement can allow solutions to leapfrog traditional development; and how they can leverage these insights in their own business.

AI Simulation Workshop

Aligning Intention with Implementation and Outcomes

This immersive and hands-on simulation exercise mirrors real-world implementation of AI technologies. It guides participants through the steps of designing and training AI so that they experience firsthand how each decision influences the workings and outcomes of what they built. They learn how to identify these mechanisms and analyze if and how they led to unwanted and unintended outcomes. Moving beyond theoretical concepts of (technical) bias and explainability, this session provides concrete tools for diagnosis, mitigation, and leadership in responsible AI.

Participants will better understand the role of human decision-making in AI systems (from rule-based automations to Generative and Agentic systems). They will be able to position explainability as a component of their leadership, and to gauge whether priorities and outcomes are aligned. And they will learn how specificity and awareness about weights, blind spots, goals, and parameter limits can be their competitive edge in product development and responsible deployment.

AI, Unintended Outcomes & The Opportunities of Responsible Technologies

When it comes to automating decision making with AI, unintended outcomes can become hard-coded into data-driven technologies, despite our intentions. Applications abound: from hiring to manufacturing optimization, from supply chain management to recommendation algorithms. But all AI applications are at risk of perpetuating, and augmenting blind spots into their models. These blind spots are not just a risk for unfairness, they can affect your bottom line, or leave your systems exposed to regulatory implications. The more you understand the inner structure of your AI systems and algorithms, the better equipped you are to leverage these insights to your advantage.

This talk unpacks the workings of the design and decision making that goes into algorithmic systems, how to identify and analyze the mechanisms in AI and how to ensure those are aligned with your goals. Additionally, in this session we will dive into the limitations and possibilities of leveraging data driven technologies, and how to be a leader in the emerging space. Participants will learn to identify different kinds of algorithms; will be able to identify opportunities for responsible AI; and will learn to assess an automated decision making system on its risk for unintended consequences.

Decision-Making AI: Repositioning Human Decisions

This session provides a foundational overview of AI systems used in decision-making roles. It moves beyond the technological surface to explore the critical human choices embedded within every stage of an AI system, from design and data labeling to model deployment. The session outlines various AI model types (from Rule-Based systems to Generative AI and Agentic AI) by framing them all within the shared Input-Rules/Weights-Outcome/Decision paradigm. A core theme is preparing leaders to answer critical questions about outsourcing, accountability, and governance by emphasizing that AI is never neutral and always reflects human values and decisions.

Learning Outcomes:

Identify the key questions and governance considerations for deploying AI systems in decision-making roles.
Differentiate between major Decision-Making AI models, including Rule-Based systems, Supervised/Unsupervised Machine Learning, Reinforcement Learning, Generative AI (including RLHF and RAG), and Agentic AI.
Explain how all AI models fundamentally operate within the Input, Rules/Weights, and Outcome/Decision framework.
Recognize and articulate the numerous human decisions—in goal setting, data preparation, and model design—that influence the outcome and values expressed by any AI system.
Understand that AI is not "neutral" or "value agnostic," and that focusing on the problem rather than just the technology is crucial for effective implementation

(Responsible) AI for Industry: Opportunities and Strategies

This session offers practical recommendations for organizations to gain a competitive advantage in their AI strategy. It addresses the current environment of low public trust and implementation friction by outlining strategic opportunities for AI adoption. Participants will explore four key frameworks for implementing and activating AI practices that are tailored to their specific industry, organizational readiness, and challenges.

Learning Outcomes:

Sovereign and Relevant: Identify unique data and model resources within their organization or industry to build a roadmap for increasing system sovereignty and autonomy.
Specific and Intentional: Develop measures for selecting the right AI models and empower teams to use analytical tools, like SHAP, to understand algorithm outcomes and ensure alignment with goals.
Explicit and Transparent: Understand how to leverage transparency as a competitive advantage by identifying opportunities for communication and reassessing relevant biases for different markets.
Human Centric: Determine the "right humans" (employees, users, stakeholders) to include in the decision-making loop and develop a clear company/brand stance on AI use that positions them as a leader in the field.

Leveraging Exponential Technologies for Positive Impact

In this session we’ll explore applying exponential technologies towards some of the most pressing problems of our time. Singularity’s Global Grand Challenges offer the lens with which we approach these new applications. This session covers how technologies are empowering leaders to create positive impact in their communities and their businesses.

Expert Bio

Sessions

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