User:Alexander Roidl/thesis-outline2

Thesis Outline

Thesis Statement

Topic

Ways of understanding complex algorithms. Ways of understanding machine learning algorithms. trough reverse engineering.

Reverse Engineering Algorithmic Images

Visual Interventions

Focus

in times of machine learning

Argument

Machine Learning is intervening in our visual world.

Revise

Machine Learning is increasingly intervening in our visual world. Algorithms analyse images, process data and even generate new images.

Scope

»Intelligent« algorithms are everywhere and they challenge the way we see. They generate new kinds of images that raise a new meaning and understanding of the world. How can we understand these algorithms in order to understand their influence on our visual perception.

Outline

Body

Image Language

On the visible and invisible

• Computer vision
  • How we help computers to help them see
  • Therefore: how computers help us see
    • Computer challenge what and how we see
    • Machines see things that remain invisible for humans
      • Relatable to images or models or databases or technology and lack of understanding

Understanding Images

• Images as analytical tools
• Features of images and how we talk about images

Towards endless image production

• The computer allows to generate every imaginable image (imagination = image)
• From mechanical reproduction to mechanical production

(Do not know where to put this questions:)

• machine to machine, why would they need vision?
• why do we need images?

Conclusion

Images change the way we perceive the world and therefore we need to be able to understand the way images are being created.

Turn it around! From specific problem > more broader terms