TIK9025 – Innovation, Welfare and Policy
Course content
Innovation, welfare and policy: The case of automation and AI technologies
The field of innovation studies is typically based on the assumption that innovation is good for the economy, and that more innovations will lead to a wealthier and more sustainable economy and society. Since the 1980s, the underlying idea that has motivated the field is that innovation leads to positive economic effects, such as economic growth and employment creation, and does for this reason foster individuals’ welfare by leading to greater wealth. Innovation research has in fact almost exclusively focused on the positive economic effects of new technologies, and how these contribute to solve grand societal challenges, e.g. by spurring firms’ productivity, industries’ international competitiveness and sustainability transition, and the dynamics and performance of national systems. Relatedly, this research has also represented the foundation for R&D and innovation policies, whose underlying rationale has so far predominantly been to foster the creation and diffusion of innovations. More recent approaches, such as systemic and third generation mission-oriented innovation policy, are also implicitly based on the belief that innovations have the ability to address and solve grand societal challenges.
In spite of the importance and large consensus around the important positive effects of innovation, it is also worthwhile to consider that innovations can sometimes have unintended and negative consequences. The history of capitalism is full of examples of innovations that have led to damaging effects on individuals, social groups, and/or the natural environment. In general terms, it is most often the case that innovations and the process of "creative destruction" lead to positive effects for some and negative effects for others, although research has so far mostly focused on the former and often neglected the latter. Investigating the dark sides of innovation means to study its unintended and negative consequences, alongside its positive effects. In short, extant innovation research has adopted a narrow definition of social welfare, which focuses on positive economic performance and material well-being, and that mostly disregards the corresponding destruction effects, and therefore also distributional impacts of innovation.
This calls for new theoretical and empirical research in innovation studies, taking into account both positive and negative socio-economic effects of innovation, its bright and dark sides, and developing new conceptual and methodological tools to study, compare and assess multidimensional and contrasting effects of innovations in a broader interdisciplinary framework. This new departure will entail an in-depth discussion of how to value the societal effects of innovation, how to measure them, and how to assess their benefits and costs according to different ethical norms and theories of social justice. This is where innovation studies must cross-fertilize with, and draw inspiration from, other fields of research in which the social value of economic actions is explicitly investigated by means of social choice theories. Specifically, the course will provide insights from well-being studies and welfare economics, and show how these fields can enrich our understanding of the effects of innovation on social welfare.
The first part of this course will discuss the notion of individual well-being, and how different types of innovation affect this. The discussion will adopt a broad notion of agents’ well-being that comprises also non-economic factors and capabilities alongside income and material wealth. The second part of the course will shift the focus to the notion of aggregate social welfare, present different theories of social justice, and discuss how to take into account the distributional impacts of technological progress. This part will show that the impacts of innovation are characterized by complex trade-offs between efficiency and equity, both in the short- and in the long-run, which are often neglected in extant research. The third part of the course will analyze the implications of these for the rationale and foundations of R&D and innovation policy. Since innovations have complex and multi-dimensional effects - positive and negative; economic and non-economic - how can policy-makers assess and define whether a given innovation should be given public support, or instead regulated and limited? The multi-dimensional and complex nature of innovation presents policy-makers with a variety of trade-offs and complex choice sets, which call for the development of new tools of social choice analysis.
Although the theme of the course is potentially relevant for a broad variety of different types of innovations, the course will specifically focus on, and discuss examples about, automation and artificial intelligence technologies. These rapidly diffusing innovations have the potential to bring positive as well as negative impacts, and they therefore represent a relevant illustration of the conceptual perspectives presented in the course.
Learning outcome
The participants will be presented with the positive bias in innovation studies, discuss relevant illustrations of the dark sides of innovation, and reflect upon how these contrasting effects may be combined together into a comprehensive and interdisciplinary research framework. The participants will also be encouraged to reflect upon the implications and challenges for R & D and innovation policy.
Admission to the course
The course is for PhD students. Other participants (who are not PhD students) may be allowed to attend the course.
Application documents:
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A short outline of your PhD project
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For candidates outside TIK: A letter of confirmation regarding candidacy within a PhD program.
Please note that the course might be cancelled or postponed if there are less than ten participants.
Teaching
The course will be structured around academic presentations of some core themes provided by international guest scholars with specific expertise on innovation and welfare.
The participants will also be asked to identify, analyze and present to the other participants a few selected cases and concrete examples of impacts of innovation on welfare. Overall, the intention is that the course will foster PhD students’ ability to critically assess multiple impacts of innovation, and use these critical insights in their own PhD work.
A reading list will be made available to the participants.
All students will be expected to read the course literature before attending. They will also be required to participate actively in discussions and group work.
A zoom link for digital participation will be made available to participants prior to the course.
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Dates: see schedule (link above)
Lecturers: see schedule (link above)
Examination
A term paper of 6 000 to 8 000 words is required in addition to active participation during the lectures.
Deadline: see schedule (link above).
Important information for the participants: The course will be divided in two parts: (1) Innovation and well-being; (2) Innovation, inequality and social welfare. Participants who like to take the exam and get the credits for their PhD program must attend both parts of the course and submit a term paper. On the other hand, participants who do not wish to take the exam are welcome to attend only the part of the course of their interest.
Language of examination
The examination text is given in English, and you submit your response in English.
Grading scale
Grades are awarded on a pass/fail scale. Read more about the grading system.
More about examinations at UiO
- Use of sources and citations
- Special exam arrangements due to individual needs
- Withdrawal from an exam
- Illness at exams / postponed exams
- Explanation of grades and appeals
- Resitting an exam
- Cheating/attempted cheating
You will find further guides and resources at the web page on examinations at UiO.