The Centre for Humans and Machines invites interested attendees to our public seminars, which feature scientists from our institute and experts from all over the world. Our seminars usually take 1 hour and provide an opportunity to meet the speaker afterwards.

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A Computational Approach to Understanding and Improving Decision-Making and Learning

Speaker: Falk Lieder, Max Planck Research Group Leader for Rationality Enhancement (MPI for Intelligent Systems)
Date: February 8, 2022 at 15:00 p.m. CET
Venue: web-based

Webex Access
Meeting number: 2744 311 8569
Password: yPEdYAdb732


Historically, many cognitive scientists have considered rational decision-making in complex real-world problems computationally intractable. Yet, in the real world, some people excel at it nonetheless. To resolve this apparent contradiction, I developed the computational modelling framework of resource-rational analysis. In this talk, I will summarize my research program on resource rationality, focusing on modelling and improving human decision-making. I will start by illustrating resource-rational analysis with computational models of human planning. We found that people use different adaptive planning strategies in different environments. The second part of my talk explores where those clever heuristics come from with computational models of metacognitive learning. In the third part of my talk, I will illustrate how combining my theory of resource rationality with my models of strategy discovery makes it possible to improve human decision-making with intelligent cognitive tutors.

Falk Lieder
Falk Lieder is a computational cognitive scientist who combines methods from psychology and artificial intelligence to understand and improve human decision-making and learning. He did his PhD. with Tom Griffiths at UC Berkeley. His dissertation “Beyond Bounded Rationality: Reverse-Engineering and Enhancing Human Intelligence" was awarded the Glushko dissertation award of the Cognitive Science Society. He was the lead organizer of the inaugural life improvement science conference and is currently a Max Planck Research Group Leader at the MPI for Intelligent Systems in Tübingen.

Artificial Intelligence in the Government: Responses to Failures and Social Impact

Speaker: Chiara Longoni, Questrom School of Business, Boston University
Date: February 22, 2022 at 15:00 p.m. CET
Venue: web-based


Artificial Intelligence (AI) is pervading the government and transforming how public services are provided to people—from allocation of government benefits and privileges to enforcement of law and regulatory mandates, monitoring of risks to public health and safety, and provision of services to the public. Unfortunately, despite technological improvements and betterments in performance, AI systems are fallible and may commit errors. How do people respond when learning of AI’s failures? In twelve preregistered studies (N = 3,026) across a range of policy areas and diverse samples, we document a robust effect of algorithmic transference: algorithmic failures are generalized more broadly than human failures. Rather than reflecting generalized algorithm aversion, algorithmic transference is rooted in social categorization: it stems from how people perceive a group of non-human agents versus a group of humans—as out-groups characterized by greater homogeneity than in-groups of comparable humans. Because AIs are perceived as more homogeneous than people, failure information about one algorithm has higher inductive potential and is transferred to another algorithm at a higher rate than failure information about a person is transferred to another person. Assessing AI’s impact on consumers and societies, we show how the premature or mismanaged deployment of faulty AI technologies may engender algorithmic transference and undermine the very institutions that AI systems are meant to modernize.

Chiara Longoni

Chiara is a behavioral scientist and Assistant Professor of Marketing at Boston University’s Questrom School of Business. Her research explores (i) the social impact of Artificial Intelligence and technology (ii) sustainability, (iii) consumer and societal welfare. Substantively, she specializes in issues related to medical decision making, sustainability in consumer and firm behavior, and messaging to promote consumer and societal well-being. Her work has been published, among others, in the Journal of Consumer Research, the Journal of Marketing Research, the Journal of Marketing, Nature Human Behavior, and Nature Communications. Her work has been featured in popular press outlets such as The Times,  Forbes, Fortune, and Harvard Business Review, in practitioner outlets such as Infermedica and Artificial Intelligence in Medicine, and podcasts such as Man & Machine and Dividing Into Data.
She teaches a semester-long course in Branding to undergraduate and MBA students, and an intensive course on the psychology of Artificial Intelligence to executives. Prior to joining Boston University, she completed a Ph.D. in marketing at New York University’s Stern School of Business. She also holds a M.S. (summa cum laude) from Bocconi University, a M.A. (Honors) in Psychology from New York University, and a M. Phil. in Marketing from New York University’s Stern School of Business. Before joining academia, she worked in strategic consulting and brand management.

Preferences in Human-Machine Interactions – The Impact of Personal Affectedness

Speaker: Anja Bodenschatz, TUM School of Social Sciences and Technology
Date: April 26, 2022 at 15:30 p.m. CET



Many autonomous systems promise major benefits for human safety, if deployed in a technologically sound manner. Still, many ethical questions arise around negative consequences these systems might entail for human welfare and how they should autonomously resolve the ethically relevant situations that they will encounter. In this talk, I will present empirical studies that show how preferences for the interaction and programming of autonomous systems change along people's affectedness with regard to the use or possible deployment of these systems. We will discuss how this affects the possibility of a societal contract on the ethical aspects of autonomous systems and what options result for programming ethical decisions.


Anja Bodenschatz
Anja Bodenschatz is a research associate at the Research Group “Ethics of Digitization”, which was instituted by the Bavarian Research Institute for Digital Transformation. Her main field of interest are ethical trade-offs and societal concerns that arise with new technologies. Methodologically a behavioral economist, she is a business scholar by training with a focus on business ethics and psychology. From this standpoint she aims to disentangle how situational, institutional and personal factors influence our moral intuitions and focuses on an empirically informed investigation of preferences in human-machine interactions.


Feb 15, 2022 at 10:00 a.m. CET: Meeyoung Cha, School of Computing, KAIST: tba (virtual)

Mar 01, 2022 at 15:00 p.m. CET: Christoph Niemann, Studio Christoph Niemann : Salon for Humans and Machines (hybrid)

Mar 22, 2022 at 15:00 p.m. CET: Julian de Freitas, Harvard Business School: tba (virtual)

Here you can find an overview of past seminars and events.





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