About me

My research interests revolve around political decision making and the practical conditions for informed and rational public debate.During my bachelor studies at the University of Bergen I focused on questions in political theory. In my bachelor thesis I wrote about John Rawls' political liberalism and the radical democratic theory of Jürgen Habermas. My master thesis defends a theory of practical rationality, and argues that there are rational answers to value questions.After completing my master thesis I studied social science and computational linguistics at the University of Oslo. I In 2020 I co-founded a startup to develop AI-based technology for deliberate practice and formative assessments with support from the Norwegian Research Council. Here is a review I did of the research base underlying this idea. We are currently exploring the accuracy of AI-generated feedback on practice assignments in law and critical thinking (ex phil). Additionally, we are interested ways to improve reasoning and decision making using formal ontologies and Bayesian networks. I recently wrote about this in a submission to an essay competition here.The main objective of my PhD research project is to identify the conditions for a valid and legitimate public evaluative framework for appraisal of policy and social progress. My hypothesis is that the best method for satisfying those conditions is to develop a national welfare index that is based on research into well-being and the values of citizens. A secondary objective of the project is to uncover the conceptual and causal structure of well-being. My hypothesis is that objective features of a person can explain what it means for that person to have positive experiences and values that are suitable for her. With Aksel Braanen Sterri and the Center for Long-term Policy I've written a policy note to the Norwegian government strategy for using quality of life in policy development.In 2024 a team of researchers and I received a grant to launch a political forecasting tournament that investigates the link between predictive accuracy and political decision making. In this experimental research project we test whether research-based methods for improving foresight can be easily learned and applied without extensive training and effort.I spend most of my time doing research or working on projects. However, I also enjoy trail running, skiing and curating spotify playlists. You may review some of my playlists under the 'other' section, or have a more thorough look at my projects in the 'research' section.

• Research
• Other

Public Models of Welfare: Legitimation and Validation of National Composite Welfare Indices

Spurred by compelling reasons to find an alternative to GDP and related preference satisfaction models of welfare for policy appraisal, many countries are now measuring quality of life based on a large number of indicators tracking both subjective and objective factors. A question now facing these countries is how, if at all, the data can be used for evaluative purposes so as to inform policy making. This paper argues that a legible and consistent assessment of policy and social progress presupposes aggregation of data into a stable composite index according to which interpersonal benefits can be compared. In this view, methods of aggregation should be informed and vindicated by public models of well-being that distinguish between the causes, correlations and constituents of welfare in a way so that the constituents of welfare resonates with citizens, and the causes of well-being is informed by scientific evidence. However, citizens and researchers alike disagree about the meaning of well-being. This fact is the premise to an important objection claiming that policy appraisal based on any model of well-being is illegitimate because it neglects the interests of citizens who have other conceptions of well-being and the good life. I defend a specific version of the value-alignment approach to the development of public models of welfare that may inform development of composite welfare indices against this and other objections. In the process of providing a defence, I articulate a view about how to evaluate the theoretical validity of public welfare models and the political legitimacy of using them to construct legible unidimensional evaluative metrics for political decision-making. My conclusion is that there is a limited role for strong policy guidance in the form of comparative unidimensional appraisals, given that the values incorporated in public evaluative frameworks are properly aligned with the values of citizens.

Eudaimonism and its Rivals: An Extended Argument for Nature Fulfillment Theories of Well-being

In this paper I present an extended argument in support of eudaimonic (functional) explanations of well-being. The argument seeks to demonstrate that rival theories, including theories that explain well-being in terms of evaluation (life satisfaction & informed desire satisfaction) and affect (phenomenal hedonism & attitudinal hedonism), either contradict our considered convictions regarding the meaning of well-being or are indeterminate. I argue that plausible versions of each theory can be made determinate if grounded in functional facts of the well-being subject. The conclusion of the argument is that functional integration in a sense inspired by the philosophy of Plato and Aristotle can accommodate the core attractions of both subjective and hedonic theories and that an eudaimonist nature-fulfillment theory of this sort best explains the nature and meaning of well-being.

• Draft of the paper

Towards a Functional Theory of Health: Modelling the Normative Significance of Functional Traits

This essay presents and defends a functional theory of health in which the degree to which some person is healthy is determined on the basis of medical facts regarding the expected causal effects of her present health condition on natural functions in her body over time. This is modeled as a causal graph representing levels of function in the interrelated traits, faculties and organ systems of the human body and mind. Parameters of the model grounds a quantitative account of health informed by clinical research. This theory of health can inform naturalistic theories of medical disorder, as well as the development of health metrics for prioritisation.

• Draft of the paper

Scientific Eudaimonism: Naturalistic Reconstruction of the Aristotelian Conception of Well-being

In this paper, I develop and defend an naturalistic theory of well-being along the lines suggested by Aristotle. According to this idea, the conceptual structure of well-being track patterns of natural normativity that permeate the domain of life along the functional joints of nature. In one interpretation of the idea, it is intrinsically good for living beings to flourish in the sense of fulfilling and integrating their nature throughout life. Due to a number of concerns, contemporary proponents of the idea reject naturalistic interpretations of it. The chief concern is that a theory of well-being grounded in natural kind properties postulated by empirical sciences is likely to contradict our considered convictions regarding the meaning of well-being. In this article, I consider three influential forms of argument based on that concern. Through engagement with these arguments, I develop a scientific sort of Aristotelian naturalism that is compatible with a modern scientific worldview, and consistent with the premises to the most important objections to it. My conclusion is that the Aristotelian approach to ground well-being in nature has a lot of unexplored potential, and is a live alternative to subjective explanatory theories of well-being.

• Paper draft
• Presentation

Forecasting Tournament to Identify Costs and Benefits of Epistemic Methods to Forecasting and Decision-making

We believe that the unclear costs and benefits of using epistemic methods are key barriers to their adoption. To alleviate this knowledge gap, we want to run an empirical study to investigate the following hypotheses: Epistemic interventions informed by research can significantly improve the in-group comprehension of expert advice committees (H1), transparency of their recommendations (H2), and the accuracy of the predictions on which those recommendations are based (H3), without incurring significant time-costs (H4).To test these hypotheses we are going to run a novel pre-post experimental tournament design which we call Tandem Tournament. In this design, we recruit participants to take part in a forecasting tournament where the prize is 15,000 NOK to the team who can give the most accurate predictions on 50 forecasting questions given over 5 months. Participants can register to join the tournament as a group, or alone, in which case they will be assigned to groups.However, and here is the innovation, all groups are further divided into two groups, a control and an experimental condition, where the winner of both is eligible to win the prize. This ensures that we can control for confounders while still motivating participants. We select questions that are likely to be interesting to participants and make a small lottery with a prize pool of 10,000 NOK that is eligible for participants who complete all tasks.

• Presentation
• Project Description

Two Directions for Research on Forecasting and Decision-making

In this paper I review findings from forecasting tournaments and some other relevant studies. In light of this research, I identify a set of methods that can be used to improve the accuracy of individuals, teams, or organisations. I then note some limitations of our knowledge of methods for good judgement and identify two obstacles to the wide adoption of these methods to practical decision-making. The two obstacles have to do with costs and relevance.I also review projects and initiatives to overcome the obstacles, and note two directions for research on forecasting and decision-making that seem particularly promising to me. They have to do with expected value assessments and quantitative models of relevance and reasoning in the form of bayesian networks.

• Forum post

The Web of Belief: How Technology Can Automate Belief Formation Processes and Support Wise Decision-Making

In this essay, I present a method for using technological innovations to improve rational belief formation and wise decision-making in an explainable manner. I assume a view of rationality in which beliefs are evaluated according to norms of intelligibility, accuracy and consistency. These norms can be quantified in terms of logical relations between beliefs. I argue that Bayesian networks are ideal tools for representing beliefs and their logical interconnections, facilitating belief evaluation and revision. Bayesian networks can be daunting for beginners, but new methods and technologies have the potential to make their application feasible for non-experts. AI technologies, in particular, have the potential to support or automate several steps in the construction and updating of Bayesian networks for reasoning in an explainable way. One of these steps consists of relating empirical evidence to theoretical and decision-relevant propositions. The result of using these methods and technologies would be an AI-powered inference engine we can query to see the rational support, empirical or otherwise, of key premises to arguments that bear on important practical decisions. With these technological innovations, decision support systems based on Bayesian networks may represent belief structures and improve our understanding, judgement, and decision-making.

• Paper

Deliberate Practice with Rapid Formative Assessment

In 2020, Anders Evensen, Andreas Netteland and I initiated an innovation project with the support of the Norwegian Research Council, Innovation Norway, and Design and Architecture Norway. We have now developed a platform for making and doing practice assignments with automatic assessment and feedback in qualitative subjects like those of social science and the humanities.Research shows that practice and feedback is important to learning, so we think that there should be more practice and feedback in qualitative subjects. Multiple choice assignments are shallow and ineffective. The alternative, essay assignments, are labour-intensive to grade, so that is not a viable alternative for most teachers.With creative thinking and the application of recent innovations in the field of AI called natural language processing (NLP), Anders, Andreas and I found a way to automate assessment and feedback for practice assignments in text-based subjects. Using this technology, we facilitate for deliberate practice with rapid formative assessment in qualitative subjects, while collecting anonymised data for learning analytics and NLP research.

• Website
• Article

Here are some of my spotify playlists.The Jungle
Space Odyssey
Strong Feelings, Groovy Rhythms
Into the Forest
Temperate Tunes
Lun Nordisk Disko
Paal's juleliste
Drømmen
Oslosommer
Under vann

Here is a link to a document with some useful links for doing research in philosophy:Resources for Philosophy Research