Algorithms – step-by-step sequences of operations that solve specific computational tasks – are transforming the world around us. They support sophisticated search engines, voice recognition software, online transactions, data compression, targeted advertising and self-driving cars. But algorithms also shape our biosphere – the global ecosystem and its thin layer of life on our planet that underpins human development.



The influence of algorithms was already coming into focus during the mid-1980s when the “hole” in the ozone layer was discovered. It turned out that the hole been overlooked for almost a decade because extremely low ozone concentrations recorded by monitoring satellites were systematically discarded by the computer’s algorithm. This delayed the response to one of the most potentially serious environmental crises in human history by several years.

Now, 30 years later, algorithms are all around us. They are embedded in artificial intelligence, machine learning, logistics, remote sensing and risk modeling, and permeate all domains of technology. As a result, they consistently and subtly shape human behavior and our influence on the world’s landscapes, oceans, air and ecosystems. Algorithms are critical ingredients in devices and services that affect our behavior – what we buy, what we consume, and how we travel. The “we” being those who can afford to consume and travel, of course.

Yet the growing influence of algorithms is truly global. Algorithms underpin almost all environmental monitoring technologies. They support the globally spanning infrastructure networks that continuously extract natural resources such as rare minerals, fossil fuels and living marine resources. And they even conduct millisecond automatic trades with financial instruments for commodities such as wheat, rice and soybeans.

We have reached a point in time when algorithms such as these deserve more scrutiny. Negative effects caused by the increasing influence of algorithms may be unintentional, and emerge unexpectedly only after considerable time. Developing algorithms that provide benefits to the few while presenting risks to the many are both unjust and unfair.

Historically, sets of principles have proven critical in guiding future development around novel technologies and their social implications. The Asilomar Conference on Recombinant DNA (1975) and the more recent “Oxford Principles” for risky geo-engineering technologies (2009) show that principles can have a profound social and political impact. Any scholar of environmental law knows of the deep mark the Precautionary Principle and the Principle of Common but Differentiated Responsibility has left on international law. In this spirit, we have formulated a set of 7 principles - “The Biosphere Code.”

A dialogue about possible principles to direct the use of algorithms needs to start now. As part of the ongoing international conference “Transformations 2015” in Stockholm, we gathered a small group of thinkers and doers – scholars, programmers, artists, entrepreneurs, game developers and others – to explore these possible principles for the development of algorithms that helps us protect and strengthen our ecosystems, and improve our creative capacities to sustain human well-being in an uncertain future. They are applicable to programmers, hackers, software companies, computer scientists, artists, designers, policy-makers and others taking active part of the algorithm revolution. The seven principles captured in the Biosphere Code Manifesto v1.0 (full version available here) are:



Principle 1. With great algorithmic powers come great responsibilities

Those implementing and using algorithms should consider the impacts of their algorithms.

Principle 2. Algorithms should serve humanity and the biosphere at large.

Algorithms should be considerate of human needs and the biosphere, and facilitate transformations towards sustainability by supporting ecologically responsible innovation.

Principle 3. The benefits and risks of algorithms should be distributed fairly

Algorithm developers should consider issues relating to the distribution of risks and opportunities more seriously. Developing algorithms that provide benefits to the few and present risks to the many are both unjust and unfair.

Principle 4. Algorithms should be flexible, adaptive and context-aware

Algorithms should be open, malleable and easy to reprogram if serious repercussions or unexpected results emerge. Algorithms should be aware of their external effects and be able to adapt to unforeseen changes.

Principle 5. Algorithms should help us expect the unexpected

Algorithms should be used in such a way that they enhance our shared capacity to deal with shocks and surprises - including problems caused by errors or misbehaviors in other algorithms.

Principle 6. Algorithmic data collection should be open and meaningful

Data collection should be transparent and respectful of public privacy. In order to avoid hidden biases, the datasets which feed into algorithms should be validated.

Principle 7. Algorithms should be inspiring, playful and beautiful

Algorithms should be used to enhance human creativity and playfulness, and to create new kinds of art. We should encourage algorithms that facilitate human collaboration, interaction and engagement - with each other, with society, and with nature.

These principles should be viewed as work in progress. Without principles such as these, the risk is all too imminent that the algorithm revolution will push us into a future “Internet of Way Too Many Stupid Things” – a growing pile of hyperconnected, sophisticated, but meaningless toys that systematically undermine the Earth system’s ability to support human development for all. Surely we can do a lot better than that.

The principles presented here are the result of discussions that took place at the event “The Biosphere Code” in Stockholm October 4th, 2015. Contributors include (in alphabetical order) Maja Brisvall (Quantified Planet), Palle Dahlstedt (University of Gothenburg, Aalborg University), Victor Galaz (Stockholm Resilience Centre, Stockholm University), Daniel Hassan (Robin Hood Minor Asset Management Cooperative), Koert van Mensvoort (Next Nature Network, Eindhoven University of Technology), Andrew Merrie (Stockholm Resilience Centre, Stockholm University), Fredrik Moberg (Albaeco/ Stockholm Resilience Centre, Stockholm University), Anders Sandberg (University of Oxford), Peter Svensson (Evothings.com), Ann-Sofie Sydow (The Game Assembly), Robin Teigland (Stockholm School of Economics), and Fernanda Torre (Stockholm Resilience Centre).