Austrian Research and Technology Report 2020

Fig. 3-1: Areas of AI research
Planning and 
decision-making
Fuzzy 
systems
Search and 
optimisation
Machine learning and
probabilistic reasoning
Neural networks
Computer vision 
Natural language processing 
and knowledge representation
Source: de Kleijn (2018), revised.

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Austrian Research and Technology Report 2020
Consequently, we can also make a rough categori-
sation of AI based on 
technology and areas of ap-
plication,
which can be understood as a pragmatic 
grouping:
• knowledge-based systems (which work primarily 
using symbols with linguistic connotations and 
with logical and database methods);
• learning systems (especially the kind of numerical 
and statistical methods used in neural networks);
• robotics (potentially restricted to autonomous 
and smart robot systems as distinct from tradi-
tional industrial robotics) and autonomous driving;
• pattern recognition, image processing and video 
analysis (or image understanding methods);
• speech processing systems (both generating and 
analysing text and speech).
The use of AI will undoubtedly bring about funda-
mental disruptive changes to the relevant societies 
in all manner of different areas. AI is also seen as 
harbouring the potential to help solve the big socie-
tal challenges.
143
The corresponding areas of applica-
tion are varied and diverse.
In November 2018, therefore, an Austrian Council 
of Ministers approved a resolution for a federal strat-
egy with the working title of “
Artificial Intelligence 
Mission Austria 2030 (AIM AT 2030)
”, which estab-
lishes a framework for the use of AI in all areas of life. 
This was based on the definition of artificial intelli-
gence agreed by the Austrian Council for Robotics 
and Artificial Intelligence (ACRAI): 
“Artificial intelli-
gence (AI) refers to systems with ‘intelligent’ be-
haviour that analyse their environment and act with 
a certain degree of autonomy in order to achieve 
specific objectives.”
144
A broad-based discussion process was thus 
launched that was designed to enable as many ex-
perts and other interested parties as possible to be 
active participants. It was underpinned by an analy-
143 See Austrian Council on Robotics and Artificial Intelligence (2019). 
144 ibid.
145 See Federal Ministry for Transport, Innovation and Technology (BMVIT) and Federal Ministry for Digital and Economic Affairs 
(BMDW) (2019b).
146 See Federal Chancellery (BKA) (2020).
sis of the current situation in Austria and an interna-
tional comparison with the pioneers in the AI field. 
One initial outcome of this process was the finding 
that Austria already enjoys a very good position in 
some niches (e.g. machine learning, robotics and au-
tonomous systems). Experts were then invited to join 
one of seven working groups to contribute their spe-
cific skills. As well as the various fields of activity, 
discussions centred mainly around the options for 
action, which were to be combined to form potential 
strategies for Austria. The findings from all the work-
ing groups were subsequently discussed with all the