Course description

Artificial Intelligence, Algorithms and Society


Computers, Artificial Intelligence (AI) and Algorithms are dramatically changing the way we live, work and do business. The last years have seen unprecedented innovation in areas such as large-scale information processing, problem solving and machine learning. In various work contexts, computers can complete tasks not only – by an order of magnitude – faster than humans, they are also more efficient, more reliable, and they seem much more creative in devising adequate problem-solving strategies. AI and Algorithms are not only used to make sense of enormous amounts of existing data, but they can also be used to make predictions about the future – as such, they become a crucial tool for decision making. At the same time, AI and Algorithms have sparked heated and often contradictory discussions in the public sphere which encompass both dystopian and utopian narratives. Here, headlines range from rouge ‘killer robots’ or ‘artificial intelligences seeking world domination’ to solving ‘computers solving hunger, poverty and illiteracy’. Today’s decision-makers will not only have to use AI and Algorithms as a part of their daily work, but they also need to understand the public discourse surrounding these phenomena and be able to make educated and measured choices.

In this course, we will explore the foundational issues that comprises current developments in artificial intelligence, primarily form a philosophy of mind perspective. Based on a solid understanding of the interplay between minds and machines, we will the proceed conceptualizing future scenarios for business and society, and deliberate on the possible economic and ethical outcomes of these.

Course content

Introduction: Current and Future Use of Artificial Intelligence

Challenges resulting from and solved through AI in Business and Society

Scenario Techniques and How to Map Possible Futures

Foundational Issues on Minds and Machines

  • (Reverse-) engineering human intelligence
  • Bodies, Minds and Machines
  • From embodied to abstract machines
  • Machines for natural language grammars
  • Brains as Machines
  • Rules and Representations
  • The probabilistic language of thought
  • Decision and the brain
  • Bayesian inference, concept learning, and nativism
  • Neural Networks
  • Deep Machine Learning
  • Bats, zombies and qualia

Future Scenarios: Poster Presentation and Discussion

Learning outcome knowledge

The goal of this course is to enable participants to take on an informed and measured stance vis-a-vis new technologies in general and AI and algorithms in particular.

  • What are the philosophical foundations of intelligence, consciousness and mind?
  • What are Computers, AI and Algorithms capable of – and where are their (current) limitations?
  • What are ethical implications of Computers, AI and Algorithms as either tools or agents in modern work and living environments?
  • Which trajectory will Computer, AI and Algorithmic development take? Which are the best-case and which are the worst-case scenarios?
  • How can we manage Computers, AI and Algorithms in the modern workplace?

Exam organisation

  • Written assignment: 50%
  • Presentation: 25%
  • Written assignment: 25%