Hasso-Plattner-InstitutSDG am HPI
Hasso-Plattner-InstitutDSG am HPI


Towards Sustainable Digital Technologies

Artificial intelligence, blockchain, big data analysis and ubiquitous data exchange. Digital transformation permeates our everyday lives around the world and is the key to solving global human challenges, such as climate change, poverty and economic prosperity for all. However, is digitalization ecologically sustainable? No, currently it is not – but this has to change now!

What is the problem?

Innovative business models and the transformation of entire economic sectors are almost exclusively based on the use of AI, Big Data, Blockchain and globally interconnected data centers. The greatest potential for growth lies in two areas: digital services, through the consistent development of digital platforms and in manufacturing by leveraging the opportunities of the Internet of  things. Individual products and services can be offered at the price of mass goods, thus increasing global prosperity. However, it is often ignored that digital technologies are also increasingly
the cause of global pollution. Every digital operation consumes energy and therefore adds to the global CO2 footprint. Very soon, digitalization will become the climate problem number one.

Graphic: HPI clean IT - AI Carbon
Artificial intelligence emissions Training a modern AI model can use up as much carbon as 300 roundtrip flights from SFO-NYC or the life cycle of 5 cars incl. fuel. / Strubell et al. 2019

How clean-IT works

Graphic: HPI clean IT: How it works

To solve the paradox of more from less, the principle of “Sustainability by Design” needs to become the very foundation of software development. Often unnecessarily complicated or wasteful IT systems design causes higher energy consumption compared to algorithmic setups that are more efficient. Innovative IT architectures can achieve the same/slightly lower precision or data throughput, while saving enormous amounts of energy. Algorithmic efficiency therefore needs to become a leading paradigm of software development. We call this  approach clean-IT.

Examples of clean-IT

Binary Neural Networks

Data Profiling with HPIValid

Heuristic Algorithms for Optimization of Submodular Functions

Energy-Aware Computing