Digital authenticity: how to spot AI-generated content

In today’s digital age, we often question whether we can trust images, videos, or texts. Tracing the source of information is becoming more and more difficult. Generative AI accelerates the creation of content at an incredible pace. Images and audio files that once required a skilled artist can now be generated by AI models in a matter of seconds. Models like OpenAI’s Sora can even produce high-quality videos!

This technology offers both opportunities and risks. On the one hand, it speeds up creative processes, but on the other hand, it can be misused for malicious purposes, such as phishing attacks or creating deceptively real deepfake videos. So how can we ensure that the content shared online is genuine?

Digital watermarks: invisible protection for content

Digital watermarks are one solution that helps verify the origin of images, videos, or audio files. These patterns are invisible to the human eye but can be detected by algorithms even after minor changes, like compressing or cropping an image, and are difficult to remove. They are primarily used to protect copyright.

However, applying watermarks to text is way more difficult because text has less redundancy than pixels in images. A related method is to insert small but visible errors into the original content. Google Maps, for instance, uses this method with fictional streets – if these streets appear in a copy, it signals copyright infringement.

Digital signatures: security through cryptography

Digital signatures are based on asymmetric cryptography. This means that the content is signed with a private key that only the creator possesses. Others can verify the authenticity of the content using a public key. Even the smallest alteration to the content invalidates the signature, making it nearly impossible to forge. Digital signatures already ensure transparency in online communication, for example through the HTTPS protocol for secure browsing.

In a world where all digital content would be protected by signatures, the origin and authenticity of any piece of media could be easily verified. For example, you could confirm who took a photo, when, and where. An initiative pushing this forward is the Coalition for Content Provenance and Authenticity (C2PA), which is developing technical standards to apply digital signatures to media and document its origin. Unlike watermarks, signatures are not permanently embedded into the content itself and can be removed without altering the material. In an ideal scenario, everyone would use digital signatures – then, missing signatures would raise doubts about the trustworthiness of the content.

GenAI detectors: AI vs. AI

GenAI detectors provide another way to recognize generated content. AI models are algorithms that leave behind certain patterns, such as specific wording or sentence structures. Other AI models can detect these. Tools like GPTZero can already identify with high accuracy whether a text originates from a generative AI model like ChatGPT or Gemini. While these detectors are not perfect yet, they provide an initial indication.

What does this mean for users?

Of all the options, digital signatures offer the strongest protection because they work across all types of content and are based on cryptographic methods. It will be interesting to see if projects like C2PA can establish trusted standards. Still, different measures may be needed depending on the purpose of ensuring the trustworthiness of digital content.
In addition to technological solutions, critical thinking remains one of the best tools for navigating the information age. The amount of available information is constantly growing; therefore, it is important to critically question, verify, and be aware of the capabilities of generative AI models.

For a more comprehensive article, check out the CONTACT Research Blog.

Scope 3 emissions: A challenge for companies

Reducing greenhouse gas (GHG) emissions is crucial in the fight against climate change. Many companies face the challenge that indirect emissions in their value chain, so-called Scope 3 emissions, are often the largest contributors. Since these emissions fall outside the direct control of the company, they are usually the most difficult to determine (and optimize). How can companies address these central challenges within their value chains?

What are Scope 1, 2, and 3 emissions?

The Greenhouse Gas (GHG) Protocol classifies emissions into three categories: Scope 1 for direct emissions from company-owned sources, Scope 2 for indirect emissions from purchased energy, and Scope 3 for all other indirect emissions, including those from upstream and downstream processes within the value chain. Scope 3 is particularly important because it often accounts for the majority of GHG emissions. The GHG Protocol defines 15 categories of Scope 3 emissions that arise from both upstream and downstream activities. These include raw material extraction, production and transportation of purchased components, and the use of the manufactured products by end consumers. These emissions are difficult to capture as they are not directly under the company’s control.

Corporate Carbon Footprint (CCF) vs. Product Carbon Footprint (PCF)

There are two central approaches to calculating emissions: the Corporate Carbon Footprint (CCF), which encompasses all activities of a company, and the Product Carbon Footprint (PCF), which focuses on the lifecycle of a specific product. The PCF is particularly important when it comes to determining emissions along the value chain. Companies that aim to measure their Scope 3 emissions also need data from their suppliers regarding the PCF of the components they purchase.

Why is measuring Scope 3 emissions important?

Companies can directly influence and therefore more easily calculate Scope 1 and Scope 2 emissions. However, Scope 3 emissions should not be overlooked when aiming to assess the entire value chain. Since emissions from upstream and downstream processes often are the largest sources of GHGs, this is the only way to identify and reduce “hotspots” within the value chain.

For many SMEs, significant emissions lie in the upstream processes. However, this is also particularly relevant for industries that rely on complex and globally distributed supply chains. The automotive industry, for instance, depends heavily on purchased components and services, which significantly impact the GHG balance. According to the study “Climate-Friendly Production in the Automotive Industry” by the Öko-Institut e.V., an average of 74.8% of Scope 3 emissions occur during the usage phase, while in-house production (Scope 1 and 2 emissions) only accounts for about 1.9%, and 18.6% originate from the upstream value chain with purchased components. As the industry focuses more and more on e-mobility, the Scope 3 emissions of purchased components – and thus those from suppliers – come into sharper focus as a key lever.

Challenges in the supply chain

The pressure on suppliers to make their production more efficient and sustainable is growing, along with the need for transparency regarding the emissions of the supplied parts. Key challenges in the supply chain include data quality and availability. To tackle this and reduce greenhouse gas emissions, companies need to break new ground, ranging from material selection to production methods. A solid data foundation supports these necessary decisions, as well as the accurate documentation of emissions.
Capturing Scope 1 and Scope 2 emissions is already mandatory under the GHG Protocol Corporate Standard, while Scope 3 reporting is currently optional. However, the importance of Scope 3 reporting is increasing, as demonstrated by EU regulations like the Corporate Sustainability Reporting Directive (CSRD) and the associated European Standards (ESRS). These regulations emphasize the disclosure of emissions as a central aspect of climate action and sustainable business practices.

Three key steps to reduce Scope 3 emissions

  1. Optimize data management: Companies should collect comprehensive data on their products and their lifecycles to make design and portfolio decisions in favor of sustainability.
  2. Ensure data sovereignty and trust: Accurate calculation of Scope 3 emissions requires control over data, particularly in the context of the upstream and downstream value chains.
  3. Use open interfaces: Open data interfaces are essential for seamless integration and communication within the value chain. Approaches like the Asset Administration Shell (AAS) and concepts such as the Digital Product Passport (DPP) can provide valuable support.

Conclusion

Measuring and optimizing Scope 3 emissions is one of the greatest challenges for companies seeking to improve their GHG balance. By leveraging better data, optimizing collaboration within the supply chain, and ensuring transparent reporting, companies can meet regulatory requirements and make progress toward a more sustainable future.

Read a more detailed article on Scope 3 emissions on the CONTACT Research Blog.

Evaluating sustainability with the green digital twin

On January 5, 2023, the Corporate Sustainability Reporting Directive (CSRD) came into effect – but what exactly does that mean? The European Parliament adopted this regulation as a significant step within the European Green Deal framework of 2019. The ambitious goal: a carbon-neutral EU by 2050 – and thus the first carbon-neutral continent in the world.

CSRD and ESRS: challenges in reporting

The classification is based on environmental, social, and governance (ESG) criteria according to the EU taxonomy. Each of these three areas encompasses different guidelines and regulations. The CSRD specifically addresses environmental aspects and obliges companies across industries to act more sustainably. The European Sustainability Reporting Standards (ESRS) further specify how these obligations should be reported.

The challenge lies in recording and calculating the required environmental data, such as pollutant emissions, in accordance with ESRS KPIs. The question is: How can this data be collected efficiently and accurately?

Efficient data collection for sustainability

Environmental databases can support sustainability reporting, for example, the database for process-oriented basic data for environmental management instruments (ProBas) provided by the German Environment Agency (Umweltbundesamt, UBA).

The digital twin plays a crucial role as a useful helper. As a digital replica of products, machines, or components, it offers a comprehensive solution to the challenges of data collection in the context of the CSRD. By fully digitalizing the product passport, relevant data can be compiled throughout the entire product lifecycle. This enables both efficient data collection and transparent data sharing along the entire value chain.

From individual parts to the overall picture

The digital twin allows to consolidate information from environmental databases, ERP, MES, and material data management systems. Based on this data, the environmental impact of each component can be assessed with the Life Cycle Assessment (LCA) method. Taking a bicycle as an example, this includes the handlebar, fork, frame, saddle, pedals, and the two wheels with tires. The LCA metrics can be recorded for single components and the entire product. These individual parameters can be used to determine the carbon footprint across the entire value chain of the bike.

This data also forms the basis for the bike’s digital product passport. By fully digitalizing the product passport, the calculated environmental data can be easily shared, for example, with retailers or consumers.

Green digital twin for the aerospace industry

In the industrial sector, the aerospace industry is particularly affected by the CSRD. As part of the PredictECO research project, CONTACT Software is working with partners from science and industry on a green digital product twin that meets the new requirements. This includes the obligation to provide evidence in the form of a digital Lifecycle Data Sheet (LDS), which documents the materials and processes used down to the smallest detail. The goal is to create a comprehensive digital twin that contains all the necessary manufacturing information for sustainable production according to the requirements from the LDS and can provide them in a standardized digital form.

Outlook

The digital twin already proves to be a field-tested solution to meet the CSRD requirements of the CSRD. Collecting environmental data throughout the entire product lifecycle not only enables efficient reporting but also contributes to creating sustainable value chains. Take advantage of the opportunities the green digital twin offers to elevate sustainability in your company to a new level.

For more information on the green digital twin, read this article on the CONTACT Research Blog.