Back to all Blog Posts

How the AI Act will change the AI industry: Everything you need to know about it now

  • Artificial Intelligence
  • Human-centered AI
  • Strategy
11. May 2023
·

Team statworx

Last December, the European Council published a dossier outlining the Council’s preliminary position on the draft law known as the AI Act. This new law is intended to regulate artificial intelligence (AI) and thus becomes a game-changer for the entire tech industry. In the following, we have compiled the most important information from the dossier, which is the current official source on the planned AI Act at the time of publication.

A legal framework for AI

Artificial intelligence has enormous potential to improve and ease all our lives. For example, AI algorithms already support early cancer detection or translate sign language in real time, thereby eliminating language barriers. But in addition to the positive effects, there are risks, as the latest deep fakes from Pope Francis or the Cambridge Analytica scandal illustrate.

The European Union (EU) is currently drafting legislation to regulate artificial intelligence to mitigate the risks of artificial intelligence. With this, the EU wants to protect consumers and ensure the ethically acceptable use of artificial intelligence. The so-called “AI Act” is still in the legislative process but is expected to be passed in 2023 – before the end of the current legislative period. Companies will then have two years to implement the legally binding requirements. Violations will be punished with fines of up to 6% of global annual turnover or €30,000,000 – whichever is higher. Therefore, companies should already start addressing the upcoming legal requirements now.

Legislation with global impact

The planned AI Act is based on the “location principle, ” meaning that not only European companies will be affected by the amendment. Thus, all companies that offer AI systems on the European market or also operate them for internal use within the EU are affected by the AI Act – with a few exceptions. Private use of AI remains untouched by the regulation so far.

Which AI systems are affected?

The definition of AI determines which systems will be affected by the AI Act. For this reason, the AI definition of the AI Act has been the subject of controversial debate in politics, business, and society for a considerable time. The initial definition was so broad that many “normal” software systems would also have been affected. The current proposal defines AI as any system developed through machine learning or logic- and knowledge-based approaches. It remains to be seen whether this definition will ultimately be adopted.

7 Principles for trustworthy AI

The “seven principles for trustworthy AI” are the most important basis of the AI Act. A group of experts from research, the digital economy, and associations developed them on behalf of the European Commission. They include not only technical aspects but also social and ethical factors that can be used to classify the trustworthiness of an AI system:

  1. Human action & oversight: decision-making should be supported without undermining human autonomy.
  2. Technical Robustness & security: accuracy, reliability, and security must be preemptively ensured.
  3. Data privacy & data governance: handling of data must be legally secure and protected.
  4. Transparency: interaction with AI must be clearly communicated, as must its limitations and boundaries.
  5. Diversity, non-discrimination & fairness: Avoidance of unfair bias must be ensured throughout the entire AI lifecycle.
  6. Environmental & societal well-being: AI solutions should have a positive impact on the environment and society as possible.
  7. Accountability: responsibilities for the development, use, and maintenance of AI systems must be defined.

Based on these principles, the AI Act’s risk-based approach was developed, allowing AI systems to be classified into one of four risk classes: low, limited, high, and unacceptable risk.

Four risk classes for trustworthy AI

The risk class of an AI system indicates the extent to which an AI system threatens the principles of trustworthy AI and which legal requirements the system must fulfill – provided the system is fundamentally permissible. This is because, in the future, not all AI systems will be allowed on the European market. For example, most “social scoring” techniques are assessed as “unacceptable” and will not be allowed by the new law.

For the other three risk classes, the rule of thumb is that the higher the risk of an AI system, the higher the legal requirements for it. Companies that offer or operate high-risk systems will have to meet the most requirements. For example, AI used to operate critical (digital) infrastructure or used in medical devices is considered such. To bring these to market, companies will have to observe high-quality standards for the used data, set up a risk management, affix a CE mark, and more.

AI systems in the “limited risk” class are subject to information and transparency obligations. Accordingly, companies must inform users of chatbots, emotion recognition systems, or deep fakes about the use of artificial intelligence. Predictive maintenance or spam filters are two examples of AI systems that fall into the lowest-risk category “low risk”. Companies that exclusively offer or use such AI solutions will hardly be affected by the upcoming AI Act. There are no legal requirements for these applications yet.

What companies can do for now

Even though the AI Act is still in the legislative process, companies should act now. The first step is to clarify how they will be affected by the AI Act. To help you do this, we have developed the AI Act Quick Check. With this free tool, AI systems can be quickly assigned to a risk class free of charge, and requirements for the system can be derived. Finally, it can be used as a basis to estimate how extensive the realization of the AI Act will be in your own company and to take initial measures. Of course, we are also happy to support you in evaluating and solving company-specific challenges related to the AI Act. Please do not hesitate to contact us!

AI ACT TOOL     AI ACT FACT SHEET

Links & Sources:

Linkedin Logo
Marcel Plaschke
Head of Strategy, Sales & Marketing
schedule a consultation
Zugehörige Leistungen
No items found.

More Blog Posts

  • Artificial Intelligence
AI Trends Report 2025: All 16 Trends at a Glance
Tarik Ashry
05. February 2025
Read more
  • Artificial Intelligence
  • Data Science
  • Human-centered AI
Explainable AI in practice: Finding the right method to open the Black Box
Jonas Wacker
15. November 2024
Read more
  • Artificial Intelligence
  • Data Science
  • GenAI
How a CustomGPT Enhances Efficiency and Creativity at hagebau
Tarik Ashry
06. November 2024
Read more
  • Artificial Intelligence
  • Data Culture
  • Data Science
  • Deep Learning
  • GenAI
  • Machine Learning
AI Trends Report 2024: statworx COO Fabian Müller Takes Stock
Tarik Ashry
05. September 2024
Read more
  • Artificial Intelligence
  • Human-centered AI
  • Strategy
The AI Act is here – These are the risk classes you should know
Fabian Müller
05. August 2024
Read more
  • Artificial Intelligence
  • GenAI
  • statworx
Back to the Future: The Story of Generative AI (Episode 4)
Tarik Ashry
31. July 2024
Read more
  • Artificial Intelligence
  • GenAI
  • statworx
Back to the Future: The Story of Generative AI (Episode 3)
Tarik Ashry
24. July 2024
Read more
  • Artificial Intelligence
  • GenAI
  • statworx
Back to the Future: The Story of Generative AI (Episode 2)
Tarik Ashry
04. July 2024
Read more
  • Artificial Intelligence
  • GenAI
  • statworx
Back to the Future: The Story of Generative AI (Episode 1)
Tarik Ashry
10. July 2024
Read more
  • Artificial Intelligence
  • GenAI
  • statworx
Generative AI as a Thinking Machine? A Media Theory Perspective
Tarik Ashry
13. June 2024
Read more
  • Artificial Intelligence
  • GenAI
  • statworx
Custom AI Chatbots: Combining Strong Performance and Rapid Integration
Tarik Ashry
10. April 2024
Read more
  • Artificial Intelligence
  • Data Culture
  • Human-centered AI
How managers can strengthen the data culture in the company
Tarik Ashry
21. February 2024
Read more
  • Artificial Intelligence
  • Data Culture
  • Human-centered AI
AI in the Workplace: How We Turn Skepticism into Confidence
Tarik Ashry
08. February 2024
Read more
  • Artificial Intelligence
  • Data Science
  • GenAI
The Future of Customer Service: Generative AI as a Success Factor
Tarik Ashry
25. October 2023
Read more
  • Artificial Intelligence
  • Data Science
How we developed a chatbot with real knowledge for Microsoft
Isabel Hermes
27. September 2023
Read more
  • Data Science
  • Data Visualization
  • Frontend Solution
Why Frontend Development is Useful in Data Science Applications
Jakob Gepp
30. August 2023
Read more
  • Artificial Intelligence
  • Human-centered AI
  • statworx
the byte - How We Built an AI-Powered Pop-Up Restaurant
Sebastian Heinz
14. June 2023
Read more
  • Artificial Intelligence
  • Recap
  • statworx
Big Data & AI World 2023 Recap
Team statworx
24. May 2023
Read more
  • Data Science
  • Human-centered AI
  • Statistics & Methods
Unlocking the Black Box – 3 Explainable AI Methods to Prepare for the AI Act
Team statworx
17. May 2023
Read more
  • Artificial Intelligence
  • Human-centered AI
  • Machine Learning
Gender Representation in AI – Part 2: Automating the Generation of Gender-Neutral Versions of Face Images
Team statworx
03. May 2023
Read more
  • Artificial Intelligence
  • Data Science
  • Statistics & Methods
A first look into our Forecasting Recommender Tool
Team statworx
26. April 2023
Read more
  • Artificial Intelligence
  • Data Science
On Can, Do, and Want – Why Data Culture and Death Metal have a lot in common
David Schlepps
19. April 2023
Read more
  • Artificial Intelligence
  • Human-centered AI
  • Machine Learning
GPT-4 - A categorisation of the most important innovations
Mareike Flögel
17. March 2023
Read more
  • Artificial Intelligence
  • Data Science
  • Strategy
Decoding the secret of Data Culture: These factors truly influence the culture and success of businesses
Team statworx
16. March 2023
Read more
  • Artificial Intelligence
  • Deep Learning
  • Machine Learning
How to create AI-generated avatars using Stable Diffusion and Textual Inversion
Team statworx
08. March 2023
Read more
  • Artificial Intelligence
  • Human-centered AI
  • Strategy
Knowledge Management with NLP: How to easily process emails with AI
Team statworx
02. March 2023
Read more
  • Artificial Intelligence
  • Deep Learning
  • Machine Learning
3 specific use cases of how ChatGPT will revolutionize communication in companies
Ingo Marquart
16. February 2023
Read more
  • Recap
  • statworx
Ho ho ho – Christmas Kitchen Party
Julius Heinz
22. December 2022
Read more
  • Artificial Intelligence
  • Deep Learning
  • Machine Learning
Real-Time Computer Vision: Face Recognition with a Robot
Sarah Sester
30. November 2022
Read more
  • Data Engineering
  • Tutorial
Data Engineering – From Zero to Hero
Thomas Alcock
23. November 2022
Read more
  • Recap
  • statworx
statworx @ UXDX Conf 2022
Markus Berroth
18. November 2022
Read more
  • Artificial Intelligence
  • Machine Learning
  • Tutorial
Paradigm Shift in NLP: 5 Approaches to Write Better Prompts
Team statworx
26. October 2022
Read more
  • Recap
  • statworx
statworx @ vuejs.de Conf 2022
Jakob Gepp
14. October 2022
Read more
  • Data Engineering
  • Data Science
Application and Infrastructure Monitoring and Logging: metrics and (event) logs
Team statworx
29. September 2022
Read more
  • Coding
  • Data Science
  • Machine Learning
Zero-Shot Text Classification
Fabian Müller
29. September 2022
Read more
  • Cloud Technology
  • Data Engineering
  • Data Science
How to Get Your Data Science Project Ready for the Cloud
Alexander Broska
14. September 2022
Read more
  • Artificial Intelligence
  • Human-centered AI
  • Machine Learning
Gender Repre­sentation in AI – Part 1: Utilizing StyleGAN to Explore Gender Directions in Face Image Editing
Isabel Hermes
18. August 2022
Read more
  • Artificial Intelligence
  • Human-centered AI
statworx AI Principles: Why We Started Developing Our Own AI Guidelines
Team statworx
04. August 2022
Read more
  • Data Engineering
  • Data Science
  • Python
How to Scan Your Code and Dependencies in Python
Thomas Alcock
21. July 2022
Read more
  • Data Engineering
  • Data Science
  • Machine Learning
Data-Centric AI: From Model-First to Data-First AI Processes
Team statworx
13. July 2022
Read more
  • Artificial Intelligence
  • Deep Learning
  • Human-centered AI
  • Machine Learning
DALL-E 2: Why Discrimination in AI Development Cannot Be Ignored
Team statworx
28. June 2022
Read more
  • R
The helfRlein package – A collection of useful functions
Jakob Gepp
23. June 2022
Read more
  • Recap
  • statworx
Unfold 2022 in Bern – by Cleverclip
Team statworx
11. May 2022
Read more
  • Artificial Intelligence
  • Data Science
  • Human-centered AI
  • Machine Learning
Break the Bias in AI
Team statworx
08. March 2022
Read more
  • Artificial Intelligence
  • Cloud Technology
  • Data Science
  • Sustainable AI
How to Reduce the AI Carbon Footprint as a Data Scientist
Team statworx
02. February 2022
Read more
  • Recap
  • statworx
2022 and the rise of statworx next
Sebastian Heinz
06. January 2022
Read more
  • Recap
  • statworx
5 highlights from the Zurich Digital Festival 2021
Team statworx
25. November 2021
Read more
  • Data Science
  • Human-centered AI
  • Machine Learning
  • Strategy
Why Data Science and AI Initiatives Fail – A Reflection on Non-Technical Factors
Team statworx
22. September 2021
Read more
  • Artificial Intelligence
  • Data Science
  • Human-centered AI
  • Machine Learning
  • statworx
Column: Human and machine side by side
Sebastian Heinz
03. September 2021
Read more
  • Coding
  • Data Science
  • Python
How to Automatically Create Project Graphs With Call Graph
Team statworx
25. August 2021
Read more
  • Coding
  • Python
  • Tutorial
statworx Cheatsheets – Python Basics Cheatsheet for Data Science
Team statworx
13. August 2021
Read more
  • Data Science
  • statworx
  • Strategy
STATWORX meets DHBW – Data Science Real-World Use Cases
Team statworx
04. August 2021
Read more
  • Data Engineering
  • Data Science
  • Machine Learning
Deploy and Scale Machine Learning Models with Kubernetes
Team statworx
29. July 2021
Read more
  • Cloud Technology
  • Data Engineering
  • Machine Learning
3 Scenarios for Deploying Machine Learning Workflows Using MLflow
Team statworx
30. June 2021
Read more
  • Artificial Intelligence
  • Deep Learning
  • Machine Learning
Car Model Classification III: Explainability of Deep Learning Models With Grad-CAM
Team statworx
19. May 2021
Read more
  • Artificial Intelligence
  • Coding
  • Deep Learning
Car Model Classification II: Deploying TensorFlow Models in Docker Using TensorFlow Serving
No items found.
12. May 2021
Read more
  • Coding
  • Deep Learning
Car Model Classification I: Transfer Learning with ResNet
Team statworx
05. May 2021
Read more
  • Artificial Intelligence
  • Deep Learning
  • Machine Learning
Car Model Classification IV: Integrating Deep Learning Models With Dash
Dominique Lade
05. May 2021
Read more
  • AI Act
Potential Not Yet Fully Tapped – A Commentary on the EU’s Proposed AI Regulation
Team statworx
28. April 2021
Read more
  • Artificial Intelligence
  • Deep Learning
  • statworx
Creaition – revolutionizing the design process with machine learning
Team statworx
31. March 2021
Read more
  • Artificial Intelligence
  • Data Science
  • Machine Learning
5 Types of Machine Learning Algorithms With Use Cases
Team statworx
24. March 2021
Read more
  • Recaps
  • statworx
2020 – A Year in Review for Me and GPT-3
Sebastian Heinz
23. Dezember 2020
Read more
  • Artificial Intelligence
  • Deep Learning
  • Machine Learning
5 Practical Examples of NLP Use Cases
Team statworx
12. November 2020
Read more
  • Data Science
  • Deep Learning
The 5 Most Important Use Cases for Computer Vision
Team statworx
11. November 2020
Read more
  • Data Science
  • Deep Learning
New Trends in Natural Language Processing – How NLP Becomes Suitable for the Mass-Market
Dominique Lade
29. October 2020
Read more
  • Data Engineering
5 Technologies That Every Data Engineer Should Know
Team statworx
22. October 2020
Read more
  • Artificial Intelligence
  • Data Science
  • Machine Learning

Generative Adversarial Networks: How Data Can Be Generated With Neural Networks
Team statworx
10. October 2020
Read more
  • Coding
  • Data Science
  • Deep Learning
Fine-tuning Tesseract OCR for German Invoices
Team statworx
08. October 2020
Read more
  • Artificial Intelligence
  • Machine Learning
Whitepaper: A Maturity Model for Artificial Intelligence
Team statworx
06. October 2020
Read more
  • Data Engineering
  • Data Science
  • Machine Learning
How to Provide Machine Learning Models With the Help Of Docker Containers
Thomas Alcock
01. October 2020
Read more
  • Recap
  • statworx
STATWORX 2.0 – Opening of the New Headquarters in Frankfurt
Julius Heinz
24. September 2020
Read more
  • Machine Learning
  • Python
  • Tutorial
How to Build a Machine Learning API with Python and Flask
Team statworx
29. July 2020
Read more
  • Data Science
  • Statistics & Methods
Model Regularization – The Bayesian Way
Thomas Alcock
15. July 2020
Read more
  • Recap
  • statworx
Off To New Adventures: STATWORX Office Soft Opening
Team statworx
14. July 2020
Read more
  • Data Engineering
  • R
  • Tutorial
How To Dockerize ShinyApps
Team statworx
15. May 2020
Read more
  • Coding
  • Python
Making Of: A Free API For COVID-19 Data
Sebastian Heinz
01. April 2020
Read more
  • Frontend
  • Python
  • Tutorial
How To Build A Dashboard In Python – Plotly Dash Step-by-Step Tutorial
Alexander Blaufuss
26. March 2020
Read more
  • Coding
  • R
Why Is It Called That Way?! – Origin and Meaning of R Package Names
Team statworx
19. March 2020
Read more
  • Data Visualization
  • R
Community Detection with Louvain and Infomap
Team statworx
04. March 2020
Read more
  • Coding
  • Data Engineering
  • Data Science
Testing REST APIs With Newman
Team statworx
26. February 2020
Read more
  • Coding
  • Frontend
  • R
Dynamic UI Elements in Shiny – Part 2
Team statworx
19. Febuary 2020
Read more
  • Coding
  • Data Visualization
  • R
Animated Plots using ggplot and gganimate
Team statworx
14. Febuary 2020
Read more
  • Machine Learning
Machine Learning Goes Causal II: Meet the Random Forest’s Causal Brother
Team statworx
05. February 2020
Read more
  • Artificial Intelligence
  • Machine Learning
  • Statistics & Methods
Machine Learning Goes Causal I: Why Causality Matters
Team statworx
29.01.2020
Read more
  • Data Engineering
  • R
  • Tutorial
How To Create REST APIs With R Plumber
Stephan Emmer
23. January 2020
Read more
  • Recaps
  • statworx
statworx 2019 – A Year in Review
Sebastian Heinz
20. Dezember 2019
Read more
  • Artificial Intelligence
  • Deep Learning
Deep Learning Overview and Getting Started
Team statworx
04. December 2019
Read more
  • Coding
  • Machine Learning
  • R
Tuning Random Forest on Time Series Data
Team statworx
21. November 2019
Read more
  • Data Science
  • R
Combining Price Elasticities and Sales Forecastings for Sales Improvement
Team statworx
06. November 2019
Read more
  • Data Engineering
  • Python
Access your Spark Cluster from Everywhere with Apache Livy
Team statworx
30. October 2019
Read more
  • Recap
  • statworx
STATWORX on Tour: Wine, Castles & Hiking!
Team statworx
18. October 2019
Read more
  • Data Science
  • R
  • Statistics & Methods
Evaluating Model Performance by Building Cross-Validation from Scratch
Team statworx
02. October 2019
Read more
  • Data Science
  • Machine Learning
  • R
Time Series Forecasting With Random Forest
Team statworx
25. September 2019
Read more
  • Coding
  • Frontend
  • R
Dynamic UI Elements in Shiny – Part 1
Team statworx
11. September 2019
Read more
  • Machine Learning
  • R
  • Statistics & Methods
What the Mape Is FALSELY Blamed For, Its TRUE Weaknesses and BETTER Alternatives!
Team statworx
16. August 2019
Read more
  • Coding
  • Python
Web Scraping 101 in Python with Requests & BeautifulSoup
Team statworx
31. July 2019
Read more
  • Coding
  • Frontend
  • R
Getting Started With Flexdashboards in R
Thomas Alcock
19. July 2019
Read more
  • Recap
  • statworx
statworx summer barbecue 2019
Team statworx
21. June 2019
Read more
  • Data Visualization
  • R
Interactive Network Visualization with R
Team statworx
12. June 2019
Read more
  • Deep Learning
  • Python
  • Tutorial
Using Reinforcement Learning to play Super Mario Bros on NES using TensorFlow
Sebastian Heinz
29. May 2019
Read more
This is some text inside of a div block.
This is some text inside of a div block.